From a644f89d630ed5455027d46fd26f0db4897e3b52 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 01/74] Basic dockstore manifest creation --- scripts/workflow_manifest.py | 24 + workflow_manifest.json | 1318 ++++++++++++++++++++++++++++++++++ 2 files changed, 1342 insertions(+) create mode 100644 scripts/workflow_manifest.py create mode 100644 workflow_manifest.json diff --git a/scripts/workflow_manifest.py b/scripts/workflow_manifest.py new file mode 100644 index 000000000..58f88637c --- /dev/null +++ b/scripts/workflow_manifest.py @@ -0,0 +1,24 @@ +import os +import json +import yaml + + +def find_dockstore_yml(directory): + dockstore_dirs = [] + for root, _, files in os.walk(directory): + if ".dockstore.yml" in files: + workflow_details = {} + # read dockstore.yml and add to workflow_details + with open(os.path.join(root, ".dockstore.yml")) as f: + # read yaml file with pyyaml + workflow_details = yaml.safe_load(f) + # add path to workflow_details + workflow_details["path"] = root + dockstore_dirs.append(workflow_details) + return dockstore_dirs + + +dockstore_dirs = find_dockstore_yml("./workflows") + +with open("workflow_manifest.json", "w") as f: + json.dump(dockstore_dirs, f, indent=4) diff --git a/workflow_manifest.json b/workflow_manifest.json new file mode 100644 index 000000000..edf851bca --- /dev/null +++ b/workflow_manifest.json @@ -0,0 +1,1318 @@ +[ + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/parallel-accession-download.ga", + "testParameterFiles": [ + "/parallel-accession-download-tests.yml" + ], + "authors": [ + { + "name": "Marius van den Beek", + "orcid": "0000-0002-9676-7032" + }, + { + "name": "IWC", + "url": "https://github.com/galaxyproject/iwc" + } + ] + } + ], + "path": "./workflows/data-fetching/parallel-accession-download" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + 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"/segmentation-and-counting-tests.yml" + ], + "authors": [ + { + "name": "Leonid Kostrykin", + "orcid": "0000-0003-1323-3762", + "url": "https://github.com/kostrykin/" + } + ] + } + ], + "path": "./workflows/imaging/fluorescence-nuclei-segmentation-and-counting" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Mass-spectrometry__GCMS-with-metaMS.ga", + "testParameterFiles": [ + "/Mass-spectrometry__GCMS-with-metaMS-tests.yml" + ], + "authors": [ + { + "name": "workflow4metabolomics", + "image": "https://raw.githubusercontent.com/workflow4metabolomics/workflow4metabolomics/master/images/logo/logo_w4m-0.1-black-orange.png", + "url": "https://workflow4metabolomics.org/" + } + ] + } + ], + "path": "./workflows/metabomics/gcms-metams" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Mass_spectrometry__LC-MS_preprocessing_with_XCMS.ga", + "testParameterFiles": [ + "/Mass_spectrometry__LC-MS_preprocessing_with_XCMS-tests.yml" + ], + "authors": [ + { + "name": "workflow4metabolomics", + "image": "https://raw.githubusercontent.com/workflow4metabolomics/workflow4metabolomics/master/images/logo/logo_w4m-0.1-black-orange.png", + "url": "https://workflow4metabolomics.org" + } + ] + } + ], + "path": "./workflows/metabomics/lcms-preprocessing" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/protein-ligand-complex-parameterization.ga", + "testParameterFiles": [ + "/protein-ligand-complex-parameterization-tests.yml" + ], + "authors": [ + { + "name": "Simon Bray", + "orcid": "0000-0002-0621-6705" + } + ] + } + ], + "path": "./workflows/computational-chemistry/protein-ligand-complex-parameterization" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/gromacs-dctmd.ga", + "testParameterFiles": [ + "/gromacs-dctmd-tests.yml" + ], + "authors": [ + { + "name": "Simon Bray", + "orcid": "0000-0002-0621-6705" + } + ] + } + ], + "path": "./workflows/computational-chemistry/gromacs-dctmd" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/gromacs-mmgbsa.ga", + "testParameterFiles": [ + "/gromacs-mmgbsa-tests.yml" + ], + "authors": [ + { + "name": "Simon Bray", + "orcid": "0000-0002-0621-6705" + } + ] + } + ], + "path": "./workflows/computational-chemistry/gromacs-mmgbsa" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/fragment-based-docking-scoring.ga", + "testParameterFiles": [ + "/fragment-based-docking-scoring-tests.yml" + ], + "authors": [ + { + "name": "Simon Bray", + "orcid": "0000-0002-0621-6705" + }, + { + "name": "Tim Dudgeon", + "orcid": "0000-0001-6879-5194" + } + ] + } + ], + "path": "./workflows/computational-chemistry/fragment-based-docking-scoring" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Generic-variation-analysis-reporting.ga", + "testParameterFiles": [ + "/Generic-variation-analysis-reporting-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/variant-calling/variation-reporting" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Generic-variation-analysis-on-WGS-PE-data.ga", + "testParameterFiles": [ + "/Generic-variation-analysis-on-WGS-PE-data-tests.yml" + ], + "authors": [ + { + "name": "Anton Nekrutenko", + "orcid": "0000-0002-5987-8032" + } + ] + } + ], + "path": "./workflows/variant-calling/generic-variant-calling-wgs-pe" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "COVID-19-SE-WGS-ILLUMINA", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/se-wgs-variation.ga", + "testParameterFiles": [ + "/se-wgs-variation-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-se-illumina-wgs-variant-calling" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "SARS-COV-2-ILLUMINA-AMPLICON-IVAR-PANGOLIN-NEXTCLADE", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/pe-wgs-ivar-analysis.ga", + "authors": [ + { + "name": "Peter van Heusden", + "orcid": "0000-0001-6553-5274" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-ivar-analysis" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "COVID-19-PE-WGS-ILLUMINA", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/pe-wgs-variation.ga", + "testParameterFiles": [ + "/pe-wgs-variation-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-wgs-variant-calling" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "COVID-19-ARTIC-ONT", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/ont-artic-variation.ga", + "testParameterFiles": [ + "/ont-artic-variation-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-ont-artic-variant-calling" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "COVID-19-PE-ARTIC-ILLUMINA", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/pe-artic-variation.ga", + "testParameterFiles": [ + "/pe-artic-variation-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "COVID-19-VARIATION-REPORTING", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/variation-reporting.ga", + "testParameterFiles": [ + "/variation-reporting-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-variation-reporting" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "COVID-19-CONSENSUS-CONSTRUCTION", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/consensus-from-variation.ga", + "testParameterFiles": [ + "/consensus-from-variation-tests.yml" + ], + "authors": [ + { + "name": "Wolfgang Maier", + "orcid": "0000-0002-9464-6640" + } + ] + } + ], + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-consensus-from-variation" + } +] \ No newline at end of file From faa95aa941fb5357f4dbb39b454b667379119bc0 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 02/74] Minor clarifications, refactoring --- scripts/workflow_manifest.py | 41 ++++++++++++++++++++++++------------ 1 file changed, 27 insertions(+), 14 deletions(-) diff --git a/scripts/workflow_manifest.py b/scripts/workflow_manifest.py index 58f88637c..f77c7b225 100644 --- a/scripts/workflow_manifest.py +++ b/scripts/workflow_manifest.py @@ -3,22 +3,35 @@ import yaml -def find_dockstore_yml(directory): - dockstore_dirs = [] +def find_and_load_dockstore_yml(directory): + """ + Find all .dockstore.yml files in the given directory and its subdirectories. + Read the contents of these files and add the path of the file to the content. + Return a list of all collected data. + """ + workflow_data = [] for root, _, files in os.walk(directory): if ".dockstore.yml" in files: - workflow_details = {} - # read dockstore.yml and add to workflow_details - with open(os.path.join(root, ".dockstore.yml")) as f: - # read yaml file with pyyaml - workflow_details = yaml.safe_load(f) - # add path to workflow_details - workflow_details["path"] = root - dockstore_dirs.append(workflow_details) - return dockstore_dirs + try: + with open(os.path.join(root, ".dockstore.yml")) as f: + workflow_details = yaml.safe_load(f) + workflow_details["path"] = root + workflow_data.append(workflow_details) + except Exception as e: + print(f"Error reading file {os.path.join(root, '.dockstore.yml')}: {e}") + return workflow_data -dockstore_dirs = find_dockstore_yml("./workflows") +def write_to_json(data, filename): + """ + Write the given data into a JSON file with the given filename. + """ + try: + with open(filename, "w") as f: + json.dump(data, f, indent=4) + except Exception as e: + print(f"Error writing to file {filename}: {e}") -with open("workflow_manifest.json", "w") as f: - json.dump(dockstore_dirs, f, indent=4) + +workflow_data = find_and_load_dockstore_yml("./workflows") +write_to_json(workflow_data, "workflow_manifest.json") From 264337acd4fd36fee5bfa9f157d838553a7f0dce Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 03/74] include readme contents --- scripts/workflow_manifest.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/scripts/workflow_manifest.py b/scripts/workflow_manifest.py index f77c7b225..432b14102 100644 --- a/scripts/workflow_manifest.py +++ b/scripts/workflow_manifest.py @@ -22,6 +22,19 @@ def find_and_load_dockstore_yml(directory): return workflow_data +def find_readmes(workflow_data): + """ + Find and read README files for each workflow in the given workflow data. + """ + for workflow in workflow_data: + try: + with open(os.path.join(workflow["path"], "README.md")) as f: + workflow["readme"] = f.read() + except Exception as e: + print(f"Error reading file {os.path.join(workflow['path'], 'README.md')}: {e}") + return workflow_data + + def write_to_json(data, filename): """ Write the given data into a JSON file with the given filename. @@ -34,4 +47,7 @@ def write_to_json(data, filename): workflow_data = find_and_load_dockstore_yml("./workflows") +print(workflow_data) +workflow_data = find_readmes(workflow_data) + write_to_json(workflow_data, "workflow_manifest.json") From 493a372630a289f36829323b752d891adf98c457 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 04/74] Regenerate manifest, formatting --- scripts/workflow_manifest.py | 5 +- workflow_manifest.json | 141 +++++++++++++++++++++++------------ 2 files changed, 97 insertions(+), 49 deletions(-) diff --git a/scripts/workflow_manifest.py b/scripts/workflow_manifest.py index 432b14102..6040a0f48 100644 --- a/scripts/workflow_manifest.py +++ b/scripts/workflow_manifest.py @@ -31,7 +31,9 @@ def find_readmes(workflow_data): with open(os.path.join(workflow["path"], "README.md")) as f: workflow["readme"] = f.read() except Exception as e: - print(f"Error reading file {os.path.join(workflow['path'], 'README.md')}: {e}") + print( + f"Error reading file {os.path.join(workflow['path'], 'README.md')}: {e}" + ) return workflow_data @@ -47,7 +49,6 @@ def write_to_json(data, filename): workflow_data = find_and_load_dockstore_yml("./workflows") -print(workflow_data) workflow_data = find_readmes(workflow_data) write_to_json(workflow_data, "workflow_manifest.json") diff --git a/workflow_manifest.json b/workflow_manifest.json index edf851bca..d9e48d193 100644 --- a/workflow_manifest.json +++ b/workflow_manifest.json @@ -22,7 +22,8 @@ ] } ], - "path": "./workflows/data-fetching/parallel-accession-download" + "path": "./workflows/data-fetching/parallel-accession-download", + "readme": "# Parallel Accession Download\n\nDownloads fastq files for sequencing run accessions provided in a text file\nusing fasterq-dump. Creates one job per listed run accession, and is therefore\nmuch faster and more robust to errors when many accessions need to be\ndownloaded.\n" }, { "version": 1.2, @@ -51,7 +52,8 @@ ] } ], - "path": "./workflows/data-fetching/sra-manifest-to-concatenated-fastqs" + "path": "./workflows/data-fetching/sra-manifest-to-concatenated-fastqs", + "readme": "# SRA manifest to concatenated fastqs\n\nThis workflow takes as input a SRA manifest from SRA Run Selector (or a tabular with a header line), downloads all sequencing run data from the SRA and arranges it into per-sample fastq or pairs of fastq datasets.\n\nIt will work out the relationship between runs and samples from the user-indicated run and sample columns in the input and will concatenate sequencing run data as needed to obtain per-sample datasets.\n\n## Input dataset\n\n- The workflow needs a single tabular input dataset, which is supposed to list SRA run identifiers in one column and sample names in another, and which needs to have a header line.\n- SRA manifests obtained via the SRA Run Selector and turned into tabular format represent valid input.\n\n## Input values\n\n- Column number with SRA run ID\n\n For manifests obtained through the SRA Run Selector this is column 1\n\n- Column number with sample names\n\n The number of the column that should be used to assign sequencing runs to samples\n The names in the column will also serve as the labels of datasets in the output collection.\n For manifests obtained through the SRA Run Selector suitable columns might be number 6 (BioSample), 16 (Experiment) or 36 (Sample Name).\n\n## Processing\n\n- The workflow downloads sequencing run data in fastq format with fasterqdump (one job per SRA run ID).\n- Run data gets concatenated if it comes from the same sample.\n\n## Outputs\n\n- There are 2 outputs, one with paired-end datasets, one with single-read datasets.\n\n## Limitations\n\n- Special characters in sample names (anything that is not an English alphabet character, digit, underscore, dash, space, dot or comma (`[a-zA-Z0-9_\\- \\.,]`) will be converted to dashes (`-`).\n" }, { "version": 1.2, @@ -72,7 +74,8 @@ ] } ], - "path": "./workflows/transcriptomics/rnaseq-sr" + "path": "./workflows/transcriptomics/rnaseq-sr", + "readme": "# RNA-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a list of datasets of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- forward adapter sequence: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the read is complementary to the coding sequence, forward means that the read is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with Stringtie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. This can also be used to get the strandedness.\n- FPKM values for genes and transcripts are computed with cufflinks using correction for multi-mapped reads (this step is optionnal).\n- FPKM/TPM values for genes are computed with StringTie (this step is optional).\n- The BAM is filtered to keep only uniquely mapped reads (tag NH:i:1).\n- Unstranded coverage is computed with bedtools and normalized to the number of million uniquely mapped reads.\n- The three coverage files are converted to bigwig.\n\n### Warning\n\n- The coverage stranded output depends on the strandedness of the library:\n - If you have an unstranded library, stranded coverages are useless\n - If you have a forward stranded library, the label matches the orientation of reads.\n - If you have a reverse stranded library, `forward` should correspond to genes on the forward strand and uses the reads mapped on the reverse strand. `reverse` should correspond to genes on the reverse strand and uses the reads mapped on the forward strand.\n\n## Contribution\n\n@lldelisle wrote the workflow and the tests.\n\n@nagoue updated the tools, made it work in usegalaxy.org, fixed some best practices.\n" }, { "version": 1.2, @@ -93,7 +96,8 @@ ] } ], - "path": "./workflows/transcriptomics/rnaseq-pe" + "path": "./workflows/transcriptomics/rnaseq-pe", + "readme": "# RNA-seq paired-end Workflow\n\n## Inputs dataset\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the first read in a pair is complementary to the coding sequence, forward means that the first read in a pair is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with StringTie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. This can also be used to get the strandedness.\n- FPKM values for genes and transcripts are computed with cufflinks using correction for multi-mapped reads (this step is optionnal).\n- FPKM/TPM values for genes are computed with StringTie.\n- The BAM is filtered to keep only uniquely mapped reads (tag NH:i:1).\n- Unstranded coverage is computed with bedtools and normalized to the number of million uniquely mapped reads.\n- The three coverage files are converted to bigwig.\n\n### Warning\n\n- The coverage stranded output depends on the strandedness of the library:\n - If you have an unstranded library, stranded coverages are useless\n - If you have a forward stranded library, the label matches the orientation of the first read in pairs.\n - If you have a reverse stranded library, the label matches the orientation of the second read in pairs.\n" }, { "version": 1.2, @@ -114,7 +118,8 @@ ] } ], - "path": "./workflows/genome-assembly/polish-with-long-reads" + "path": "./workflows/genome-assembly/polish-with-long-reads", + "readme": "# Assembly polishing with Racon workflow\n\n## Inputs\n\n- Sequencing reads in format: fastq, fastq.gz, fastqsanger.gz or fastqsanger\n- Genome assembly to be polished, in fasta format\n\n## What does the workflow do\n\n- After long reads have been assembled into a genome (contigs), this can be polished with the same long reads. \n- This workflow uses the tool minimap2 to map the long reads back to the assembly, and then uses Racon to make polishes. \n- This is repeated a further 3 times. \n\nIn more detail:\n\n- minimap2 : long reads are mapped to assembly => overlaps.paf.\n- overaps, long reads, assembly => Racon => polished assembly 1\n- using polished assembly 1 as input; repeat minimap2 + racon => polished assembly 2\n- using polished assembly 2 as input, repeat minimap2 + racon => polished assembly 3\n- using polished assembly 3 as input, repeat minimap2 + racon => polished assembly 4\n\n## Settings\n\n- Run as-is or change parameters at runtime.\n- For the input at \"minimap settings for long reads\", enter (map-pb) for PacBio reads, (map-hifi) for PacBio HiFi reads, or (map-ont) for Oxford Nanopore reads.\n\n## Outputs\n\nThere is one output: the polished assembly in fasta format. \n\n" }, { "version": 1.2, @@ -135,7 +140,8 @@ ] } ], - "path": "./workflows/genome-assembly/assembly-with-flye" + "path": "./workflows/genome-assembly/assembly-with-flye", + "readme": "# Genome assembly with Flye workflow\n\n\n## Why use this workflow?\n\n- This is a fairly simple workflow that assembles a genome from long sequencing reads.\n- It takes in sequencing reads from PacBio (Hifi or non-Hifi), or Oxford Nanopore.\n- If you have PacBio Hifi reads, you may prefer to use a workflow with the assembly tool Hifiasm, such as the those in the suite of VGP workflows. \n\n## Inputs\n\nRaw sequencing reads from PacBio or Oxford Nanopore in format:\nfasta, fasta.gz, fastq, fastq.gz, fastqsanger.gz or fastqsanger\n\n## What does the workflow do\n\n- Assembles the reads with the tool Flye\n- Summarizes the statistics with the tool Fasta statistics\n- Report with the tool Quast\n- Renders the assembly graph with the tool Bandage\n\n## Settings\n\nRun as-is or change parameters at runtime\n\nFor example:\n- change the Flye option of \"mode\" to the correct sequencing type\n- change the Quast option for \"Type of organism\" to correct taxon\n \n## Outputs\n\n- Flye assembly output - four files: fasta, gfa for bandage, graph_dot file, assembly info\n- Fasta statistics\n- Bandage image\n- Quast report\n" }, { "version": 1.2, @@ -156,7 +162,8 @@ ] } ], - "path": "./workflows/proteomics/openms-metaprosip" + "path": "./workflows/proteomics/openms-metaprosip", + "readme": "# MetaProSIP: automated inference of elemental fluxes in microbial communities\n\n## Inputs dataset\n\n- `Centroided LC-MS datasets` in mzML (MetaProSIP is mainly tested on data generated by orbitrap instruments)\n- `Fasta Database` in Fasta (aminoacid sequences)\n\n## Inputs values\n\n- `Precursor monoisotopic mass tolerance` (ppm): This value is passed to\n - MSGFPlusAdapter parameter `Precursor monoisotopic mass tolerance` (-precursor_mass_tolerance)\n - MetaProSIP parameter `Tolerance in ppm` (-mz_tolerance_ppm)\n- Fixed modifications\n- Variable modifications\n- Labeled element\n\n## Processing\n\n- DecoyDatabase: Add decoy sequences to the Fasta database (for FDR calculation)\n- FeatureFinderCentroided: identify eluting peptides that correspond to isotopologues with natural isotopic distributions \n- MSGFPlusAdapter: identify peptides through peptide fragment fingerprinting (database search)\n- FeatureFinderMultiplex: detect elution profiles of unlabeled peptides\n- PeptideIndexer: annotate protein association to identified peptides\n- FalseDiscoveryRate: Calculate FDR\n- IDMapper: map identified spectra to elution profiles\n- MetaProSIP: calculate the protein-SIP features, to perform functional grouping, and for protein inference\n" }, { "version": 1.2, @@ -177,7 +184,8 @@ ] } ], - "path": "./workflows/repeatmasking" + "path": "./workflows/repeatmasking", + "readme": "# RepeatMasking Workflow\n\nThis workflow uses RepeatModeler and RepeatMasker for genome analysis.\n\n- RepeatModeler is a software package for identifying and modeling de novo families of transposable elements (TEs). At the heart of RepeatModeler are three de novo repeat search programs (RECON, RepeatScout and LtrHarvest/Ltr_retriever) which use complementary computational methods to identify repeat element boundaries and family relationships from sequence data.\n\n- RepeatMasker is a program that analyzes DNA sequences for *interleaved repeats* and *low-complexity* DNA sequences. The result of the program is a detailed annotation of the repeats present in the query sequence, as well as a modified version of the query sequence in which all annotated repeats are present.\n\n## Input dataset for RepeatModeler\n- RepeatModeler requires a single input file, a genome in fasta format.\n\n\n## Outputs dataset for RepeatModeler\n- Two output files are generated:\n - summary file (.tbl)\n - fasta file containing alignments in order of appearance in the query sequence\n\n\n## Input dataset for RepeatMasker\n- ReapatMasker requires the fasta file generated by RepeatModeler\n\n## Outputs datasets for RepeatMasker\n- Five output files are generated:\n - a fasta file\n - .gff3 file\n - a table summarizing the repeated content of the sequence analyzed\n - a file with statistics related to the repeated content of the sequence analyzed\n - a summary of the mutation sites found and the order of grouping\n \n" }, { "version": 1.2, @@ -198,7 +206,8 @@ ] } ], - "path": "./workflows/epigenetics/cutandrun" + "path": "./workflows/epigenetics/cutandrun", + "readme": "# CUT&RUN (and CUT&TAG) Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually CUT&RUN is Truseq and CUT&TAG is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera\n- reference_genome: this field will be adapted to the genomes available for bowtie2\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb\n- The BAM is filtered to keep only MAPQ30 and concordant pairs\n- The PCR duplicates are removed with Picard (only from version 0.6)\n- The BAM is converted to BED to enable macs2 to take both pairs into account\n- The peaks are called with macs2 which at the same time generates a coverage file (normalized or not).\n- The coverage file is converted to bigwig\n- A multiQC is run to have an overview of the QC\n" }, { "version": 1.2, @@ -219,7 +228,8 @@ ] } ], - "path": "./workflows/epigenetics/chipseq-sr" + "path": "./workflows/epigenetics/chipseq-sr", + "readme": "# ChIP-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of fastqsanger files.\n\n## Inputs values\n\n- adapters sequence_forward: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30.\n- The peaks are called with MACS2 with a fixed extension of 200bp which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n" }, { "version": 1.2, @@ -285,7 +295,8 @@ ] } ], - "path": "./workflows/epigenetics/hic-hicup-cooler" + "path": "./workflows/epigenetics/hic-hicup-cooler", + "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n" }, { "version": 1.2, @@ -306,7 +317,8 @@ ] } ], - "path": "./workflows/epigenetics/average-bigwig-between-replicates" + "path": "./workflows/epigenetics/average-bigwig-between-replicates", + "readme": "# Average Bigwig between replicates\n\nThis workflow is very useful when you processed multiple samples in collections and you want to generate an average coverage per condition.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of bigwigs (normalized). The identifiers of your bigwigs must be like:\n - whatever_sample1_identificationOfReplicate1\n - whatever_sample1_identificationOfReplicate2\n - ...\n - whatever_sample2_identificationOfReplicate1\n - whatever_sample2_identificationOfReplicate2\n - ...\n\n## Inputs values\n\n- bin_size: this is used when average of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs. I suggest 5bp for RNA-seq and 50bp for other applications.\n\n## Processing\n\n- The workflow will split identifiers between everything which is before the last underscore which will be the *sample* and everything which is after the last underscore which will be the *replicate identifier*. And restructure the collection as list:list:\n - whatever_sample1:\n - identificationOfReplicate1\n - identificationOfReplicate2\n - ...\n - whatever_sample2:\n - identificationOfReplicate1\n - identificationOfReplicate2\n - ---\n - ...\n- Then it will average bigwigs into each inner list\n\n## Outputs\n\n- The output is a collection of bigwig datasets like:\n - whatever_sample1\n - whatever_sample2\n - ...\n" }, { "version": 1.2, @@ -357,7 +369,8 @@ ] } ], - "path": "./workflows/epigenetics/consensus-peaks" + "path": "./workflows/epigenetics/consensus-peaks", + "readme": "# Consensus peaks Workflow\n\nThe goal of this workflow is to get a list of confident peaks with summits from n replicates.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of datasets with n BAM where PCR duplicates have been removed (the workflow also works for nested list if you have multiple conditions each with multiple replicates).\n\n## Inputs values\n\n- Minimum number of overlap: Minimum number of replicates into which the final summit should be present.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- bin_size: this is the bin sized used to compute the average of normalized profiles. Large values will allow to have a smaller output file but with less resolution while small values will increase computation time and size of the output file to produce a more resolutive bigwig.\n\n## Strategy summary\n\nHere is a generated example to highlight the strategy:\n![strategy](./strategy.png)\n\n## Processing\n\n- The workflow will:\n - first part:\n - call peaks and compute normalized coverage on each BAM individually\n - average normalized profiles\n - compute the intersection between all peaks and filter when at least x replicate overlaps\n - second part:\n - subset all BAM to get the same number of reads\n - call peaks on all subsetted BAM combined\n - finally, keep only peaks from the second part that have summits overlapping the filtered intersection of the first part.\n" }, { "version": 1.2, @@ -378,7 +391,8 @@ ] } ], - "path": "./workflows/epigenetics/atacseq" + "path": "./workflows/epigenetics/atacseq", + "readme": "# ATACseq Workflow\n\nThis workflow is highly concordant with the corresponding training material.\nYou can have more information about ATAC-seq analysis in the [slides](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/slides.html) and the [tutorial](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/tutorial.html).\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- reference_genome: this field will be adapted to the genomes available for bowtie2 and the genomes available for bedtools slopbed (dbkeys table)\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- bin_size: this is used when normalization of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs.\n\n## Processing\n\n- The workflow will remove nextera adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb.\n- The BAM is filtered to keep only MAPQ30, concordant pairs and pairs outside of the mitochondria.\n- The PCR duplicates are removed with Picard (only from version 0.8).\n- The BAM is converted to BED to enable macs2 to take both pairs into account.\n- The peaks are called with macs2 which at the same time generates a coverage file.\n- The coverage file is converted to bigwig\n- The amount of reads 500bp from summits and the total number of reads are computed.\n- Two normalizations are computed:\n - By million reads\n - By million reads in peaks (500bp from summits)\n- Other QC are performed:\n - A histogram with fragment length is computed.\n - The evaluation of percentage of reads to chrM or MT is computed.\n- A multiQC is run to have an overview of the QC.\n\n### Warning\n\n- The `reference_genome` parameter value is used to select references in bowtie2 and bedtools slopbed. Only references that are present in bowtie2 **and** bedtools slopbed are selectable. If your favorite reference genome is not available ask your administrator to make sure that each bowtie2 reference has a corresponding len file for use in bedtools slopbed.\n" }, { "version": 1.2, @@ -399,7 +413,8 @@ ] } ], - "path": "./workflows/epigenetics/chipseq-pe" + "path": "./workflows/epigenetics/chipseq-pe", + "readme": "# ChIP-seq paired-end Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapters sequences: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Fragments.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any pair with mate smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30 and concordant pairs.\n- The peaks are called with MACS2 which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n\n## Contribution\n\n@lldelisle wrote the workflow.\n\n@nagoue updated the tools, made it work in usegalaxy.org, fixed the best practices and wrote the tests.\n" }, { "version": 1.2, @@ -423,7 +438,8 @@ ] } ], - "path": "./workflows/amplicon/dada2" + "path": "./workflows/amplicon/dada2", + "readme": "# Dada2: amplicon analysis for paired end data\n\n## Inputs dataset\n\n- `Paired input data` paired input collection in FASTQ format\n\n## Inputs values\n\n- `Read length forward/reverse reads` length of the forward/reverse reads to which they should be truncated in the filter and trim step\n- `Pool samples` pooling may increase sensitivity\n- `Reference database` that should be used for taxonomic assignment\n\n## Processing\n\nThe workflow follows the steps described in the [dada2 tutorial](https://benjjneb.github.io/dada2/tutorial.html).\n\nAs a first step the input collection is sorted. This is important because the dada2 step outputs\na collection in sorted order. If the input collection would not be sorted then the mergePairs step\nsamples would be mixed up.\n\n- `FilterAndTrim` Quality control by filtering and trimming reads\n- `QualityProfile` is called before and after the FilterAndTrim step\n- `Unzip Collection` separates forward and reverse reads (the next steps are evaluated separately on forward and reverse reads)\n- `learnErrors` learn error rates\n- `dada` filter noisy reads\n- `mergePairs` merge forward and reverse reads\n- `makeSequenceTable` create the sequence table\n- `removeBimeraDenovo` remove chimeric sequencs\n- `assignTaxonomy` assign taxonomic information from a reference data base\n\n## TODO\n\nSome possibilities to extend/improve the workflow\n\n- output BIOM\n- use ASV1, ... in sequence table and taxonomy output, and output additional fasta\n- allow to use custom taxonomy / make it optional\n" }, { "version": 1.2, @@ -505,7 +521,8 @@ ] } ], - "path": "./workflows/amplicon/qiime2/qiime2-I-import" + "path": "./workflows/amplicon/qiime2/qiime2-I-import", + "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." }, { "version": 1.2, @@ -549,7 +566,8 @@ ] } ], - "path": "./workflows/amplicon/qiime2/qiime2-II-denoising" + "path": "./workflows/amplicon/qiime2/qiime2-II-denoising", + "readme": "# QIIME2 workflows\n\n## Available workflows\n\nDenoising (using `qiime2`'s `dada2` integration for paired / single end data.\n\n## Inputs\n\n- Demultiplexed sequences as a qiime2 aertifact file (`qza`) containing the sequence information.\n- Metadata table (`tabular`)\n- Truncation length\n- Trimming length (optional)\n\nFor the paired end workflow the truncation and trimming length for the reverse reads can / has to be given.\n\n\n## Processing\n\n- Denoising with `qiime2 dada2 denoise-single`/`paired`\n- For each of the three outputs (see below) another tool is started to prepare a corresponding qzv file\n - representative sequences `qiime2 feature-table tabulate-seqs `\n - denoising statistics `qiime2 metadata tabulate`\n - summary of the feature table\n\n## Outputs\n\n - representative sequences \n - denoising statistics \n - summary of the feature table (how many sequences are lost in the corresponding steps)\n" }, { "version": 1.2, @@ -585,7 +603,8 @@ ] } ], - "path": "./workflows/scRNAseq/baredsc" + "path": "./workflows/scRNAseq/baredsc", + "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n" }, { "version": 1.2, @@ -653,7 +672,8 @@ ] } ], - "path": "./workflows/scRNAseq/fastq-to-matrix-10x" + "path": "./workflows/scRNAseq/fastq-to-matrix-10x", + "readme": "# Single-cell RNA-seq fastq to matrix for 10X data\n\nThese workflows are inspired by the [training material](https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-preprocessing-tenx/tutorial.html). Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n" }, { "version": 1.2, @@ -689,7 +709,8 @@ ] } ], - "path": "./workflows/scRNAseq/velocyto" + "path": "./workflows/scRNAseq/velocyto", + "readme": "# Velocyto on 10X data\n\nThese workflows simply run velocyto. There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n" }, { "version": 1.2, @@ -711,7 +732,8 @@ ] } ], - "path": "./workflows/virology/pox-virus-amplicon" + "path": "./workflows/virology/pox-virus-amplicon", + "readme": "# Pox Virus Illumina Amplicon Workflow for half-genomes sequencing data\n\nThis workflow generates consensus sequences from Illumina PE-sequenced ARTIC data of pox virus samples.\n\nIt requires that all samples have been sequenced in two halves in two separate sequencing runs, and utilizes this property to resolve the inverted terminal repeat (ITR) sequences of pox virus genomes.\n\nThe workflow uses BWA-MEM for mapping the reads from each half-genome sequencing run to a correspondingly masked version of the reference genome, merges the resulting two read mappings, and uses iVar for primer trimming and consensus sequence generation.\n\nConceptually, this workflow builds on https://github.com/iwc-workflows/sars-cov-2-pe-illumina-artic-ivar-analysis and adds the logic for the split genome mapping and merging of the results." }, { "version": 1.2, @@ -732,7 +754,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Purge-duplicate-contigs-VGP6" + "path": "./workflows/VGP-assembly-v2/Purge-duplicate-contigs-VGP6", + "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Primary Assembly (hap1) [fasta] (Generated by the contigging workflow)\n3. Alternate Assembly (hap2) [fasta] (Generated by the contigging workflow)\n4. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n5. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n6. Estimated Genome Size [txt]\n7. Name of first haplotype\n8. Name of second haplotype\n9. Lineage of you species for Busco Orthologs\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies\n" }, { "version": 1.2, @@ -756,7 +779,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Scaffolding-Bionano-VGP7" + "path": "./workflows/VGP-assembly-v2/Scaffolding-Bionano-VGP7", + "readme": "# Scaffolding with Bionano\n\nScaffolding using Bionano optical map data\n\n## Inputs\n\n1. Bionano data [cmap]\n2. Estimated genome size [txt]\n3. Phased assembly generated by Hifiasm [gfa1]\n\n## Outputs\n\n1. Scaffolds\n2. Non-scaffolded contigs\n3. QC: Assembly statistics\n4. QC: Nx plot\n5. QC: Size plot" }, { "version": 1.2, @@ -801,7 +825,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-VGP1" + "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-VGP1", + "readme": "# VGP Workflow #1\n\nThis workflow produces a Meryl database and Genomescope outputs that will be used to determine parameters for following workflows, and assess the quality of genome assemblies. Specifically, it provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality.\n\n### Inputs\n\n- A collection of Hifi long reads in FASTQ format\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl Database of kmer counts\n- GenomeScope\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n\n ![image](https://github.com/galaxyproject/iwc/assets/4291636/565238fc-f8a9-46ac-8b31-6276410fa436)\n" }, { "version": 1.2, @@ -825,7 +850,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Purge-duplicates-one-haplotype-VGP6b" + "path": "./workflows/VGP-assembly-v2/Purge-duplicates-one-haplotype-VGP6b", + "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups in a single haplotype(could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Assembly to purge (e.g. hap1) [fasta] (Generated by the contigging workflow)\n3. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n4. Estimated Genome Size [txt]\n5. Assembly to leave alone (used for merqury statistics) (e.g. hap2) [fasta] (Generated by the contigging workflow)\n6. Name of un-altered assembly\n7. Name of purged assembly\n\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies" }, { "version": 1.2, @@ -873,7 +899,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Scaffolding-HiC-VGP8" + "path": "./workflows/VGP-assembly-v2/Scaffolding-HiC-VGP8", + "readme": "# Scaffolding with HiC data\n\nThis workflow perfoms scaffolding using HiC data with YAHS. It is designed to be run as part of one the VGP analysis trajectories. \nExample of trajectory : \n- VGP1 : Kmer profiling \n- VGP4 : Genome assembly with HiC phasing\n- VGP6 : Purge duplicated haplotigs\n- VGP8 : Scaffolding with HiC\n\n## Inputs\n\n1. Scaffolded assembly [fasta]\n2. Concatenated HiC forward reads [fastq]\n3. Concatenated HiC reverse reads [fastq]\n4. Restriction enzyme sequence [txt]\n5. Estimated genome size [txt]\n\n### Outputs\n\n1. Scaffolds in [fasta] and [gfa] format\n2. QC: Assembly statistics\n3. QC: Nx plot\n4. QC: Size plot\n5. QC: BUSCO report\n6. QC: Pretext Maps before and after scaffolding" }, { "version": 1.2, @@ -901,7 +928,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-HiC-phasing-VGP4" + "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-HiC-phasing-VGP4", + "readme": "# Contiging Solo w/HiC:\n\nGenerate phased assembly based on PacBio Hifi Reads using HiC data from the same individual for phasing.\n\n## Inputs\n\n1. Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n## Outputs\n\n1. Haplotype 1 assembly ([fasta] and [gfa])\n2. Haplotype 2 assembly ([fasta] and [gfa])\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies" }, { "version": 1.2, @@ -925,7 +953,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-trio-VGP2" + "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-trio-VGP2", + "readme": "# VGP Workflow #1\n\nThis workflow collects the metrics on the properties of the genome under consideration by analyzing the *k*-mer frequencies. It provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality. It uses reads from two parental genomes to partition long reads from the offspring into haplotype-specific *k*-mer databases.\n\n### Inputs\n\n- Collection of Hifi long reads [fastq] (Collection)\n- Paternal short-read Illumina sequencing reads [fastq] (Collection)\n- Maternal short-read Illumina sequencing reads [fastq] (Collection)\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl databases of k-mer counts\n - Child\n - Paternal haplotype\n - Maternal haplotype\n- GenomeScope metrics for child and the two parental genomes (three GenomeScope profiles in total)\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n \n ![image](https://github.com/galaxyproject/iwc/assets/4291636/35282f8e-d021-44f6-8e03-7b58b32d6d00)\n" }, { "version": 1.2, @@ -949,7 +978,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-Trio-phasing-VGP5" + "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-Trio-phasing-VGP5", + "readme": "# Assembly with Hifi reads and Trio Data\n\nGenerate phased assembly based on PacBio Hifi Reads using parental Illumina data for phasing\n\n## Inputs\n\n1. Hifi long reads [fastq]\n2. Concatenated Illumina reads : Paternal [fastq]\n3. Concatenated Illumina reads : Maternal [fastq]\n4. K-mer database [meryldb]\n5. Paternal hapmer database [meryldb]\n6. Maternal hapmer database [meryldb]\n7. Genome profile summary generated by Genomescope [txt]\n8. Genome model parameters generated by Genomescope [tabular]\n9. Homozygous read coverage (Estimated from the Genomescope model if not provided)\n10. Lineage of the species being assembled\n11. Bloom Filter\n12. Name of first haplotype\n13. Name of second haplotype\n\n## Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. Merqury report for both assemblies\n5. Assembly statistics for both assemblies\n6. Nx Plot for both assemblies\n7. Size plot for both assemblies\n\n\n" }, { "version": 1.2, @@ -973,7 +1003,8 @@ ] } ], - "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-only-VGP3" + "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-only-VGP3", + "readme": "## Contiging Solo w/HiC:\n\nGenerate phased assembly based on PacBio Hifi Reads using HiC data from the same individual for phasing.\n\n\n### Inputs\n\n\n1. Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n\n### Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblie\n" }, { "version": 1.2, @@ -995,7 +1026,8 @@ ] } ], - "path": "./workflows/imaging/fluorescence-nuclei-segmentation-and-counting" + "path": "./workflows/imaging/fluorescence-nuclei-segmentation-and-counting", + "readme": "# Segmentation and counting of cell nuclei in fluorescence microscopy images\n\nThis workflow performs segmentation and counting of cell nuclei using fluorescence microscopy images. The segmentation step is performed using Otsu thresholding (Otsu, 1979). The workflow is based on the tutorial: https://training.galaxyproject.org/training-material/topics/imaging/tutorials/imaging-introduction/tutorial.html\n\n![](test-data/overlay_image.png)\n\n## Inputs\n\n**`input_image`:** The fluorescence microscopy images to be segmented. Must be the single image channel, which contains the cell nuclei.\n\n## Outputs\n\n**`overlay_image`:** An overlay of the original image and the outlines of the segmentated objects, each also annotated with a unique number.\n\n**`objects_count`:** Table with a single column `objects` and a single row (the actual number of objects).\n\n**`label_image`:** The segmentation result (label map, which contains a unique label for each segmented object).\n" }, { "version": 1.2, @@ -1017,7 +1049,8 @@ ] } ], - "path": "./workflows/metabomics/gcms-metams" + "path": "./workflows/metabomics/gcms-metams", + "readme": "# Mass spectrometry: GCMS with metaMS \n\nThis workflow uses the XCMS tool R package [(Smith, C.A. 2006)](https://bioconductor.org/packages/release/bioc/html/xcms.html) to extract, filter, align and fill gaps, and uses the CAMERA R package [(Kuhl, C 2012)](https://bioconductor.org/packages/release/bioc/html/CAMERA.html) to annotate isotopes, adducts and fragments.\n\nThis workflow is composed with the XCMS tool R package [(Smith, C.A. 2006)](https://bioconductor.org/packages/release/bioc/html/xcms.html) to extract and the metaMS R package [(Wehrens, R 2014)](https://bioconductor.org/packages/release/bioc/html/metaMS.html) for the field of untargeted metabolomics. \n\n\ud83c\udf93 For more information see the [Galaxy Training Network tutorial: Mass spectrometry: GC-MS analysis with metaMS package](https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/gcms/tutorial.html)\n\n## Inputs\n### sampleMetadata\nThe sampleMetadata tabular file corresponds to a table containing information about your samples\n\nA sample metadata file contains various information for each of your raw files:\n- Classes which will be used during the preprocessing steps\n- Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order\n- Different experimental conditions which can be used for statistics\n- Any information about samples that you want to keep, in a column format\n\nThe content of your sample metadata file has to be filled by you, since it is not contained in your raw data. Note that you can either:\n- Upload an existing metadata file\n- Use a template to create one (because it can be painful to get the sample list without misspelling or omission)\n - Generate a template with the `xcms get a sampleMetadata file` tool available in Galaxy\n - Fill it using your favorite table editor (Excel, LibreOffice)\n - Upload it within Galaxy\n\n**Formats:** tab-separated values as tsv, tab, txt, ...\n\n### Mass-spectrometry Dataset Collection\nMass-spectrometry data files gathered in a Galaxy Dataser Collection\n\n**Formats:** open format as mzXML, mzMl, mzData and netCDF\n\n## Main steps\n1. MSnbase readMSData: read the mzXML and prepare for xcms\n2. XCMS findChromPeaks: peak picking\n3. metaMS.runGC: definition of pseudo-spectra\n" }, { "version": 1.2, @@ -1039,7 +1072,8 @@ ] } ], - "path": "./workflows/metabomics/lcms-preprocessing" + "path": "./workflows/metabomics/lcms-preprocessing", + "readme": "# Mass spectrometry: LC-MS preprocessing with XCMS \n\nThis workflow uses the XCMS tool R package [(Smith, C.A. 2006)](https://bioconductor.org/packages/release/bioc/html/xcms.html) to extract, filter, align and fill gaps, and uses the CAMERA R package [(Kuhl, C 2012)](https://bioconductor.org/packages/release/bioc/html/CAMERA.html) to annotate isotopes, adducts and fragments.\n\n\ud83c\udf93 For more information see the [Galaxy Training Network tutorial: Mass spectrometry: LC-MS preprocessing with XCMS](https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html)\n\n## Inputs\n### sampleMetadata\nThe sampleMetadata tabular file corresponds to a table containing information about your samples\n\nA sample metadata file contains various information for each of your raw files:\n- Classes which will be used during the preprocessing steps\n- Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order\n- Different experimental conditions which can be used for statistics\n- Any information about samples that you want to keep, in a column format\n\nThe content of your sample metadata file has to be filled by you, since it is not contained in your raw data. Note that you can either:\n- Upload an existing metadata file\n- Use a template to create one (because it can be painful to get the sample list without misspelling or omission)\n - Generate a template with the `xcms get a sampleMetadata file` tool available in Galaxy\n - Fill it using your favorite table editor (Excel, LibreOffice)\n - Upload it within Galaxy\n\n**Formats:** tab-separated values as tsv, tab, txt, ...\n\n### Mass-spectrometry Dataset Collection\nMass-spectrometry data files gathered in a Galaxy Dataser Collection\n\n**Formats:** open format as mzXML, mzMl, mzData and netCDF\n\n## Main steps\n1. MSnbase readMSData: read the mzXML and prepare for xcms\n2. XCMS findChromPeaks: peak picking\n3. XCMS groupChromPeaks: determining shared ions across samples\n4. XCMS adjustRtime: retention time correction\n5. XCMS fillChromPeaks: integrating areas of missing peaks\n6. CAMERA.annotate: annotation\n" }, { "version": 1.2, @@ -1060,7 +1094,8 @@ ] } ], - "path": "./workflows/computational-chemistry/protein-ligand-complex-parameterization" + "path": "./workflows/computational-chemistry/protein-ligand-complex-parameterization", + "readme": "# Protein-ligand complex parameterization\n\nParameterizes an input protein (PDB) and ligand (SDF) file prior to molecular\ndynamics simulation with GROMACS.\n\nThis is a simple workflow intended for use as a subworkflow in more complex\nMD workflows. It is used as a subworkflow by the GROMACS MMGBSA and dcTMD\nworkflows. \n" }, { "version": 1.2, @@ -1081,7 +1116,8 @@ ] } ], - "path": "./workflows/computational-chemistry/gromacs-dctmd" + "path": "./workflows/computational-chemistry/gromacs-dctmd", + "readme": "# GROMACS dcTMD free energy calculation\n\nPerform an ensemble of targeted MD simulations of a user-specified size using\nthe GROMACS PULL code and calculate dcTMD free energy and friction profiles\nfor the resulting dissocation pathway. Note that pathway separation is not\nperformed by the workflow; the user is responsible for checking the ensemble themselves.\n\nThe input protein (PDB) and ligand (SDF) files provided are parameterized by\nthe 'Protein-ligand complex parameterization' subworkflow.\n\nNote that the workflow uses a MDP file for configuring the TMD simulations; this\nis packaged alongside the workflow as `tmd.mdp`.\n\n## Citations\n* Steffen Wolf and Gerhard Stock (2018), Targeted Molecular Dynamics Calculations of Free Energy Profiles Using a Nonequilibrium Friction Correction, J. Chem. Theory Comput. doi:10.1021/acs.jctc.8b00835\n* Steffen Wolf, Benjamin Lickert, Simon Bray and Gerhard Stock (2020), Multisecond ligand dissociation dynamics from atomistic simulations, Nat. Commun. doi:10.1038/s41467-020-16655-1\n" }, { "version": 1.2, @@ -1102,7 +1138,8 @@ ] } ], - "path": "./workflows/computational-chemistry/gromacs-mmgbsa" + "path": "./workflows/computational-chemistry/gromacs-mmgbsa", + "readme": "# GROMACS MMGBSA free energy calculation\n\nPerform an ensemble of MD simulations of a user-specified size using GROMACS,\nand calculate MMGBSA free energies using AmberTools. An ensemble average is\ncalculated and returned to the user as the final input.\n\nThe input protein (PDB) and ligand (SDF) files provided are parameterized by\nthe 'Protein-ligand complex parameterization' subworkflow.\n" }, { "version": 1.2, @@ -1127,7 +1164,8 @@ ] } ], - "path": "./workflows/computational-chemistry/fragment-based-docking-scoring" + "path": "./workflows/computational-chemistry/fragment-based-docking-scoring", + "readme": "# Fragment-based virtual screening with docking and pose scoring\n\nDock a compound library against a target protein with rDock and validate the\nposes generated against a reference fragment using SuCOS to compare the feature\noverlap. Poses are filtered by a user-specified SuCOS threshold.\n\nA list of fragments should be specified which will be used to define the cavity\nfor docking, using the 'Frankenstein ligand' technique. For more details, please\nsee https://www.informaticsmatters.com/blog/2018/11/23/cavities-and-frankenstein-molecules.html\n\nCompounds are split into collections and then recombined to allow the workflow\nto be run in a highly parallelized fashion. To specify the level of\nparallelization, use the 'Collection size' parameter.\n" }, { "version": 1.2, @@ -1148,7 +1186,8 @@ ] } ], - "path": "./workflows/variant-calling/variation-reporting" + "path": "./workflows/variant-calling/variation-reporting", + "readme": "Generic variation analysis reporting\n--------------------------------------\n\nThis workflow takes table of variants produced by any of the variant calling workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/variant-calling\nand generates a list of variants by Samples and by Variant.\n" }, { "version": 1.2, @@ -1169,7 +1208,8 @@ ] } ], - "path": "./workflows/variant-calling/generic-variant-calling-wgs-pe" + "path": "./workflows/variant-calling/generic-variant-calling-wgs-pe", + "readme": "Generic variation analysis on WGS PE data\n-------------------------------------------\n\nThis workflows performs paired end read mapping with bwa-mem followed by\nsensitive variant calling across a wide range of AFs with lofreq and variant\nannotation with snpEff. The reference genome can be provided as a GenBank file.\n" }, { "version": 1.2, @@ -1190,7 +1230,8 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-se-illumina-wgs-variant-calling" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-se-illumina-wgs-variant-calling", + "readme": "COVID-19: variation analysis on WGS SE data\n-------------------------------------------\n\nThis workflows performs single end read mapping with bowtie2 followed by\nsensitive variant calling across a wide range of AFs with lofreq and variant\nannotation with snpEff 4.5covid19.\n" }, { "version": 1.2, @@ -1208,7 +1249,8 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-ivar-analysis" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-ivar-analysis", + "readme": "# COVID-19 sequence analysis on Illumina Amplicon PE data\n\nThis workflow implements an [iVar](https://github.com/andersen-lab/ivar) based analysis similar to\nthe one in [ncov2019-artic-nf](https://github.com/connor-lab/ncov2019-artic-nf), [covid-19-signal](https://github.com/jaleezyy/covid-19-signal/) and the Thiagen [Titan workflow](https://github.com/theiagen/public_health_viral_genomics). These workflows (written in Nextflow, Snakemake and WDL) are widely in use in [COG UK](https://www.cogconsortium.uk/), [CanCOGeN](https://www.genomecanada.ca/en/cancogen) and some US state public health laboratories.\n\nThis workflow is also the subject of a Galaxy Training Network tutorial (currently a [Work in Progress](https://github.com/galaxyproject/training-material/pull/2633)).\nIt differs from [this workflow](https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling) in\nthat it does not use `lofreq` and is aimed at rapid analysis of majority variants and lineage/clade assignment with `pangolin` and `nextclade`.\n\nTODO:\n\n1. Add support for QC using negative and positive controls\n2. Integrate with phylogeny tools including IQTree and UShER (and possibly more).\n" }, { "version": 1.2, @@ -1229,7 +1271,8 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-wgs-variant-calling" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-wgs-variant-calling", + "readme": "COVID-19: variation analysis on WGS PE data\n-------------------------------------------\n\nThis workflows performs paired end read mapping with bwa-mem followed by\nsensitive variant calling across a wide range of AFs with lofreq and variant\nannotation with snpEff 4.5covid19.\n" }, { "version": 1.2, @@ -1250,7 +1293,8 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-ont-artic-variant-calling" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-ont-artic-variant-calling", + "readme": "COVID-19: variation analysis on ARTIC ONT data\n----------------------------------------------\n\nThis workflow for ONT-sequenced ARTIC data is modeled after the alignment/variant-calling steps of the [ARTIC pipeline](https://artic.readthedocs.io/en/latest/). It performs, essentially, the same steps as that pipeline\u2019s minion command, i.e. read mapping with minimap2 and variant calling with medaka. Like the Illumina ARTIC workflow it uses ivar for primer trimming. Since ONT-sequenced reads have a much higher error rate than Illumina-sequenced reads and are therefor plagued more by false-positive variant calls, this workflow does make no attempt to handle amplicons affected by potential primer-binding site mutations.\n" }, { "version": 1.2, @@ -1271,7 +1315,8 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling", + "readme": "COVID-19: variation analysis on ARTIC PE data\n---------------------------------------------\n\nThe workflow for Illumina-sequenced ampliconic data builds on the RNASeq workflow\nfor paired-end data using the same steps for mapping and variant calling, but\nadds extra logic for trimming amplicon primer sequences off reads with the ivar\npackage. In addition, this workflow uses ivar also to identify amplicons\naffected by primer-binding site mutations and, if possible, excludes reads\nderived from such \"tainted\" amplicons when calculating allele-frequencies\nof other variants.\n" }, { "version": 1.2, @@ -1292,7 +1337,8 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-variation-reporting" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-variation-reporting", + "readme": "COVID-19: variation analysis reporting\n--------------------------------------\n\nThis workflow takes VCF datasets of variants produced by any of the\n\"*-variant-calling\" workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling\nand generates tabular reports of variants by samples and by variant, along with\nan overview plot of variants and their allele-frequencies across all samples.\n" }, { "version": 1.2, @@ -1313,6 +1359,7 @@ ] } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-consensus-from-variation" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-consensus-from-variation", + "readme": "COVID-19: consensus construction\n--------------------------------\n\nThis workflow aims at generating reliable consensus sequences from variant\ncalls according to transparent criteria that capture at least some of the\ncomplexity of variant calling.\n\nIt takes a collection of VCFs (with DP and DP4 INFO fields) and a collection of\nthe corresponding aligned reads (for the purpose of calculating genome-wide\ncoverage) such as produced by any of the variant calling workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling\nand generates a collection of viral consensus sequences and a multisample FASTA\nof all these sequences.\n\nEach consensus sequence is guaranteed to capture all called, filter-passing (as\nper the FILTER column of the VCF input) variants found in the VCF of its sample\nthat reach a user-defined consensus allele frequency threshold.\n\nFilter-failing variants and variants below a second user-defined minimal\nallele frequency threshold will be ignored.\n\nGenomic positions of filter-passing variants with an allele frequency in\nbetween the two thresholds will be hard-masked (with N) in the consensus\nsequence of their sample.\n\nGenomic positions with a coverage (calculated from the read alignments input)\nbelow another user-defined threshold will be hard-masked, too, unless they are\nconsensus variant sites.\n" } ] \ No newline at end of file From dcceeff6d967e10e130d8069bd491882b50ebc61 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 05/74] Basic manifest for tinkering --- scripts/workflow_manifest.py | 6 ++---- workflow_manifest.json | 12 +----------- 2 files changed, 3 insertions(+), 15 deletions(-) diff --git a/scripts/workflow_manifest.py b/scripts/workflow_manifest.py index 6040a0f48..f18d9ef88 100644 --- a/scripts/workflow_manifest.py +++ b/scripts/workflow_manifest.py @@ -3,7 +3,7 @@ import yaml -def find_and_load_dockstore_yml(directory): +def find_and_load_compliant_workflows(directory): """ Find all .dockstore.yml files in the given directory and its subdirectories. Read the contents of these files and add the path of the file to the content. @@ -31,9 +31,7 @@ def find_readmes(workflow_data): with open(os.path.join(workflow["path"], "README.md")) as f: workflow["readme"] = f.read() except Exception as e: - print( - f"Error reading file {os.path.join(workflow['path'], 'README.md')}: {e}" - ) + print(f"Error reading file {os.path.join(workflow['path'], 'README.md')}: {e}") return workflow_data diff --git a/workflow_manifest.json b/workflow_manifest.json index d9e48d193..fc56c6779 100644 --- a/workflow_manifest.json +++ b/workflow_manifest.json @@ -296,17 +296,7 @@ } ], "path": "./workflows/epigenetics/hic-hicup-cooler", - "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n" - }, - { - "version": 1.2, - "workflows": [ - { - "name": "main", - "subclass": "Galaxy", - "publish": true, - "primaryDescriptorPath": "/average-bigwig-between-replicates.ga", - "testParameterFiles": [ + "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n" }, { "version": 1.2, "workflows": [ { "name": "main", "subclass": "Galaxy", "publish": true, "primaryDescriptorPath": "/average-bigwig-between-replicates.ga", "testParameterFiles": [ "/average-bigwig-between-replicates-tests.yml" ], "authors": [ From a47187dfc21decaf70d8b8f75eb81b83e3a5977c Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 06/74] basic astro --- showcase/.gitignore | 24 + showcase/README.md | 54 + showcase/astro.config.mjs | 8 + showcase/package-lock.json | 12507 +++++++++++++++++++ showcase/package.json | 19 + showcase/public/favicon.svg | 9 + showcase/src/components/Card.astro | 61 + showcase/src/components/WorkflowDetail.vue | 22 + showcase/src/components/WorkflowList.vue | 15 + showcase/src/env.d.ts | 1 + showcase/src/layouts/Layout.astro | 51 + showcase/src/pages/index.astro | 123 + showcase/src/pages/workflow/[path].astro | 12 + showcase/tsconfig.json | 6 + 14 files changed, 12912 insertions(+) create mode 100644 showcase/.gitignore create mode 100644 showcase/README.md create mode 100644 showcase/astro.config.mjs create mode 100644 showcase/package-lock.json create mode 100644 showcase/package.json create mode 100644 showcase/public/favicon.svg create mode 100644 showcase/src/components/Card.astro create mode 100644 showcase/src/components/WorkflowDetail.vue create mode 100644 showcase/src/components/WorkflowList.vue create mode 100644 showcase/src/env.d.ts create mode 100644 showcase/src/layouts/Layout.astro create mode 100644 showcase/src/pages/index.astro create mode 100644 showcase/src/pages/workflow/[path].astro create mode 100644 showcase/tsconfig.json diff --git a/showcase/.gitignore b/showcase/.gitignore new file mode 100644 index 000000000..016b59ea1 --- /dev/null +++ b/showcase/.gitignore @@ -0,0 +1,24 @@ +# build output +dist/ + +# generated types +.astro/ + +# dependencies +node_modules/ + +# logs +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* + +# environment variables +.env +.env.production + +# macOS-specific files +.DS_Store + +# jetbrains setting folder +.idea/ diff --git a/showcase/README.md b/showcase/README.md new file mode 100644 index 000000000..1db3fb399 --- /dev/null +++ b/showcase/README.md @@ -0,0 +1,54 @@ +# Astro Starter Kit: Basics + +```sh +npm create astro@latest -- --template basics +``` + +[![Open in StackBlitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/github/withastro/astro/tree/latest/examples/basics) +[![Open with CodeSandbox](https://assets.codesandbox.io/github/button-edit-lime.svg)](https://codesandbox.io/p/sandbox/github/withastro/astro/tree/latest/examples/basics) +[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/withastro/astro?devcontainer_path=.devcontainer/basics/devcontainer.json) + +> 🧑‍🚀 **Seasoned astronaut?** Delete this file. Have fun! + +![just-the-basics](https://github.com/withastro/astro/assets/2244813/a0a5533c-a856-4198-8470-2d67b1d7c554) + +## 🚀 Project Structure + +Inside of your Astro project, you'll see the following folders and files: + +```text +/ +├── public/ +│ └── favicon.svg +├── src/ +│ ├── components/ +│ │ └── Card.astro +│ ├── layouts/ +│ │ └── Layout.astro +│ └── pages/ +│ └── index.astro +└── package.json +``` + +Astro looks for `.astro` or `.md` files in the `src/pages/` directory. Each page is exposed as a route based on its file name. + +There's nothing special about `src/components/`, but that's where we like to put any Astro/React/Vue/Svelte/Preact components. + +Any static assets, like images, can be placed in the `public/` directory. + +## 🧞 Commands + +All commands are run from the root of the project, from a terminal: + +| Command | Action | +| :------------------------ | :----------------------------------------------- | +| `npm install` | Installs dependencies | +| `npm run dev` | Starts local dev server at `localhost:4321` | +| `npm run build` | Build your production site to `./dist/` | +| `npm run preview` | Preview your build locally, before deploying | +| `npm run astro ...` | Run CLI commands like `astro add`, `astro check` | +| `npm run astro -- --help` | Get help using the Astro CLI | + +## 👀 Want to learn more? + +Feel free to check [our documentation](https://docs.astro.build) or jump into our [Discord server](https://astro.build/chat). diff --git a/showcase/astro.config.mjs b/showcase/astro.config.mjs new file mode 100644 index 000000000..2ff3bdcfc --- /dev/null +++ b/showcase/astro.config.mjs @@ -0,0 +1,8 @@ +import { defineConfig } from 'astro/config'; + +import vue from "@astrojs/vue"; + +// https://astro.build/config +export default defineConfig({ + integrations: [vue()] +}); \ No newline at end of file diff --git a/showcase/package-lock.json b/showcase/package-lock.json new file mode 100644 index 000000000..987ee4a18 --- /dev/null +++ b/showcase/package-lock.json @@ -0,0 +1,12507 @@ +{ + "name": "showcase", + "version": "0.0.1", + "lockfileVersion": 2, + "requires": true, + "packages": { + "": { + "name": "showcase", + "version": "0.0.1", + "dependencies": { + "@astrojs/check": "^0.7.0", + "@astrojs/vue": "^4.2.0", + "astro": "^4.8.6", + "typescript": "^5.4.5", + "vue": "^3.4.27" + } + }, + "node_modules/@ampproject/remapping": { + "version": "2.3.0", + "resolved": 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"start": "astro dev", + "build": "astro check && astro build", + "preview": "astro preview", + "astro": "astro" + }, + "dependencies": { + "@astrojs/check": "^0.7.0", + "@astrojs/vue": "^4.2.0", + "astro": "^4.8.6", + "typescript": "^5.4.5", + "vue": "^3.4.27" + } +} diff --git a/showcase/public/favicon.svg b/showcase/public/favicon.svg new file mode 100644 index 000000000..f157bd1c5 --- /dev/null +++ b/showcase/public/favicon.svg @@ -0,0 +1,9 @@ + + + + diff --git a/showcase/src/components/Card.astro b/showcase/src/components/Card.astro new file mode 100644 index 000000000..bd6d5971e --- /dev/null +++ b/showcase/src/components/Card.astro @@ -0,0 +1,61 @@ +--- +interface Props { + title: string; + body: string; + href: string; +} + +const { href, title, body } = Astro.props; +--- + +
  • + +

    + {title} + → +

    +

    + {body} +

    +     +
    • + diff --git a/showcase/src/components/WorkflowDetail.vue b/showcase/src/components/WorkflowDetail.vue new file mode 100644 index 000000000..9e8a80ff0 --- /dev/null +++ b/showcase/src/components/WorkflowDetail.vue @@ -0,0 +1,22 @@ + + + + \ No newline at end of file diff --git a/showcase/src/components/WorkflowList.vue b/showcase/src/components/WorkflowList.vue new file mode 100644 index 000000000..134064d8e --- /dev/null +++ b/showcase/src/components/WorkflowList.vue @@ -0,0 +1,15 @@ + + + \ No newline at end of file diff --git a/showcase/src/env.d.ts b/showcase/src/env.d.ts new file mode 100644 index 000000000..f964fe0cf --- /dev/null +++ b/showcase/src/env.d.ts @@ -0,0 +1 @@ +/// diff --git a/showcase/src/layouts/Layout.astro b/showcase/src/layouts/Layout.astro new file mode 100644 index 000000000..7b552be19 --- /dev/null +++ b/showcase/src/layouts/Layout.astro @@ -0,0 +1,51 @@ +--- +interface Props { + title: string; +} + +const { title } = Astro.props; +--- + + + + + + + + + + {title} + + + + + + diff --git a/showcase/src/pages/index.astro b/showcase/src/pages/index.astro new file mode 100644 index 000000000..fb6262872 --- /dev/null +++ b/showcase/src/pages/index.astro @@ -0,0 +1,123 @@ +--- +import Layout from '../layouts/Layout.astro'; +import Card from '../components/Card.astro'; +--- + + +
    + +

    Welcome to Astro

    +

    + To get started, open the directory src/pages in your project.
    + Code Challenge: Tweak the "Welcome to Astro" message above. +

    +
      + + + + +
    +
    +     + + diff --git a/showcase/src/pages/workflow/[path].astro b/showcase/src/pages/workflow/[path].astro new file mode 100644 index 000000000..262bfaefc --- /dev/null +++ b/showcase/src/pages/workflow/[path].astro @@ -0,0 +1,12 @@ +--- +import { useParams } from 'astro'; +import WorkflowDetail from '../../components/WorkflowDetail.vue'; +import manifest from '../../data/manifest.json'; + +const { path } = useParams(); +const workflow = manifest.find(w => w.path === `./workflows${path}`); +--- + + + + \ No newline at end of file diff --git a/showcase/tsconfig.json b/showcase/tsconfig.json new file mode 100644 index 000000000..30cf17bb8 --- /dev/null +++ b/showcase/tsconfig.json @@ -0,0 +1,6 @@ +{ + "extends": "astro/tsconfigs/strict", + "compilerOptions": { + "jsx": "preserve" + } +} \ No newline at end of file From e32cbfcfddce07d1beac2199cfd0089acc78bed1 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 07/74] Incremental work, rebase flat --- showcase/src/components/WorkflowList.vue | 39 ++++++++----- showcase/src/data/workflow_manifest.json | 1 + showcase/src/pages/index.astro | 61 ++------------------ showcase/src/pages/workflow/[path].astro | 12 ---- showcase/src/pages/workflows/[...slug].astro | 31 ++++++++++ 5 files changed, 63 insertions(+), 81 deletions(-) create mode 120000 showcase/src/data/workflow_manifest.json delete mode 100644 showcase/src/pages/workflow/[path].astro create mode 100644 showcase/src/pages/workflows/[...slug].astro diff --git a/showcase/src/components/WorkflowList.vue b/showcase/src/components/WorkflowList.vue index 134064d8e..d9b4b2cbc 100644 --- a/showcase/src/components/WorkflowList.vue +++ b/showcase/src/components/WorkflowList.vue @@ -1,15 +1,28 @@ - - \ No newline at end of file +} + \ No newline at end of file diff --git a/showcase/src/data/workflow_manifest.json b/showcase/src/data/workflow_manifest.json new file mode 120000 index 000000000..2fa18ab1a --- /dev/null +++ b/showcase/src/data/workflow_manifest.json @@ -0,0 +1 @@ +../../../workflow_manifest.json \ No newline at end of file diff --git a/showcase/src/pages/index.astro b/showcase/src/pages/index.astro index fb6262872..8a6ab9028 100644 --- a/showcase/src/pages/index.astro +++ b/showcase/src/pages/index.astro @@ -1,65 +1,14 @@ --- import Layout from '../layouts/Layout.astro'; -import Card from '../components/Card.astro'; +import manifest from '../data/workflow_manifest.json'; +import WorkflowList from "../components/WorkflowList.vue"; +import { Debug } from 'astro:components'; ---
    - -

    Welcome to Astro

    -

    - To get started, open the directory src/pages in your project.
    - Code Challenge: Tweak the "Welcome to Astro" message above. -

    -
      - - - - -
    +

    Intergalactic Workflow Commission Gallery

    +
    diff --git a/showcase/src/pages/workflow/[path].astro b/showcase/src/pages/workflow/[path].astro deleted file mode 100644 index 262bfaefc..000000000 --- a/showcase/src/pages/workflow/[path].astro +++ /dev/null @@ -1,12 +0,0 @@ ---- -import { useParams } from 'astro'; -import WorkflowDetail from '../../components/WorkflowDetail.vue'; -import manifest from '../../data/manifest.json'; - -const { path } = useParams(); -const workflow = manifest.find(w => w.path === `./workflows${path}`); ---- - - - - \ No newline at end of file diff --git a/showcase/src/pages/workflows/[...slug].astro b/showcase/src/pages/workflows/[...slug].astro new file mode 100644 index 000000000..f586574cb --- /dev/null +++ b/showcase/src/pages/workflows/[...slug].astro @@ -0,0 +1,31 @@ +--- +import { Astro, getStaticPaths, getStaticProps } from 'astro'; +import WorkflowDetail from '../../components/WorkflowDetail.vue'; +import manifest from '../../data/workflow_manifest.json'; + +// Define getStaticPaths to generate paths for each workflow +export const getStaticPaths = async () => { + const paths = manifest.map((workflow) => { + // Extract the slug from the workflow path + const slug = workflow.path.replace('./workflows/', ''); + return { params: { slug: slug } }; + }); + + return paths; +}; + +// Define getStaticProps to fetch data for each page +export const getStaticProps = async ({ params }) => { + const slugPath = params.slug.join('/'); + const workflow = manifest.find((w) => w.path === `./workflows/${slugPath}`); + return { props: { workflow } }; +}; + +// Get the slug from params +const { props } = Astro; +const { workflow } = props; +--- + + + + \ No newline at end of file From 4f20bc4ec0f27ba099e757743c7d714722d95de4 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 08/74] More data loading --- scripts/workflow_manifest.py | 84 +- workflow_manifest.json | 68964 ++++++++++++++++++++++++++++++++- 2 files changed, 68876 insertions(+), 172 deletions(-) diff --git a/scripts/workflow_manifest.py b/scripts/workflow_manifest.py index f18d9ef88..f2263e389 100644 --- a/scripts/workflow_manifest.py +++ b/scripts/workflow_manifest.py @@ -8,30 +8,81 @@ def find_and_load_compliant_workflows(directory): Find all .dockstore.yml files in the given directory and its subdirectories. Read the contents of these files and add the path of the file to the content. Return a list of all collected data. + """ workflow_data = [] for root, _, files in os.walk(directory): if ".dockstore.yml" in files: try: - with open(os.path.join(root, ".dockstore.yml")) as f: + dockstore_path = os.path.join(root, ".dockstore.yml") + with open(dockstore_path) as f: workflow_details = yaml.safe_load(f) workflow_details["path"] = root workflow_data.append(workflow_details) + + # Now inspect the details which are something like this: + # version: 1.2 + # workflows: + # - name: Velocyto-on10X-from-bundled + # subclass: Galaxy + # publish: true + # primaryDescriptorPath: /Velocyto-on10X-from-bundled.ga + # testParameterFiles: + # - /Velocyto-on10X-from-bundled-tests.yml + # authors: + # - name: Lucille Delisle + # orcid: 0000-0002-1964-4960 + # - name: Velocyto-on10X-filtered-barcodes + # subclass: Galaxy + # publish: true + # primaryDescriptorPath: /Velocyto-on10X-filtered-barcodes.ga + # testParameterFiles: + # - /Velocyto-on10X-filtered-barcodes-tests.yml + # authors: + # - name: Lucille Delisle + # orcid: 0000-0002-1964-4960 + + for workflow in workflow_details["workflows"]: + # For each listed workflow, load the primaryDescriptorPath + # file, which is the actual galaxy workflow. + # strip leading slash from primaryDescriptorPath if present -- these are relative. + workflow_path = os.path.join( + root, workflow["primaryDescriptorPath"].lstrip("/") + ) + try: + with open(workflow_path) as f: + workflow["definition"] = json.load(f) + except Exception as e: + print( + f"No workflow file: {os.path.join(root, workflow['primaryDescriptorPath'])}: {e}" + ) + + # also try to load a README.md file for each workflow + try: + with open(os.path.join(root, "README.md")) as f: + workflow["readme"] = f.read() + # catch FileNotFound + except FileNotFoundError: + print(f"No README.md at {os.path.join(root, 'README.md')}") + except Exception as e: + print( + f"Error reading file {os.path.join(root, 'README.md')}: {e}" + ) + + # also try to load a CHANGELOG.md file for each workflow + try: + with open(os.path.join(root, "CHANGELOG.md")) as f: + workflow["changelog"] = f.read() + except FileNotFoundError: + print(f"No CHANGELOG.md at {os.path.join(root, 'CHANGELOG.md')}") + except Exception as e: + print( + f"Error reading file {os.path.join(root, 'CHANGELOG.md')}: {e}" + ) + except Exception as e: print(f"Error reading file {os.path.join(root, '.dockstore.yml')}: {e}") - return workflow_data - -def find_readmes(workflow_data): - """ - Find and read README files for each workflow in the given workflow data. - """ - for workflow in workflow_data: - try: - with open(os.path.join(workflow["path"], "README.md")) as f: - workflow["readme"] = f.read() - except Exception as e: - print(f"Error reading file {os.path.join(workflow['path'], 'README.md')}: {e}") return workflow_data @@ -46,7 +97,6 @@ def write_to_json(data, filename): print(f"Error writing to file {filename}: {e}") -workflow_data = find_and_load_dockstore_yml("./workflows") -workflow_data = find_readmes(workflow_data) - -write_to_json(workflow_data, "workflow_manifest.json") +if __name__ == "__main__": + workflow_data = find_and_load_compliant_workflows("./workflows") + write_to_json(workflow_data, "workflow_manifest.json") diff --git a/workflow_manifest.json b/workflow_manifest.json index fc56c6779..f5caaffeb 100644 --- a/workflow_manifest.json +++ b/workflow_manifest.json @@ -19,11 +19,286 @@ "name": "IWC", "url": "https://github.com/galaxyproject/iwc" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Downloads fastq files for sequencing run accessions provided in a text file using fasterq-dump. Creates one job per listed run accession.", + "comments": [], + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-9676-7032", + "name": "Marius van den Beek" + }, + { + "class": "Organization", + "name": "IWC", + "url": "https://github.com/galaxyproject/iwc" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.1.13", + "name": "Parallel Accession Download", + "steps": { + "0": { + "annotation": "Text file containing run accessions (starting with SRR, ERR or DRR), one per line.", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Text file containing run accessions (starting with SRR, ERR or DRR), one per line.", + "name": "Run accessions" + } + ], + "label": "Run accessions", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 0, + "top": 0 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"txt\"], \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "e9e5605e-29e1-4f90-9693-0e40a2ddfd8f", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1", + "errors": null, + "id": 1, + "input_connections": { + "split_parms|input": { + "id": 0, + "output_name": "output" + } + }, + "inputs": [ + { + "description": "runtime parameter for tool Split file", + "name": "split_parms" + } + ], + "label": "Split accessions to collection", + "name": "Split file", + "outputs": [ + { + "name": "list_output_txt", + "type": "input" + } + ], + "position": { + "left": 279.51666259765625, + "top": 86.01666259765625 + }, + "post_job_actions": { + "HideDatasetActionlist_output_txt": { + "action_arguments": {}, + "action_type": "HideDatasetAction", + "output_name": "list_output_txt" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1", + "tool_shed_repository": { + "changeset_revision": "baabc30154cd", + "name": "split_file_to_collection", + "owner": "bgruening", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"split_parms\": {\"select_ftype\": \"txt\", \"__current_case__\": 5, \"input\": {\"__class__\": \"ConnectedValue\"}, \"select_mode\": {\"mode\": \"chunk\", \"__current_case__\": 0, \"chunksize\": \"1\"}, \"newfilenames\": \"split_file\", \"select_allocate\": {\"allocate\": \"byrow\", \"__current_case__\": 2}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.5.1", + "type": "tool", + "uuid": "f8d776ff-e1ba-4bde-9b4b-392d825fd2b7", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1", + "errors": null, + "id": 2, + "input_connections": { + "input|file_list": { + 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"input_connections": { + "input": { + "id": 2, + "output_name": "output_collection" + } + }, + "inputs": [], + "label": "flatten single end output", + "name": "Apply rules", + "outputs": [ + { + "name": "output", + "type": "input" + } + ], + "position": { + "left": 905.0499572753906, + "top": 215.0250244140625 + }, + "post_job_actions": { + "TagDatasetActionoutput": { + "action_arguments": { + "tags": "name:SE" + }, + "action_type": "TagDatasetAction", + "output_name": "output" + } + }, + "tool_id": "__APPLY_RULES__", + "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"rules\": {\"mapping\": [{\"collapsible_value\": {\"__class__\": \"RuntimeValue\"}, \"columns\": [1], \"connectable\": true, \"editing\": false, \"is_workflow\": false, \"type\": \"list_identifiers\"}], \"rules\": [{\"collapsible_value\": {\"__class__\": \"RuntimeValue\"}, \"connectable\": true, \"error\": null, \"is_workflow\": false, \"type\": \"add_column_metadata\", \"value\": \"identifier0\", \"warn\": null}, {\"collapsible_value\": {\"__class__\": \"RuntimeValue\"}, \"connectable\": true, \"error\": null, \"is_workflow\": false, \"type\": \"add_column_metadata\", \"value\": \"identifier1\", \"warn\": null}]}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.1.0", + "type": "tool", + "uuid": "946d9610-c363-4915-b93a-f074169ef812", + "when": null, + "workflow_outputs": [ + { + "label": "Single End Reads", + "output_name": "output", + "uuid": "e2bf276c-0956-473e-a778-b3b3df7351f5" + } + ] + } + }, + "tags": [], + "uuid": "15c3229d-8786-457f-a020-7aa64c0cf6e8", + "version": 10 + }, + "readme": "# Parallel Accession Download\n\nDownloads fastq files for sequencing run accessions provided in a text file\nusing fasterq-dump. Creates one job per listed run accession, and is therefore\nmuch faster and more robust to errors when many accessions need to be\ndownloaded.\n", + "changelog": "# Changelog\n\n## [0.1.13] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.1.12] 2024-04-16\n\n### Changed\n\n- Remove unnecessary param_value_from_file step and directly pass file with identifiers to fasterqdump\n\n## [0.1.11] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.1.10] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.1.9] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1.8] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.1.7] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n\n## [0.1.6] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3`\n\n## [0.1.5] 2023-09-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1`\n\n## [0.1.4] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0`\n\n## [0.1.3] 2022-02-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1`\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.1] - 2021-06-23\n\n### Added\n\n- Initial version of Parallel Accession Download workflow.\n" } ], - "path": "./workflows/data-fetching/parallel-accession-download", - "readme": "# Parallel Accession Download\n\nDownloads fastq files for sequencing run accessions provided in a text file\nusing fasterq-dump. Creates one job per listed run accession, and is therefore\nmuch faster and more robust to errors when many accessions need to be\ndownloaded.\n" + "path": "./workflows/data-fetching/parallel-accession-download" }, { "version": 1.2, @@ -49,11 +324,754 @@ "name": "Wolfgang Maier", "orcid": "0000-0002-9464-6640" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a SRA_manifest from SRA Run Selector and will generate one fastq file or fastq pair of file for each experiment (concatenated multiple runs if necessary). 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+ "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__input_ext\": \"fastqsanger.gz\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"dataset_names\": false, \"global_condition\": {\"input_type\": \"singles\", \"__current_case__\": 0, \"inputs\": {\"__class__\": \"ConnectedValue\"}}, \"headers\": \"0\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.4.2", + "type": "tool", + "uuid": "49a70885-3374-4680-bbd2-ad57b8be543d", + "when": null, + "workflow_outputs": [ + { + "label": "single_output", + "output_name": "out_file1", + "uuid": "71cbe11d-24ff-4e86-954f-acb439332d0a" + } + ] + } + }, + "tags": [], + "uuid": "363898af-e598-4f0e-abd9-e6ded395ce66", + "version": 3 + }, + "readme": "# SRA manifest to concatenated fastqs\n\nThis workflow takes as input a SRA manifest from SRA Run Selector (or a tabular with a header line), downloads all sequencing run data from the SRA and arranges it into per-sample fastq or pairs of fastq datasets.\n\nIt will work out the relationship between runs and samples from the user-indicated run and sample columns in the input and will concatenate sequencing run data as needed to obtain per-sample datasets.\n\n## Input dataset\n\n- The workflow needs a single tabular input dataset, which is supposed to list SRA run identifiers in one column and sample names in another, and which needs to have a header line.\n- SRA manifests obtained via the SRA Run Selector and turned into tabular format represent valid input.\n\n## Input values\n\n- Column number with SRA run ID\n\n For manifests obtained through the SRA Run Selector this is column 1\n\n- Column number with sample names\n\n The number of the column that should be used to assign sequencing runs to samples\n The names in the column will also serve as the labels of datasets in the output collection.\n For manifests obtained through the SRA Run Selector suitable columns might be number 6 (BioSample), 16 (Experiment) or 36 (Sample Name).\n\n## Processing\n\n- The workflow downloads sequencing run data in fastq format with fasterqdump (one job per SRA run ID).\n- Run data gets concatenated if it comes from the same sample.\n\n## Outputs\n\n- There are 2 outputs, one with paired-end datasets, one with single-read datasets.\n\n## Limitations\n\n- Special characters in sample names (anything that is not an English alphabet character, digit, underscore, dash, space, dot or comma (`[a-zA-Z0-9_\\- \\.,]`) will be converted to dashes (`-`).\n", + "changelog": "# Changelog\n\n## [0.5] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.3] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.2.4] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.2.3] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n\n## [0.2.2] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.2.1] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.1` was updated to `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2`\n\n## [0.1] 2023-10-23\nFirst release.\n" } ], - "path": "./workflows/data-fetching/sra-manifest-to-concatenated-fastqs", - "readme": "# SRA manifest to concatenated fastqs\n\nThis workflow takes as input a SRA manifest from SRA Run Selector (or a tabular with a header line), downloads all sequencing run data from the SRA and arranges it into per-sample fastq or pairs of fastq datasets.\n\nIt will work out the relationship between runs and samples from the user-indicated run and sample columns in the input and will concatenate sequencing run data as needed to obtain per-sample datasets.\n\n## Input dataset\n\n- The workflow needs a single tabular input dataset, which is supposed to list SRA run identifiers in one column and sample names in another, and which needs to have a header line.\n- SRA manifests obtained via the SRA Run Selector and turned into tabular format represent valid input.\n\n## Input values\n\n- Column number with SRA run ID\n\n For manifests obtained through the SRA Run Selector this is column 1\n\n- Column number with sample names\n\n The number of the column that should be used to assign sequencing runs to samples\n The names in the column will also serve as the labels of datasets in the output collection.\n For manifests obtained through the SRA Run Selector suitable columns might be number 6 (BioSample), 16 (Experiment) or 36 (Sample Name).\n\n## Processing\n\n- The workflow downloads sequencing run data in fastq format with fasterqdump (one job per SRA run ID).\n- Run data gets concatenated if it comes from the same sample.\n\n## Outputs\n\n- There are 2 outputs, one with paired-end datasets, one with single-read datasets.\n\n## Limitations\n\n- Special characters in sample names (anything that is not an English alphabet character, digit, underscore, dash, space, dot or comma (`[a-zA-Z0-9_\\- \\.,]`) will be converted to dashes (`-`).\n" + "path": "./workflows/data-fetching/sra-manifest-to-concatenated-fastqs" }, { "version": 1.2, @@ -71,11 +1089,1812 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a list of single-reads fastqs. 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Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the read is complementary to the coding sequence, forward means that the read is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with Stringtie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. This can also be used to get the strandedness.\n- FPKM values for genes and transcripts are computed with cufflinks using correction for multi-mapped reads (this step is optionnal).\n- FPKM/TPM values for genes are computed with StringTie (this step is optional).\n- The BAM is filtered to keep only uniquely mapped reads (tag NH:i:1).\n- Unstranded coverage is computed with bedtools and normalized to the number of million uniquely mapped reads.\n- The three coverage files are converted to bigwig.\n\n### Warning\n\n- The coverage stranded output depends on the strandedness of the library:\n - If you have an unstranded library, stranded coverages are useless\n - If you have a forward stranded library, the label matches the orientation of reads.\n - If you have a reverse stranded library, `forward` should correspond to genes on the forward strand and uses the reads mapped on the reverse strand. `reverse` should correspond to genes on the reverse strand and uses the reads mapped on the forward strand.\n\n## Contribution\n\n@lldelisle wrote the workflow and the tests.\n\n@nagoue updated the tools, made it work in usegalaxy.org, fixed some best practices.\n", + "changelog": "# Changelog\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.5] 2023-09-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n\n### Manual update\n- Use STAR to compute normalized strand-specific coverage\n- Add an option to use StringTie to compute FPKM\n- Make cufflinks step optional\n\n## [0.4.1] 2023-09-14\n- add author in dockstore file\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-02\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1`\n\n## [0.1] 2022-10-12\n\nFirst release.\n" } ], - "path": "./workflows/transcriptomics/rnaseq-sr", - "readme": "# RNA-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a list of datasets of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- forward adapter sequence: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the read is complementary to the coding sequence, forward means that the read is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with Stringtie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. 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Inputs dataset\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the first read in a pair is complementary to the coding sequence, forward means that the first read in a pair is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with StringTie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. This can also be used to get the strandedness.\n- FPKM values for genes and transcripts are computed with cufflinks using correction for multi-mapped reads (this step is optionnal).\n- FPKM/TPM values for genes are computed with StringTie.\n- The BAM is filtered to keep only uniquely mapped reads (tag NH:i:1).\n- Unstranded coverage is computed with bedtools and normalized to the number of million uniquely mapped reads.\n- The three coverage files are converted to bigwig.\n\n### Warning\n\n- The coverage stranded output depends on the strandedness of the library:\n - If you have an unstranded library, stranded coverages are useless\n - If you have a forward stranded library, the label matches the orientation of the first read in pairs.\n - If you have a reverse stranded library, the label matches the orientation of the second read in pairs.\n", + "changelog": "# Changelog\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.5] 2023-09-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n\n### Manual update\n- Use STAR to compute normalized strand-specific coverage\n- Add an option to use StringTie to compute FPKM\n- Make cufflinks step optional\n\n## [0.4.1] 2023-09-14\n- add author in dockstore file\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-02\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1`\n\n## [0.1] 2022-10-21\n\nFirst release.\n" } ], - "path": "./workflows/transcriptomics/rnaseq-pe", - "readme": "# RNA-seq paired-end Workflow\n\n## Inputs dataset\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the first read in a pair is complementary to the coding sequence, forward means that the first read in a pair is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. 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\"ConnectedValue\"}, \"e\": \"0.3\", \"error_threshold\": \"0.3\", \"f\": \"false\", \"fragment_correction\": false, \"g\": \"-8\", \"gap\": \"-4\", \"include_unpolished\": false, \"m\": \"5\", \"match\": \"3\", \"mismatch\": \"-5\", \"no_trimming\": false, \"overlaps\": {\"__class__\": \"ConnectedValue\"}, \"q\": \"10.0\", \"quality_threshold\": \"10.0\", \"reads\": {\"__class__\": \"ConnectedValue\"}, \"u\": \"true\", \"w\": \"500\", \"window_length\": \"500\", \"x\": \"-4\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.5.0+galaxy1", + "type": "tool", + "uuid": "53f4572e-3a4a-4585-89ab-9459f8a61720", + "when": null, + "workflow_outputs": [ + { + "label": "Assembly polished by long reads using Racon", + "output_name": "consensus", + "uuid": "bcf0f03c-5951-46a7-aa38-545aed9bc183" + } + ] + } + }, + "tags": [], + "uuid": "68d6270a-bfd1-452a-abc9-4a314e13af85", + "version": 9 + }, + "readme": "# Assembly polishing with Racon workflow\n\n## Inputs\n\n- Sequencing reads in format: fastq, fastq.gz, fastqsanger.gz or fastqsanger\n- Genome assembly to be polished, in fasta format\n\n## What does the workflow do\n\n- After long reads have been assembled into a genome (contigs), this can be polished with the same long reads. \n- This workflow uses the tool minimap2 to map the long reads back to the assembly, and then uses Racon to make polishes. \n- This is repeated a further 3 times. \n\nIn more detail:\n\n- minimap2 : long reads are mapped to assembly => overlaps.paf.\n- overaps, long reads, assembly => Racon => polished assembly 1\n- using polished assembly 1 as input; repeat minimap2 + racon => polished assembly 2\n- using polished assembly 2 as input, repeat minimap2 + racon => polished assembly 3\n- using polished assembly 3 as input, repeat minimap2 + racon => polished assembly 4\n\n## Settings\n\n- Run as-is or change parameters at runtime.\n- For the input at \"minimap settings for long reads\", enter (map-pb) for PacBio reads, (map-hifi) for PacBio HiFi reads, or (map-ont) for Oxford Nanopore reads.\n\n## Outputs\n\nThere is one output: the polished assembly in fasta format. \n\n", + "changelog": "# Changelog\n\n## [0.1] 2023-07-15\nFirst release.\n" } ], - "path": "./workflows/genome-assembly/polish-with-long-reads", - "readme": "# Assembly polishing with Racon workflow\n\n## Inputs\n\n- Sequencing reads in format: fastq, fastq.gz, fastqsanger.gz or fastqsanger\n- Genome assembly to be polished, in fasta format\n\n## What does the workflow do\n\n- After long reads have been assembled into a genome (contigs), this can be polished with the same long reads. \n- This workflow uses the tool minimap2 to map the long reads back to the assembly, and then uses Racon to make polishes. \n- This is repeated a further 3 times. \n\nIn more detail:\n\n- minimap2 : long reads are mapped to assembly => overlaps.paf.\n- overaps, long reads, assembly => Racon => polished assembly 1\n- using polished assembly 1 as input; repeat minimap2 + racon => polished assembly 2\n- using polished assembly 2 as input, repeat minimap2 + racon => polished assembly 3\n- using polished assembly 3 as input, repeat minimap2 + racon => polished assembly 4\n\n## Settings\n\n- Run as-is or change parameters at runtime.\n- For the input at \"minimap settings for long reads\", enter (map-pb) for PacBio reads, (map-hifi) for PacBio HiFi reads, or (map-ont) for Oxford Nanopore reads.\n\n## Outputs\n\nThere is one output: the polished assembly in fasta format. \n\n" + "path": "./workflows/genome-assembly/polish-with-long-reads" }, { "version": 1.2, @@ -137,11 +5321,277 @@ "name": "Anna Syme", "orcid": "0000-0002-9906-0673" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Assemble long reads with Flye, then view assembly statistics and assembly graph", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-9906-0673", + "name": "Anna Syme" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.2", + "name": "Genome assembly with Flye", + "report": { + "markdown": "\n# Workflow Execution Report\n\n## Workflow Inputs\n```galaxy\ninvocation_inputs()\n```\n\n## Workflow Outputs\n```galaxy\ninvocation_outputs()\n```\n\n## Workflow\n```galaxy\nworkflow_display()\n```\n\n" + }, + "steps": { + "0": { + "annotation": "Sequence reads e.g. nanopore", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Sequence reads e.g. nanopore", + "name": "Input sequence reads" + } + ], + "label": "Input sequence reads", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 0, + "top": 263.5110244255367 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "501d7387-3bed-4510-891f-a4571a48d9ab", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "", + "content_id": 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This is a fairly simple workflow that assembles a genome from long sequencing reads.\n- It takes in sequencing reads from PacBio (Hifi or non-Hifi), or Oxford Nanopore.\n- If you have PacBio Hifi reads, you may prefer to use a workflow with the assembly tool Hifiasm, such as the those in the suite of VGP workflows. \n\n## Inputs\n\nRaw sequencing reads from PacBio or Oxford Nanopore in format:\nfasta, fasta.gz, fastq, fastq.gz, fastqsanger.gz or fastqsanger\n\n## What does the workflow do\n\n- Assembles the reads with the tool Flye\n- Summarizes the statistics with the tool Fasta statistics\n- Report with the tool Quast\n- Renders the assembly graph with the tool Bandage\n\n## Settings\n\nRun as-is or change parameters at runtime\n\nFor example:\n- change the Flye option of \"mode\" to the correct sequencing type\n- change the Quast option for \"Type of organism\" to correct taxon\n \n## Outputs\n\n- Flye assembly output - four files: fasta, gfa for bandage, graph_dot file, assembly info\n- Fasta statistics\n- Bandage image\n- Quast report\n", + "changelog": "# Changelog\n\n## [0.2] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/flye/flye/2.9.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/flye/flye/2.9.3+galaxy0`\n\nAll notable changes to this project will be documented in this file.\n\nThe format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),\nand this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).\n\n## [0.1] 2023-07-14\nFirst release.\n" } ], - "path": "./workflows/genome-assembly/assembly-with-flye", - "readme": "# Genome assembly with Flye workflow\n\n\n## Why use this workflow?\n\n- This is a fairly simple workflow that assembles a genome from long sequencing reads.\n- It takes in sequencing reads from PacBio (Hifi or non-Hifi), or Oxford Nanopore.\n- If you have PacBio Hifi reads, you may prefer to use a workflow with the assembly tool Hifiasm, such as 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\"0.95\", \"heatmap_bins\": \"20\", \"observed_peak_fraction\": \"0.5\", \"min_consecutive_isotopes\": \"2\", \"score_plot_yaxis_min\": \"0.0\", \"collect_method\": \"correlation_maximum\", \"lowRIA_correlation_threshold\": \"-1.0\", \"force\": false, \"test\": \"False\"}, \"cluster\": false, \"correlation_threshold\": \"0.7\", \"decomposition_threshold\": \"0.7\", \"filter_monoisotopic\": false, \"in_fasta\": {\"__class__\": \"ConnectedValue\"}, \"in_featureXML\": {\"__class__\": \"ConnectedValue\"}, \"in_mzML\": {\"__class__\": \"ConnectedValue\"}, \"intensity_threshold\": \"10.0\", \"labeling_element\": {\"__class__\": \"ConnectedValue\"}, \"mz_tolerance_ppm\": {\"__class__\": \"ConnectedValue\"}, \"plot_extension\": \"png\", \"qc_output_directory\": \"\", \"report_natural_peptides\": false, \"rt_tolerance_s\": \"30.0\", \"use_averagine_ids\": false, \"use_unassigned_ids\": false, \"weight_merge_window\": \"5.0\", \"xic_threshold\": \"0.7\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2.8+galaxy0", + "type": "tool", + "uuid": "224b7012-ffd4-4286-9338-97ac411bb313", + "when": null, + "workflow_outputs": [ + { + "label": "Feature fitting result", + "output_name": "out_csv", + "uuid": "b2370639-8c23-46a6-be8a-b2136d0b8de0" + }, + { + "label": "Peptide centric result", + "output_name": "out_peptide_centric_csv", + "uuid": "1985589f-e690-48e4-a41f-7dc20eb7446f" + } + ] + } + }, + "tags": [], + "uuid": "b03da1a7-fc6f-419f-aa2c-431a670f9a96", + "version": 1 + }, + "readme": "# MetaProSIP: automated inference of elemental fluxes in microbial communities\n\n## Inputs dataset\n\n- `Centroided LC-MS datasets` in mzML (MetaProSIP is mainly tested on data generated by orbitrap instruments)\n- `Fasta Database` in Fasta (aminoacid sequences)\n\n## Inputs values\n\n- `Precursor monoisotopic mass tolerance` (ppm): This value is passed to\n - MSGFPlusAdapter parameter `Precursor monoisotopic mass tolerance` (-precursor_mass_tolerance)\n - MetaProSIP parameter `Tolerance in ppm` (-mz_tolerance_ppm)\n- Fixed modifications\n- Variable modifications\n- Labeled element\n\n## Processing\n\n- DecoyDatabase: Add decoy sequences to the Fasta database (for FDR calculation)\n- FeatureFinderCentroided: identify eluting peptides that correspond to isotopologues with natural isotopic distributions \n- MSGFPlusAdapter: identify peptides through peptide fragment fingerprinting (database search)\n- FeatureFinderMultiplex: detect elution profiles of unlabeled peptides\n- PeptideIndexer: annotate protein association to identified peptides\n- FalseDiscoveryRate: Calculate FDR\n- IDMapper: map identified spectra to elution profiles\n- MetaProSIP: calculate the protein-SIP features, to perform functional grouping, and for protein inference\n", + "changelog": "# Changelog\n\n## [0.1] 2023-04-13\nFirst release.\n" } ], - "path": "./workflows/proteomics/openms-metaprosip", - "readme": "# MetaProSIP: automated inference of elemental fluxes in microbial communities\n\n## Inputs dataset\n\n- `Centroided LC-MS datasets` in mzML (MetaProSIP is mainly tested on data generated by orbitrap instruments)\n- `Fasta Database` in Fasta (aminoacid sequences)\n\n## Inputs values\n\n- `Precursor monoisotopic mass tolerance` (ppm): This value is passed to\n - MSGFPlusAdapter parameter `Precursor monoisotopic mass tolerance` (-precursor_mass_tolerance)\n - MetaProSIP parameter `Tolerance in ppm` (-mz_tolerance_ppm)\n- Fixed modifications\n- Variable modifications\n- Labeled element\n\n## Processing\n\n- DecoyDatabase: Add decoy sequences to the Fasta database (for FDR calculation)\n- FeatureFinderCentroided: identify eluting peptides that correspond to isotopologues with natural isotopic distributions \n- MSGFPlusAdapter: identify peptides through peptide fragment fingerprinting (database search)\n- FeatureFinderMultiplex: detect elution profiles of unlabeled peptides\n- PeptideIndexer: annotate protein association to identified peptides\n- FalseDiscoveryRate: Calculate FDR\n- IDMapper: map identified spectra to elution profiles\n- MetaProSIP: calculate the protein-SIP features, to perform functional grouping, and for protein inference\n" + "path": "./workflows/proteomics/openms-metaprosip" }, { "version": 1.2, @@ -181,11 +6191,187 @@ "name": "Romane Libouban", "email": "romane.libouban@irisa.fr" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "", + "format-version": "0.1", + "license": "MIT", + "release": "0.1", + "name": "Repeat masking with RepeatModeler and RepeatMasker", + "creator": [ + { + "class": "Person", + "email": "mailto:romane.libouban@irisa.fr", + "name": "Romane Libouban" + } + ], + "steps": { + "0": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Apply repeat masking to this fasta file", + "name": "input" + } + ], + "label": "input", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 10, + "top": 10 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "ab5e19b0-ce35-4e54-a55e-f75243c86e3d", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/csbl/repeatmodeler/repeatmodeler/2.0.4+galaxy1", + "errors": null, + "id": 1, + "input_connections": { + "input_file": { + "id": 0, + "output_name": "output" + } + }, + "inputs": [], + "label": null, + "name": "RepeatModeler", + "outputs": [ + { + "name": "sequences", + "type": "fasta" + }, + { + "name": "seeds", + "type": "stockholm" + } + ], + "position": { + "left": 230, + "top": 10 + }, + "post_job_actions": {}, + "tool_id": "toolshed.g2.bx.psu.edu/repos/csbl/repeatmodeler/repeatmodeler/2.0.4+galaxy1", + "tool_shed_repository": { + "changeset_revision": "8661b2607b7e", + "name": "repeatmodeler", + "owner": "csbl", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__input_ext\": \"input\", \"chromInfo\": \"/shared/ifbstor1/galaxy/mutable-config/tool-data/shared/ucsc/chrom/?.len\", \"input_file\": null, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2.0.4+galaxy1", + "type": "tool", + "uuid": "9312ba36-4275-4d40-8ba6-95eea1b23b11", + "when": null, + "workflow_outputs": [ + { + "output_name": "sequences", + "label": "RepeatModeler consensus sequences" + }, + { + "output_name": "seeds", + "label": "RepeatModeler seeds alignments" + } + ] + }, + "2": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/repeat_masker/repeatmasker_wrapper/4.1.5+galaxy0", + "errors": null, + "id": 2, + "input_connections": { + "input_fasta": { + "id": 1, + "output_name": "sequences" + } + }, + "inputs": [], + "label": null, + "name": "RepeatMasker", + "outputs": [ + { + "name": "output_masked_genome", + "type": "fasta" + }, + { + "name": "output_log", + "type": "tabular" + }, + { + "name": "output_table", + "type": "txt" + }, + { + "name": "output_repeat_catalog", + "type": "txt" + }, + { + "name": "output_gff", + "type": "gff" + } + ], + "position": { + "left": 450, + "top": 10 + }, + "post_job_actions": {}, + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/repeat_masker/repeatmasker_wrapper/4.1.5+galaxy0", + "tool_shed_repository": { + "changeset_revision": "ba6d2c32f797", + "name": "repeat_masker", + "owner": "bgruening", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__input_ext\": \"input\", \"advanced\": {\"is_only\": false, \"is_clip\": false, \"no_is\": false, \"rodspec\": false, \"primspec\": false, \"nolow\": false, \"noint\": false, \"norna\": false, \"alu\": false, \"div\": false, \"search_speed\": \"\", \"frag\": \"40000\", \"gc\": null, \"gccalc\": false, \"nocut\": false, \"xout\": false, \"keep_alignments\": false, \"invert_alignments\": false, \"poly\": false}, \"chromInfo\": \"/shared/ifbstor1/galaxy/mutable-config/tool-data/shared/ucsc/chrom/?.len\", \"excln\": true, \"gff\": true, \"input_fasta\": null, \"repeat_source\": {\"source_type\": \"dfam\", \"__current_case__\": 0, \"species_source\": {\"species_from_list\": \"no\", \"__current_case__\": 1, \"species_name\": \"\"}}, \"xsmall\": true, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "4.1.5+galaxy0", + "type": "tool", + "uuid": "e6c8e6a1-efe8-4291-b12b-5fdb3795b6ca", + "when": null, + "workflow_outputs": [ + { + "output_name": "output_masked_genome", + "label": "RepeatMasker masked genome" + }, + { + "output_name": "output_log", + "label": "RepeatMasker output log" + }, + { + "output_name": "output_table", + "label": "RepeatMasker repeat statistics" + }, + { + "output_name": "output_repeat_catalog", + "label": "RepeatMasker repeat catalog" + }, + { + "output_name": "output_gff", + "label": "RepeatMasker repeat annotation" + } + ] + } + }, + "tags": [], + "uuid": "f25be8fa-7823-456f-9707-a497703f48d7", + "version": 0 + }, + "readme": "# RepeatMasking Workflow\n\nThis workflow uses RepeatModeler and RepeatMasker for genome analysis.\n\n- RepeatModeler is a software package for identifying and modeling de novo families of transposable elements (TEs). At the heart of RepeatModeler are three de novo repeat search programs (RECON, RepeatScout and LtrHarvest/Ltr_retriever) which use complementary computational methods to identify repeat element boundaries and family relationships from sequence data.\n\n- RepeatMasker is a program that analyzes DNA sequences for *interleaved repeats* and *low-complexity* DNA sequences. The result of the program is a detailed annotation of the repeats present in the query sequence, as well as a modified version of the query sequence in which all annotated repeats are present.\n\n## Input dataset for RepeatModeler\n- RepeatModeler requires a single input file, a genome in fasta format.\n\n\n## Outputs dataset for RepeatModeler\n- Two output files are generated:\n - summary file (.tbl)\n - fasta file containing alignments in order of appearance in the query sequence\n\n\n## Input dataset for RepeatMasker\n- ReapatMasker requires the fasta file generated by RepeatModeler\n\n## Outputs datasets for RepeatMasker\n- Five output files are generated:\n - a fasta file\n - .gff3 file\n - a table summarizing the repeated content of the sequence analyzed\n - a file with statistics related to the repeated content of the sequence analyzed\n - a summary of the mutation sites found and the order of grouping\n \n", + "changelog": "# Changelog\n\n## [0.1]\n\nInitial version of the RepeatMasking workflow for genomic sequencing data." } ], - "path": "./workflows/repeatmasking", - "readme": "# RepeatMasking Workflow\n\nThis workflow uses RepeatModeler and RepeatMasker for genome analysis.\n\n- RepeatModeler is a software package for identifying and modeling de novo families of transposable elements (TEs). At the heart of RepeatModeler are three de novo repeat search programs (RECON, RepeatScout and LtrHarvest/Ltr_retriever) which use complementary computational methods to identify repeat element boundaries and family relationships from sequence data.\n\n- RepeatMasker is a program that analyzes DNA sequences for *interleaved repeats* and *low-complexity* DNA sequences. The result of the program is a detailed annotation of the repeats present in the query sequence, as well as a modified version of the query sequence in which all annotated repeats are present.\n\n## Input dataset for RepeatModeler\n- RepeatModeler requires a single input file, a genome in fasta format.\n\n\n## Outputs dataset for RepeatModeler\n- Two output files are generated:\n - summary file (.tbl)\n - fasta file containing alignments in order of appearance in the query sequence\n\n\n## Input dataset for RepeatMasker\n- ReapatMasker requires the fasta file generated by RepeatModeler\n\n## Outputs datasets for RepeatMasker\n- Five output files are generated:\n - a fasta file\n - .gff3 file\n - a table summarizing the repeated content of the sequence analyzed\n - a file with statistics related to the repeated content of the sequence analyzed\n - a summary of the mutation sites found and the order of grouping\n \n" + "path": "./workflows/repeatmasking" }, { "version": 1.2, @@ -203,11 +6389,860 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow take as input a collection of paired fastq. Remove adapters with cutadapt, map pairs with bowtie2 allowing dovetail. Keep MAPQ30 and concordant pairs. BAM to BED. MACS2 with \"ATAC\" parameters.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.10", + "name": "CUTandRUN", + "steps": { + "0": { + "annotation": "Should be a paired collection with CUT and RUN fastqs", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Should be a paired collection with CUT and RUN fastqs", + "name": "PE fastq input" + } + ], + "label": "PE fastq input", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 268 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list:paired\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "9fbb875d-05b1-4557-bd2e-710f80dd1a21", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Please use: For R1: - For TrueSeq (CUT and RUN): GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC - For Nextera (CUT and TAG): CTGTCTCTTATACACATCTCCGAGCCCACGAGAC ", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "Please use: For R1: - For TrueSeq (CUT and RUN): GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC - For Nextera (CUT and TAG): CTGTCTCTTATACACATCTCCGAGCCCACGAGAC ", + "name": "adapter_forward" + } + ], + "label": "adapter_forward", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 22, + "top": 375 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "1eac70a4-a4b7-42c7-82cd-913f23b4f941", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "Please use: For R2: - For TruSeq (CUT and RUN): GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT or AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT - For Nextera (CUT and TAG): CTGTCTCTTATACACATCTGACGCTGCCGACGA", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "Please use: For R2: - For TruSeq (CUT and RUN): GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT or AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT - For Nextera (CUT and TAG): CTGTCTCTTATACACATCTGACGCTGCCGACGA", + "name": "adapter_reverse" + } + ], + "label": "adapter_reverse", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 62, + "top": 483 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "68b198e5-7de8-445f-807f-7f432090e2c7", + "when": null, + "workflow_outputs": [] + }, + "3": { + "annotation": "reference_genome", + "content_id": null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "reference_genome", + "name": 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Usually CUT&RUN is Truseq and CUT&TAG is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera\n- reference_genome: this field will be adapted to the genomes available for bowtie2\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb\n- The BAM is filtered to keep only MAPQ30 and concordant pairs\n- The PCR duplicates are removed with Picard (only from version 0.6)\n- The BAM is converted to BED to enable macs2 to take both pairs into account\n- The peaks are called with macs2 which at the same time generates a coverage file (normalized or not).\n- The coverage file is converted to bigwig\n- A multiQC is run to have an overview of the QC\n", + "changelog": "# Changelog\n\n## [0.10] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.9] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.8] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.7] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/3.1.1.0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.6.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.6] 2023-10-19\n\nFix the remove duplicate step!\nIn all previous versions, due to an error, PCR duplicates were not removed.\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-03-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.3` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-06\nFirst release.\n" } ], - "path": "./workflows/epigenetics/cutandrun", - "readme": "# CUT&RUN (and CUT&TAG) Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. 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\"cutadapt\", \"__current_case__\": 5, \"input\": {\"__class__\": \"ConnectedValue\"}}}, {\"__index__\": 1, \"software_cond\": {\"software\": \"bowtie2\", \"__current_case__\": 3, \"input\": {\"__class__\": \"ConnectedValue\"}}}, {\"__index__\": 2, \"software_cond\": {\"software\": \"macs2\", \"__current_case__\": 16, \"input\": {\"__class__\": \"ConnectedValue\"}}}], \"saveLog\": false, \"title\": \"\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.11+galaxy1", + "type": "tool", + "uuid": "fb066848-43df-412a-9767-9613bac7d961", + "when": null, + "workflow_outputs": [ + { + "label": "MultiQC webpage", + "output_name": "html_report", + "uuid": "2167289f-6c78-479a-8d3b-95caf11d0c4e" + }, + { + "label": "MultiQC on input dataset(s): Stats", + "output_name": "stats", + "uuid": "d4c3e0a7-d5b7-4307-8669-0254a3723ce0" + } + ] + } + }, + "tags": [ + "ChIP" + ], + "uuid": "fe6bda9f-1fc2-4a86-bf8d-e779c79466fc", + "version": 1 + }, + "readme": "# ChIP-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of fastqsanger files.\n\n## Inputs values\n\n- adapters sequence_forward: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30.\n- The peaks are called with MACS2 with a fixed extension of 200bp which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n", + "changelog": "# Changelog\n\n## [0.9] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.8] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.7] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-18\nFirst release.\n" } ], - "path": "./workflows/epigenetics/chipseq-sr", - "readme": "# ChIP-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of fastqsanger files.\n\n## Inputs values\n\n- adapters sequence_forward: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30.\n- The peaks are called with MACS2 with a fixed extension of 200bp which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n" + "path": "./workflows/epigenetics/chipseq-sr" }, { "version": 1.2, @@ -247,7 +7976,1221 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a collection of paired fastq. It uses HiCUP to go from fastq to validPair file using the middle of the fragment as coordinates. The pairs are filtered for MAPQ and sorted by cooler to generate a tabix dataset. Cooler is used to generate a balanced cool file to the desired resolution.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.3", + "name": "Hi-C_fastqToCool_hicup_cooler", + "steps": { + "0": { + "annotation": "Should be a paired collection with Hi-C fastqs", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Should be a paired collection with Hi-C fastqs", + "name": "PE fastq input" + } + ], + "label": "PE fastq input", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 101.53334045410156 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list:paired\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "30fe3d0f-541a-478a-b57d-a43c0c16ccad", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "only use genome ids which have bowtie2 indexes", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "only use genome ids which have bowtie2 indexes", + "name": "genome name" + } + ], + "label": "genome name", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 39.01666259765625, + "top": 171.5 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "45194ed6-a1e9-4248-8d3a-f51febc36d61", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "Restriction enzyme used e.g. A^GATCT,BglII. 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"output_name": "outFileName", + "uuid": "27b9c4ea-2a6a-4477-bd5e-7f69a89d69fa" + } + ] + } + }, + "tags": [ + "Hi-C" + ], + "uuid": "2196fbff-317e-437d-a022-696a1f95a850", + "version": 4 + }, + "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", + "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" }, { "name": "chic-fastq-to-cool-hicup-cooler", @@ -262,7 +9205,1436 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow take as input a collection of paired fastq. 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Cooler is used to generate a balanced cool file to the desired resolution.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.3", + "name": "cHi-C_fastqToCool_hicup_cooler", + "steps": { + "0": { + "annotation": "Should be a paired collection with Hi-C fastqs", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Should be a paired collection with Hi-C fastqs", + "name": "PE fastq input" + } + ], + "label": "PE fastq input", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 39.12167999999406 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list:paired\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "30fe3d0f-541a-478a-b57d-a43c0c16ccad", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "only use genome ids which have bowtie2 indexes", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "only use genome ids which have bowtie2 indexes", + "name": "genome name" + } + ], + "label": "genome name", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 39, + "top": 109.12167999999406 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "45194ed6-a1e9-4248-8d3a-f51febc36d61", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "Restriction enzyme used e.g. A^GATCT,BglII. 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case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", + "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" }, { "name": "hic-juicermediumtabix-to-cool-cooler", @@ -277,7 +10649,311 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow uses as input a collection of juicer medium tabix files and a genome name. It builds balanced cool file to the desired resolution.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.3", + "name": "Hi-C_juicermediumtabixToCool_cooler", + "steps": { + "0": { + "annotation": "For example 10000 for 10kb", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "For example 10000 for 10kb", + "name": "Bin size in bp" + } + ], + "label": "Bin size in bp", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0, + "top": 33.5 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "d0a82863-82f8-426c-addb-06066e9d0a73", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "This is used to get the chromosome sizes", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "This is used to get the chromosome sizes", + "name": "genome name" + } + ], + "label": "genome name", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 46, + "top": 123.5 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "48506f80-b1b5-4d1d-98a6-c6882de026f1", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Juicer Medium Tabix with validPairs" + } + ], + "label": "Juicer Medium Tabix with validPairs", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 129.25, + "top": 208.25 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "588962a4-8ce4-4929-81fd-a9dfdd032598", + "when": null, + "workflow_outputs": [] + }, + "3": { + "annotation": "Recommended value: cis-only", + "content_id": null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "Recommended value: cis-only", + "name": "Interactions to consider to calculate weights in normalization step" + } + ], + "label": "Interactions to consider to calculate weights in normalization step", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 221, + "top": 309.75 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "d6375500-a591-47a9-b126-950347e3e7a8", + "when": null, + "workflow_outputs": [] + }, + "4": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/lldelisle/cooler_makebins/cooler_makebins/0.9.3+galaxy0", + "errors": null, + "id": 4, + "input_connections": { + "binsize": { + "id": 0, + "output_name": "output" + }, + "size_source|fasta_cached": { + "id": 1, + "output_name": "output" + } + }, + "inputs": [], + "label": "make bed with bins", + "name": "cooler_makebins", + "outputs": [ + { + "name": "output", + "type": "bed" + } + ], + "position": { + "left": 489.25, + "top": 0 + }, + "post_job_actions": { + "HideDatasetActionoutput": { + "action_arguments": {}, + "action_type": "HideDatasetAction", + "output_name": "output" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/lldelisle/cooler_makebins/cooler_makebins/0.9.3+galaxy0", + "tool_shed_repository": { + "changeset_revision": "ebd2a52eb245", + "name": "cooler_makebins", + "owner": "lldelisle", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"binsize\": {\"__class__\": \"ConnectedValue\"}, \"size_source\": {\"size_source_selector\": \"cached\", \"__current_case__\": 0, \"fasta_cached\": {\"__class__\": \"ConnectedValue\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.9.3+galaxy0", + "type": "tool", + "uuid": "34e0a213-93e8-466e-b07b-ede1443ee7d6", + "when": null, + "workflow_outputs": [] + }, + "5": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/lldelisle/cooler_cload_tabix/cooler_cload_tabix/0.9.3+galaxy1", + "errors": null, + "id": 5, + "input_connections": { + "assembly": { + "id": 1, + "output_name": "output" + }, + "format_sel|input_pairs": { + "id": 2, + "output_name": "output" + }, + "input_bed": { + "id": 4, + "output_name": "output" + } + }, + "inputs": [], + "label": "Load pairs in matrix", + "name": "cooler_cload_tabix", + "outputs": [ + { + "name": "output", + "type": "cool" + } + ], + "position": { + "left": 762.25, + "top": 58 + }, + "post_job_actions": { + "RenameDatasetActionoutput": { + "action_arguments": { + "newname": "matrix with raw values" + }, + "action_type": "RenameDatasetAction", + "output_name": "output" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/lldelisle/cooler_cload_tabix/cooler_cload_tabix/0.9.3+galaxy1", + "tool_shed_repository": { + "changeset_revision": "0641e1c892c6", + "name": "cooler_cload_tabix", + "owner": "lldelisle", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"assembly\": {\"__class__\": \"ConnectedValue\"}, \"format_sel\": {\"format\": \"juicer_medium\", \"__current_case__\": 0, \"input_pairs\": {\"__class__\": \"ConnectedValue\"}}, \"input_bed\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.9.3+galaxy1", + "type": "tool", + "uuid": "d411eea7-7996-44f2-af2a-feecb854a067", + "when": null, + "workflow_outputs": [ + { + "label": "matrix with raw values", + "output_name": "output", + "uuid": "d398b493-9b5d-412f-a06d-d1cfdc904feb" + } + ] + }, + "6": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/lldelisle/cooler_balance/cooler_balance/0.9.3+galaxy0", + "errors": null, + "id": 6, + "input_connections": { + "cistrans": { + "id": 3, + "output_name": "output" + }, + "input": { + "id": 5, + "output_name": "output" + } + }, + "inputs": [ + { + "description": "runtime parameter for tool cooler_balance", + "name": "blacklist" + } + ], + "label": "ICE normalization", + "name": "cooler_balance", + "outputs": [ + { + "name": "output", + "type": "cool" + } + ], + "position": { + "left": 991.25, + "top": 254.5 + }, + "post_job_actions": { + "RenameDatasetActionoutput": { + "action_arguments": { + "newname": "matrix with iced values" + }, + "action_type": "RenameDatasetAction", + "output_name": "output" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/lldelisle/cooler_balance/cooler_balance/0.9.3+galaxy0", + "tool_shed_repository": { + "changeset_revision": "8f9fe0667b89", + "name": "cooler_balance", + "owner": "lldelisle", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"blacklist\": {\"__class__\": \"RuntimeValue\"}, \"cistrans\": {\"__class__\": \"ConnectedValue\"}, \"convergencepolicy\": \"error\", \"ignorediags\": \"2\", \"ignoredist\": \"0\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"madmax\": \"5\", \"maxiters\": \"200\", \"mincount\": \"0\", \"minnnz\": \"10\", \"name\": \"weight\", \"tol\": \"1e-05\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.9.3+galaxy0", + "type": "tool", + "uuid": "44270887-1c96-4ede-8bb9-3db2a07eeb6e", + "when": null, + "workflow_outputs": [ + { + "label": "matrix with iced values", + "output_name": "output", + "uuid": "1d4fe955-922e-40bf-b879-a71290af3ea7" + } + ] + } + }, + "tags": [ + "Hi-C" + ], + "uuid": "48733b55-4cde-45d4-a69e-78faff0db3f5", + "version": 1 + }, + "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", + "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" }, { "name": "hic-fastq-to-pairs-hicup", @@ -292,11 +10968,457 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a collection of paired fastq. It uses HiCUP to go from fastq to validPair file. First truncate the fastq using the cutting sequence to guess the fill-in. Then map the truncated fastq. Then asign to fragment and filter the self-ligated and dandling ends or internal (it can also filter for the size). Then it removes the duplicates. Convert the output to be compatible with juicebox or cooler using the middle of the fragment as coordinates. Finally filter for mapping quality", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.3", + "name": "Hi-C_fastqToPairs_hicup", + "steps": { + "0": { + "annotation": "Should be a paired collection with Hi-C fastqs", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Should be a paired collection with Hi-C fastqs", + "name": "PE fastq input" + } + ], + "label": "PE fastq input", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 12.5 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list:paired\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "30fe3d0f-541a-478a-b57d-a43c0c16ccad", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "use the bowtie2 indexes to display choices", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "use the bowtie2 indexes to display choices", + "name": "genome name" + } + ], + "label": "genome name", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 39, + "top": 82.5 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "45194ed6-a1e9-4248-8d3a-f51febc36d61", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "Restriction enzyme used e.g. A^GATCT,BglII. Some Hi-C protocols may use several enzymes. To specify several enzymes, use the ':' to separate them e.g. A^GATCT,BglII:A^AGCTT,HindIII:^GATC,DpnII. HiCUP accomodates N in restriction enzyme: e.g. :A^ANCTT", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "Restriction enzyme used e.g. A^GATCT,BglII. Some Hi-C protocols may use several enzymes. To specify several enzymes, use the ':' to separate them e.g. A^GATCT,BglII:A^AGCTT,HindIII:^GATC,DpnII. HiCUP accomodates N in restriction enzyme: e.g. :A^ANCTT", + "name": "Restriction enzyme" + } + ], + "label": "Restriction enzyme", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 58, + "top": 155.5 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "ec011ceb-c601-464f-8661-ca9c0b335bb5", + "when": null, + "workflow_outputs": [] + }, + "3": { + "annotation": "Hi-C protocol did NOT include a fill-in of sticky ends prior to re-ligation and therefore reads shall be truncated at the restriction site sequence", + "content_id": null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "Hi-C protocol did NOT include a fill-in of sticky ends prior to re-ligation and therefore reads shall be truncated at the restriction site sequence", + "name": "No fill-in" + } + ], + "label": "No fill-in", + "name": "Input parameter", + 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"uuid": "48f579ea-eaac-49ee-b38f-93c82f8b7d76", + "version": 2 + }, + "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", + "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" } ], - "path": "./workflows/epigenetics/hic-hicup-cooler", - "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and 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"19023604-eee1-4099-b1c2-abe3de93b3f3" + } + ] + } + }, + "tags": [], + "uuid": "c6ed4b0e-d719-4997-9860-ba99488ec332", + "version": 6 + }, + "readme": "# Average Bigwig between replicates\n\nThis workflow is very useful when you processed multiple samples in collections and you want to generate an average coverage per condition.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of bigwigs (normalized). The identifiers of your bigwigs must be like:\n - whatever_sample1_identificationOfReplicate1\n - whatever_sample1_identificationOfReplicate2\n - ...\n - whatever_sample2_identificationOfReplicate1\n - whatever_sample2_identificationOfReplicate2\n - ...\n\n## Inputs values\n\n- bin_size: this is used when average of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs. I suggest 5bp for RNA-seq and 50bp for other applications.\n\n## Processing\n\n- The workflow will split identifiers between everything which is before the last underscore which will be the *sample* and everything which is after the last underscore which will be the *replicate identifier*. And restructure the collection as list:list:\n - whatever_sample1:\n - identificationOfReplicate1\n - identificationOfReplicate2\n - ...\n - whatever_sample2:\n - identificationOfReplicate1\n - identificationOfReplicate2\n - ---\n - ...\n- Then it will average bigwigs into each inner list\n\n## Outputs\n\n- The output is a collection of bigwig datasets like:\n - whatever_sample1\n - whatever_sample2\n - ...\n", + "changelog": "# Changelog\n\n## [0.2] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.1] 2023-09-22\nFirst release.\n" } ], - "path": "./workflows/epigenetics/average-bigwig-between-replicates", - "readme": "# Average Bigwig between replicates\n\nThis workflow is very useful when you processed multiple samples in collections and you want to generate an average coverage per condition.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of bigwigs (normalized). The identifiers of your bigwigs must be like:\n - whatever_sample1_identificationOfReplicate1\n - whatever_sample1_identificationOfReplicate2\n - ...\n - whatever_sample2_identificationOfReplicate1\n - whatever_sample2_identificationOfReplicate2\n - ...\n\n## Inputs values\n\n- bin_size: this is used when average of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs. I suggest 5bp for RNA-seq and 50bp for other applications.\n\n## Processing\n\n- The workflow will split identifiers between everything which is before the last underscore which will be the *sample* and everything which is after the last underscore which will be the *replicate identifier*. 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\"bargraph\", \"section_name\": \"Reads in peaks\", \"title\": \"Number of reads in peaks\", \"description\": \"Number of reads falling 500bp from a summit\", \"xlab\": \"\", \"ylab\": \"\", \"input\": {\"__class__\": \"ConnectedValue\"}}}], \"saveLog\": false, \"title\": \"\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.11+galaxy1", + "type": "tool", + "uuid": "112d720f-c747-4c92-985f-ebdb52086cc9", + "when": null, + "workflow_outputs": [ + { + "label": "MultiQC webpage", + "output_name": "html_report", + "uuid": "c22aafb2-d9f2-43c3-a6c4-cfe4a3166c07" + }, + { + "label": "MultiQC on input dataset(s): Stats", + "output_name": "stats", + "uuid": "6071150d-48db-4cf8-bfed-2cbdb2635856" + } + ] + } + }, + "tags": [ + "ATACseq" + ], + "uuid": "02785f0c-c445-4419-9f95-a202eaf6493a", + "version": 1 + }, + "readme": "# ATACseq Workflow\n\nThis workflow is highly concordant with the corresponding training material.\nYou can have more information about ATAC-seq analysis in the [slides](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/slides.html) and the [tutorial](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/tutorial.html).\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- reference_genome: this field will be adapted to the genomes available for bowtie2 and the genomes available for bedtools slopbed (dbkeys table)\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- bin_size: this is used when normalization of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs.\n\n## Processing\n\n- The workflow will remove nextera adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb.\n- The BAM is filtered to keep only MAPQ30, concordant pairs and pairs outside of the mitochondria.\n- The PCR duplicates are removed with Picard (only from version 0.8).\n- The BAM is converted to BED to enable macs2 to take both pairs into account.\n- The peaks are called with macs2 which at the same time generates a coverage file.\n- The coverage file is converted to bigwig\n- The amount of reads 500bp from summits and the total number of reads are computed.\n- Two normalizations are computed:\n - By million reads\n - By million reads in peaks (500bp from summits)\n- Other QC are performed:\n - A histogram with fragment length is computed.\n - The evaluation of percentage of reads to chrM or MT is computed.\n- A multiQC is run to have an overview of the QC.\n\n### Warning\n\n- The `reference_genome` parameter value is used to select references in bowtie2 and bedtools slopbed. Only references that are present in bowtie2 **and** bedtools slopbed are selectable. If your favorite reference genome is not available ask your administrator to make sure that each bowtie2 reference has a corresponding len file for use in bedtools slopbed.\n", + "changelog": "# Changelog\n\n## [0.14] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.13] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.12] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.11] 2024-03-18\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy2`\n\n## [0.10] 2024-03-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/samtools_idxstats/samtools_idxstats/2.0.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/samtools_idxstats/samtools_idxstats/2.0.5`\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/3.1.1.0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.9] 2023-10-23\n\nFix the normalization factor. It was coverage per reads and per reads in peaks instead of per million reads and per million reads in peaks.\n\n## [0.8] 2023-10-19\n\nFix the remove duplicate step!\nIn all previous versions, due to an error, PCR duplicates were not removed.\n\n## [0.7] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.6] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.5.1] 2023-09-22\n\nFix bug in normalize profiles when used with multiple samples (in 0.5.0 it is averaging samples instead of normalizing each sample).\n\n## [0.5] 2023-03-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.3` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_coveragebed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_coveragebed/2.30.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- add normalization steps for coverage\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-12\nFirst release.\n" } ], - "path": "./workflows/epigenetics/atacseq", - "readme": "# ATACseq Workflow\n\nThis workflow is highly concordant with the corresponding training material.\nYou can have more information about ATAC-seq analysis in the [slides](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/slides.html) and the [tutorial](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/tutorial.html).\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- reference_genome: this field will be adapted to the genomes available for bowtie2 and the genomes available for bedtools slopbed (dbkeys table)\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- bin_size: this is used when normalization of coverage is performed. 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Only references that are present in bowtie2 **and** bedtools slopbed are selectable. If your favorite reference genome is not available ask your administrator to make sure that each bowtie2 reference has a corresponding len file for use in bedtools slopbed.\n" + "path": "./workflows/epigenetics/atacseq" }, { "version": 1.2, @@ -400,11 +17475,736 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a collection of paired fastqs. Remove adapters with cutadapt, map pairs with bowtie2. Keep MAPQ30 and concordant pairs. MACS2 for paired bam.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.9", + "name": "ChIPseq_PE", + "steps": { + "0": { + "annotation": "Should be a paired collection with ChIPseq fastqs", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Should be a paired collection with ChIPseq fastqs", + "name": "PE fastq input" + } + ], + "label": "PE fastq input", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 0 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list:paired\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "e09c0852-1db3-4a68-b88c-1b94c205cb6c", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Please use: For R1: - For Nextera: 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If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Fragments.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any pair with mate smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30 and concordant pairs.\n- The peaks are called with MACS2 which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n\n## Contribution\n\n@lldelisle wrote the workflow.\n\n@nagoue updated the tools, made it work in usegalaxy.org, fixed the best practices and wrote the tests.\n", + "changelog": "# Changelog\n\n## [0.9] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.8] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.7] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.6.1] 2024-03-14\n\nFix bug introduced in 0.6: the second adapter sequence was not used.\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## 2022-10-20\nChIPseq_PE has been renamed chipseq-pe (still version 0.1)\n\n## [0.1] 2022-10-06\nFirst release.\n" } ], - "path": "./workflows/epigenetics/chipseq-pe", - "readme": "# ChIP-seq paired-end Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapters sequences: this depends on the library preparation. 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This is important because the dada2 step outputs\na collection in sorted order. 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Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. 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null}", + "tool_version": "2023.5.0+q2galaxy.2023.5.0.2", + "type": "tool", + "uuid": "cf48f270-6c6c-4fad-8c1d-2b02bb73ae49", + "when": null, + "workflow_outputs": [ + { + "label": "Summary of the demultiplexing", + "output_name": "visualization", + "uuid": "1aa2fe61-6a59-44c9-8079-a1d4a7ed8345" + } + ] + } + }, + "tags": [], + "uuid": "b09b5420-bb7c-4f27-9c90-7e2031889379", + "version": 49 + }, + "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." }, { "name": "QIIME2-Ic import demultiplexed data single end", @@ -489,7 +19951,293 @@ "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", "address": "Permoserstra\u00dfe 15, 04318 Leipzig" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Importing demultiplexed data (single-end)", + "creator": [ + { + "class": "Person", + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.1", + "name": "QIIME2 Ic: Demultiplexed data (single-end)", + "steps": { + "0": { + "annotation": "A collection of single-end demultiplexed sequences", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "A collection of single-end demultiplexed sequences", + "name": "Sequence collection" + } + ], + "label": "Sequence collection", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 9.339782603705014 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"fastqsanger.gz\", \"fastqillumina.gz\"], \"tag\": null, \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "35c1a1b1-daeb-4cd1-bd91-e5f0016ec79a", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Extract a list of the names of sequence files", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/collection_element_identifiers/collection_element_identifiers/0.0.2", + "errors": null, + "id": 1, + "input_connections": { + "input_collection": { + "id": 0, + "output_name": "output" + } + }, + "inputs": [], + "label": "Extract element identifiers", + "name": "Extract element identifiers", + "outputs": [ + { + 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}, + "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." }, { "name": "QIIME2-Id import demultiplexed data paired end", @@ -508,11 +20256,284 @@ "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", "address": "Permoserstra\u00dfe 15, 04318 Leipzig" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Importing demultiplexed data (paired-end)", + "creator": [ + { + "class": "Person", + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ" + } + ], + "format-version": "0.1", + "release": "0.1", + "license": "MIT", + "name": "QIIME2 Id: Demultiplexed data (paired-end)", + "steps": { + "0": { + "annotation": "Import of the paired-end demultiplexed sequences", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Import 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"changeset_revision": "d8a9f74f1a6d", + "name": "qiime2__demux__summarize", + "owner": "q2d2", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__q2galaxy__GUI__section__extra_opts__\": {\"n\": \"10000\"}, \"data\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2023.5.0+q2galaxy.2023.5.0.2", + "type": "tool", + "uuid": "cf48f270-6c6c-4fad-8c1d-2b02bb73ae49", + "when": null, + "workflow_outputs": [ + { + "label": "visualization", + "output_name": "visualization", + "uuid": "e7d259fd-ffa7-4d18-af74-343cedca4d8f" + } + ] + } + }, + "tags": [], + "uuid": "f4887024-6f68-4d53-a889-5635366dd18d", + "version": 2 + }, + "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." } ], - "path": "./workflows/amplicon/qiime2/qiime2-I-import", - "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." + "path": "./workflows/amplicon/qiime2/qiime2-I-import" }, { "version": 1.2, @@ -534,7 +20555,381 @@ "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", "address": "Permoserstra\u00dfe 15, 04318 Leipzig" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Use DADA2 for sequence quality control. DADA2 is a pipeline for detecting and correcting (where possible) Illumina amplicon sequence data. As implemented in the q2-dada2 plugin, this quality control process will additionally filter any phiX reads (commonly present in marker gene Illumina sequence data) that are identified in the sequencing data, and will filter chimeric sequences.", + "comments": [], + "creator": [ + { + "class": "Person", + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ" + } + ], + "format-version": "0.1", + "release": "0.1", + "license": "MIT", + "name": "QIIME2 IIa: Denoising (sequence quality control) and feature table creation (single-end)", + "steps": { + "0": { + "annotation": "Tab separated metadata file", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Tab separated metadata file", + "name": "Metadata" + } + ], + "label": "Metadata", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 0, + "top": 140.20380466285837 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"tabular\"], \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "8dde0c69-40f1-415a-a866-5d1115e80cdf", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Demultiplexed sequences in qza format", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "Demultiplexed sequences in qza format", + "name": "Demultiplexed sequences" + } + ], + "label": "Demultiplexed sequences", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 0.7889777582004348, + "top": 256.1421426050462 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"qza\"], \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "e250ddc1-f567-40ca-9f2b-e07bbf84cdec", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "Length to which the sequence sould be truncated. 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\"__q2galaxy__GUI__conditional__sample_metadata__\": {\"type\": \"tsv\", \"__current_case__\": 0, \"source\": {\"__class__\": \"ConnectedValue\"}}}]}, \"table\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2023.5.0+q2galaxy.2023.5.0.2", + "type": "tool", + "uuid": "f6376403-1be3-4bc0-af85-d5e2e04984b2", + "when": null, + "workflow_outputs": [ + { + "label": "DADA2 output table", + "output_name": "visualization", + "uuid": "13960a03-ee65-4385-8936-b7ff5e5a98f3" + } + ] + } + }, + "tags": [], + "uuid": "718df5b9-9cbb-4792-be50-604e18ef0548", + "version": 2 + }, + "readme": "# QIIME2 workflows\n\n## Available workflows\n\nDenoising (using `qiime2`'s `dada2` integration for paired / single end data.\n\n## Inputs\n\n- Demultiplexed sequences as a qiime2 aertifact file (`qza`) containing the sequence information.\n- Metadata table (`tabular`)\n- Truncation length\n- Trimming length (optional)\n\nFor the paired end workflow the truncation and trimming length for the reverse reads can / has to be given.\n\n\n## Processing\n\n- Denoising with `qiime2 dada2 denoise-single`/`paired`\n- For each of the three outputs (see below) another tool is started to prepare a corresponding qzv file\n - representative sequences `qiime2 feature-table tabulate-seqs `\n - denoising statistics `qiime2 metadata tabulate`\n - summary of the feature table\n\n## Outputs\n\n - representative sequences \n - denoising statistics \n - summary of the feature table (how many sequences are lost in the corresponding steps)\n" }, { "name": "QIIME2-IIb denoising and feature table creation for paired ended data", @@ -553,11 +20948,450 @@ "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", "address": "Permoserstra\u00dfe 15, 04318 Leipzig" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Use DADA2 for sequence quality control. DADA2 is a pipeline for detecting and correcting (where possible) Illumina amplicon sequence data. As implemented in the q2-dada2 plugin, this quality control process will additionally filter any phiX reads (commonly present in marker gene Illumina sequence data) that are identified in the sequencing data, and will filter chimeric sequences.", + "comments": [], + "creator": [ + { + "class": "Person", + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ" + } + ], + "format-version": "0.1", + "release": "0.1", + "license": "MIT", + "name": "QIIME2 IIb: Denoising (sequence quality control) and feature table creation (paired-end)", + "steps": { + "0": { + "annotation": "Tab separated metadata file", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Tab separated metadata file", + "name": "Metadata" + } + ], + "label": "Metadata", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 1.6647546421401653, + "top": 139.9560324460615 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"tabular\"], \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "8dde0c69-40f1-415a-a866-5d1115e80cdf", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Demultiplexed sequences in qza format", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "Demultiplexed sequences in qza format", + "name": "Demultiplexed sequences" + } + ], + "label": "Demultiplexed sequences", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 2.4506271621231845, + "top": 238.07957958589887 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"qza\"], \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "e250ddc1-f567-40ca-9f2b-e07bbf84cdec", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "Length to which the forward read sequence should be truncated. Will remove bases from the 3' end.", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "Length to which the forward read sequence should be truncated. Will remove bases from the 3' end.", + "name": "Truncation length (forward)" + } + ], + "label": "Truncation length (forward)", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 1.5784534434758744, + "top": 353.55220274941445 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "02f3a9bf-0e92-4682-b6b3-ab6b5a332937", + "when": null, + "workflow_outputs": [] + }, + "3": { + "annotation": "Length to which the reverse read sequence should be truncated. Will remove bases from the 3' end.", + "content_id": null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "Length to which the reverse read sequence should be truncated. Will remove bases from the 3' end.", + "name": "Truncation length (reverse)" + } + ], + "label": "Truncation length (reverse)", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0.12398288926847933, + "top": 478.1294436628793 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "2af02538-19c9-4ffc-924e-5108987064a1", + "when": null, + "workflow_outputs": [] + }, + "4": { + "annotation": "Number of bases at the 5' end of the forward read that should be removed. Default: 0.\n\n\nMention the length up to which you want to trim your sequences from the left.\nIf not needed, put 0.", + "content_id": null, + "errors": null, + "id": 4, + "input_connections": {}, + "inputs": [ + { + "description": "Number of bases at the 5' end of the forward read that should be removed. Default: 0.\n\n\nMention the length up to which you want to trim your sequences from the left.\nIf not needed, put 0.", + "name": "Trimming length (forward)" + } + ], + "label": "Trimming length (forward)", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0, + "top": 592.1359047583886 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": true}", + "tool_version": null, + "type": "parameter_input", + "uuid": "cf76e446-d3c1-4682-820c-f6a2f76343d1", + "when": null, + "workflow_outputs": [] + }, + "5": { + "annotation": "Number of bases at the 5' end of the reverse read that should be removed. Default: 0.\n", + "content_id": null, + "errors": null, + "id": 5, + "input_connections": {}, + "inputs": [ + { + "description": "Number of bases at the 5' end of the reverse read that should be removed. Default: 0.\n", + "name": "Trimming length (reverse)" + } + ], + "label": "Trimming length (reverse)", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0.14257701997123728, + "top": 708.0834213595151 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": true}", + "tool_version": null, + "type": "parameter_input", + "uuid": "ccc4f7a3-5e34-4933-ab8b-167e8c944aa7", + "when": null, + "workflow_outputs": [] + }, + "6": { + "annotation": "qiime2 dada2 denoise-paired\nDenoise and dereplicate paired-end sequences\nSmall insight: if the denoising percentage is lower or poorer, reduce 'trunc_q: Int' from 2 to 1.", + "content_id": "toolshed.g2.bx.psu.edu/repos/q2d2/qiime2__dada2__denoise_paired/qiime2__dada2__denoise_paired/2023.5.0+q2galaxy.2023.5.0.2", + "errors": null, + "id": 6, + "input_connections": { + "__q2galaxy__GUI__section__extra_opts__|trim_left_f": { + "id": 4, + "output_name": "output" + }, + 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+ "newname": "dada2_stats_visualisation" + }, + "action_type": "RenameDatasetAction", + "output_name": "visualization" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/q2d2/qiime2__metadata__tabulate/qiime2__metadata__tabulate/2023.5.0+q2galaxy.2023.5.0.2", + "tool_shed_repository": { + "changeset_revision": "d6e1b976c373", + "name": "qiime2__metadata__tabulate", + "owner": "q2d2", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__q2galaxy__GUI__section__extra_opts__\": {\"page_size\": \"100\"}, \"input\": [{\"__index__\": 0, \"__q2galaxy__GUI__conditional__input__\": {\"type\": \"qza\", \"__current_case__\": 1, \"source\": {\"__class__\": \"ConnectedValue\"}}}], \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2023.5.0+q2galaxy.2023.5.0.2", + "type": "tool", + "uuid": "082c2df8-422c-4661-b39d-181ef7ff3072", + "when": null, + "workflow_outputs": [ + { + "label": "DADA2 statistics visualisation", + "output_name": "visualization", + "uuid": 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} + ] + } + }, + "tags": [], + "uuid": "8b8c4f4c-7cc0-422d-9a6f-47357faa0082", + "version": 1 + }, + "readme": "# QIIME2 workflows\n\n## Available workflows\n\nDenoising (using `qiime2`'s `dada2` integration for paired / single end data.\n\n## Inputs\n\n- Demultiplexed sequences as a qiime2 aertifact file (`qza`) containing the sequence information.\n- Metadata table (`tabular`)\n- Truncation length\n- Trimming length (optional)\n\nFor the paired end workflow the truncation and trimming length for the reverse reads can / has to be given.\n\n\n## Processing\n\n- Denoising with `qiime2 dada2 denoise-single`/`paired`\n- For each of the three outputs (see below) another tool is started to prepare a corresponding qzv file\n - representative sequences `qiime2 feature-table tabulate-seqs `\n - denoising statistics `qiime2 metadata tabulate`\n - summary of the feature table\n\n## Outputs\n\n - representative sequences \n - denoising statistics \n - summary of the feature table (how many sequences are lost in the corresponding steps)\n" } ], - "path": "./workflows/amplicon/qiime2/qiime2-II-denoising", - "readme": "# QIIME2 workflows\n\n## Available workflows\n\nDenoising (using `qiime2`'s `dada2` integration for paired / single end data.\n\n## Inputs\n\n- Demultiplexed sequences as a qiime2 aertifact file (`qza`) containing the sequence information.\n- Metadata table (`tabular`)\n- Truncation length\n- Trimming length (optional)\n\nFor the paired end workflow the truncation and trimming length for the reverse reads can / has to be given.\n\n\n## Processing\n\n- Denoising with `qiime2 dada2 denoise-single`/`paired`\n- For each of the three outputs (see below) another tool is started to prepare a corresponding qzv file\n - representative sequences `qiime2 feature-table tabulate-seqs `\n - denoising statistics `qiime2 metadata tabulate`\n - summary of the feature table\n\n## Outputs\n\n - representative sequences \n - denoising statistics \n - summary of the feature table (how many sequences are lost in the corresponding steps)\n" + "path": "./workflows/amplicon/qiime2/qiime2-II-denoising" }, { "version": 1.2, @@ -575,7 +21409,645 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run baredSC in 1 dimension in logNorm for 1 to N gaussians and combine models.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.4", + "name": "baredSC_1d_logNorm", + "steps": { + "0": { + "annotation": "The dataset must have a first row with row names. 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+ "uuid": "1ea0b92d-d863-435a-96ac-1e547fdbc994", + "version": 7 + }, + "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n", + "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0`\n\n## [0.3] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0`\n\n## [0.2] 2023-12-01\n\n### Add 'compute p-value' parameter in 2d\n\n### Semi-automatic update\n- all baredsc tools were updated from `1.1.2+galaxy0` to `1.1.2+galaxy1`\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1] 2023-10-03\n\nFirst release.\n" }, { "name": "baredSC-2d-logNorm", @@ -590,11 +22062,779 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run baredSC in 2 dimensions in logNorm for 1 to N gaussians and combine models.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.4", + "name": "baredSC_2d_logNorm", + "steps": { + "0": { + "annotation": "The dataset must have a first row with row names. 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{\"__class__\": \"ConnectedValue\"}, \"xmin\": \"0.0\", \"xmax\": {\"__class__\": \"ConnectedValue\"}, \"nx\": \"25\", \"minScalex\": \"0.1\", \"ymin\": \"0.0\", \"ymax\": {\"__class__\": \"ConnectedValue\"}, \"ny\": \"25\", \"minScaley\": \"0.1\", \"scale\": {\"type\": \"Seurat\", \"__current_case__\": 0, \"targetSum\": \"10000.0\"}, \"seed\": \"1\"}, \"advanced\": {\"getPVal\": {\"__class__\": \"ConnectedValue\"}, \"osampx\": \"10\", \"osampxpdf\": \"4\", \"osampy\": \"10\", \"osampypdf\": \"4\", \"coviscale\": \"1.0\", \"nis\": \"1000\", \"scalePrior\": \"0.3\"}, \"filter\": {\"nb\": \"0\", \"__current_case__\": 0}, \"geneXColName\": {\"__class__\": \"ConnectedValue\"}, \"geneYColName\": {\"__class__\": \"ConnectedValue\"}, \"input_counts\": {\"filetype\": \"tabular\", \"__current_case__\": 0, \"input\": {\"__class__\": \"ConnectedValue\"}}, \"plots\": {\"image_file_format\": \"png\", \"title\": \"\", \"removeFirstSamples\": \"-1\", \"nsampInPlot\": \"100000\", \"prettyBinsx\": \"-1\", \"prettyBinsy\": \"-1\", \"log1pColorScale\": false, \"splity\": \"\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.1.3+galaxy0", + "type": "tool", + "uuid": "e4eebae4-0952-4d21-8bb6-d16d1b5397b3", + "when": null, + "workflow_outputs": [ + { + "label": "combined_pdf2d", + "output_name": "pdf2d", + "uuid": "0fff7566-a7d9-4dac-b77b-416e6a2f56ef" + }, + { + "label": "combined_pdf2d_flat", + "output_name": "pdf2d_flat", + "uuid": "79eb786a-7465-4f24-aafa-d2520028527d" + }, + { + "label": "combined_plot", + "output_name": "plot", + "uuid": "db367996-7c6c-4cd3-8692-c0483fbc671c" + }, + { + "label": "combined_other_outputs", + "output_name": "other_outputs", + "uuid": "eca7f33c-3a1d-41d7-a56a-925167baf364" + } + ] + } + }, + "tags": [], + "uuid": "1936816b-958a-4140-b839-58be4cdae1a5", + "version": 1 + }, + "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n", + "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0`\n\n## [0.3] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0`\n\n## [0.2] 2023-12-01\n\n### Add 'compute p-value' parameter in 2d\n\n### Semi-automatic update\n- all baredsc tools were updated from `1.1.2+galaxy0` to `1.1.2+galaxy1`\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1] 2023-10-03\n\nFirst release.\n" } ], - "path": "./workflows/scRNAseq/baredsc", - "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n" + "path": "./workflows/scRNAseq/baredsc" }, { "version": 1.2, @@ -628,7 +22868,2180 @@ "name": "Wendi Bacon", "orcid": "0000-0002-8170-8806" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow processes the CMO fastqs with CITE-seq-Count and include the translation step required for cellPlex processing. In parallel it processes the Gene Expresion fastqs with STARsolo, filter cells with DropletUtils and reformat all outputs to be easily used by the function 'Read10X' from Seurat.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-4181-2676", + "name": "Mehmet Tekman" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-2799-424X", + "name": "Hans-Rudolf Hotz" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-6833-9049", + "name": "Daniel Blankenberg" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-8170-8806", + "name": "Wendi Bacon" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.4", + "name": "scRNA-seq_preprocessing_10X_cellPlex", + "steps": { + "0": { + "annotation": "reads containing genes", + "content_id": null, + "errors": null, + 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You can use 24000.", + "content_id": null, + "errors": null, + "id": 7, + "input_connections": {}, + "inputs": [ + { + "description": "Used by CITE-seq-Count, does not really seem to impact result. 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CITE-seq output", + "name": "Pick parameter value", + "outputs": [ + { + "name": "data_param", + "type": "input" + } + ], + "position": { + "left": 1450.6999816894531, + "top": 841.5938543505861 + }, + "post_job_actions": { + "RenameDatasetActiondata_param": { + "action_arguments": { + "newname": "Seurat input for CMO (UMI)" + }, + "action_type": "RenameDatasetAction", + "output_name": "data_param" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.2.0", + "tool_shed_repository": { + "changeset_revision": "b19e21af9c52", + "name": "pick_value", + "owner": "iuc", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"style_cond\": {\"pick_style\": \"first\", \"__current_case__\": 0, \"type_cond\": {\"param_type\": \"data\", \"__current_case__\": 4, \"pick_from\": [{\"__index__\": 0, \"value\": {\"__class__\": \"ConnectedValue\"}}]}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.2.0", + "type": "tool", + "uuid": 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Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n", + "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n\n## [0.3] 2024-02-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.2] 2024-02-05\n\n### Tool updates\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy3` was updated to 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\"__rerun_remap_job_id__\": null}", + "tool_version": "1.1.0", + "type": "tool", + "uuid": "95eb63d6-f1a2-4f0d-b426-fc46a5133471", + "when": null, + "workflow_outputs": [ + { + "label": "STARsolo cell ranger-like output", + "output_name": "output", + "uuid": "3a6385df-d937-4c8a-9430-9bafe0cb2f57" + } + ] + } + }, + "tags": "", + "uuid": "415c1b14-3b63-4d27-8c34-42e452cb49f1" + }, + "tool_id": null, + "type": "subworkflow", + "uuid": "697a68da-9cb9-469b-8102-30c3a3ee589f", + "when": null, + "workflow_outputs": [ + { + "label": "Seurat input for gene expression (filtered)", + "output_name": "STARsolo cell ranger-like output", + "uuid": "6cb072df-9e26-456b-ab4f-bc95345b02b4" + } + ] + } + }, + "tags": [ + "#single-cell" + ], + "uuid": "19feac09-8db7-4e3f-9774-8b815918cfa7", + "version": 2 + }, + "readme": "# Single-cell RNA-seq fastq to matrix for 10X data\n\nThese workflows are inspired by the [training material](https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-preprocessing-tenx/tutorial.html). Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n", + "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n\n## [0.3] 2024-02-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.2] 2024-02-05\n\n### Tool updates\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n- `pick_value` was replaced by `toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.2.0`\n\n\n\n## [0.1] 2023-12-21\n\nFirst release.\n" } ], - "path": "./workflows/scRNAseq/fastq-to-matrix-10x", - "readme": "# Single-cell RNA-seq fastq to matrix for 10X data\n\nThese workflows are inspired by the [training material](https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-preprocessing-tenx/tutorial.html). Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n" + "path": "./workflows/scRNAseq/fastq-to-matrix-10x" }, { "version": 1.2, @@ -681,7 +26120,371 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run velocyto to get loom with counts of spliced and unspliced. 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There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n", + "changelog": "# Changelog\n\n## [0.2] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy2`\n## [0.1] 2024-01-26\n\nFirst release.\n" }, { "name": "Velocyto-on10X-filtered-barcodes", @@ -696,11 +26499,190 @@ "name": "Lucille Delisle", "orcid": "0000-0002-1964-4960" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run velocyto to get loom with counts of spliced and unspliced", + "comments": [], + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.2", + "name": "Velocyto-on10X-filtered-barcodes", + "steps": { + "0": { + "annotation": "This can be output of CellRanger or STARsolo", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "This can be output of CellRanger or STARsolo", + "name": "BAM files with CB and UB" + } + ], + "label": "BAM files with CB and UB", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 0 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"bam\"], \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "043d198b-3af0-477d-be11-5d1373280379", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "This can be output of STARsolo or DropletUtils (too many barcodes will make memory errors)", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "This can be output of STARsolo or DropletUtils (too many barcodes will make memory errors)", + "name": "filtered barcodes" + } + ], + "label": "filtered barcodes", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 55.999999999999986, + "top": 108.33333333333333 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"format\": [\"tsv\"], \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "03b0d22c-3b46-4460-8c18-b524bc09d655", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "gtf file", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "gtf file", + "name": "gtf file" + } + ], + "label": "gtf file", + "name": "Input dataset", + "outputs": [], + "position": { + 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There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n", + "changelog": "# Changelog\n\n## [0.2] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy2`\n## [0.1] 2024-01-26\n\nFirst release.\n" } ], - "path": "./workflows/scRNAseq/velocyto", - "readme": "# Velocyto on 10X data\n\nThese workflows simply run velocyto. There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n" + "path": "./workflows/scRNAseq/velocyto" }, { "version": 1.2, @@ -719,11 +26701,2279 @@ "name": "Wolfgang Maier", "orcid": "0000-0002-9464-6640" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "A workflow for the analysis of pox virus genomes sequenced as half-genomes (for ITR resolution) in a tiled-amplicon approach", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0001-6897-1215", + "name": "Viktoria Isabel Schwarz" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-9464-6640", + "name": "Wolfgang Maier" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.1", + "name": "Pox Virus Illumina Amplicon Workflow from half-genomes", + "steps": { + "0": { + "annotation": "The viral reference sequence to map sequenced reads against", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "The viral reference sequence to map sequenced reads against", + "name": "Reference FASTA" + } + ], + "label": "Reference FASTA", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 244.316650390625, + "top": 642.8833312988281 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\"}", + "tool_version": null, + "type": "data_input", + "uuid": "f17c7022-fc94-42b5-ae90-7b3ec3d70ffb", + "workflow_outputs": [] + }, + "1": { + "annotation": "The workflow expects a primer scheme split into two separate sequencing pools. 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merging of the results.", + "changelog": "# Changelog\n\n## [0.1]\n\nInitial version of Pox Virus Illumina Amplicon workflow (iVar based) for half-genomes sequencing data" } ], - "path": "./workflows/virology/pox-virus-amplicon", - "readme": "# Pox Virus Illumina Amplicon Workflow for half-genomes sequencing data\n\nThis workflow generates consensus sequences from Illumina PE-sequenced ARTIC data of pox virus samples.\n\nIt requires that all samples have been sequenced in two halves in two separate sequencing runs, and utilizes this property to resolve the inverted terminal repeat (ITR) sequences of pox virus genomes.\n\nThe workflow uses BWA-MEM for mapping the reads from each half-genome sequencing run to a correspondingly masked version of the reference genome, merges the resulting two read mappings, and uses iVar for primer trimming and consensus sequence generation.\n\nConceptually, this workflow builds on 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"b5516866-8b4f-41b8-a19a-12e1362d344c" + } + ] + } + }, + "tags": [ + "VGP_curated" + ], + "uuid": "4818fdda-7a91-481a-a62f-ccab45a3c0f1", + "version": 2 + }, + "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Primary Assembly (hap1) [fasta] (Generated by the contigging workflow)\n3. Alternate Assembly (hap2) [fasta] (Generated by the contigging workflow)\n4. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n5. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n6. Estimated Genome Size [txt]\n7. Name of first haplotype\n8. Name of second haplotype\n9. Lineage of you species for Busco Orthologs\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies\n", + "changelog": "# Changelog\n\n\n## [0.3.8] 2024-04-23\n\n### Added\n\n- Add Busco Gff output\n\n## [0.3.7] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n## [0.3.6] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0`\n\n## [0.3.5] 2024-03-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n\n## [0.3.4] 2024-02-15\n\n- Remove tag filtering\n- Add merqury histogram outputs\n\n## [0.3.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.3.2] - 2023-11-15\n\n### Added\n\n- more descriptive lables for inputs\n\n## [0.3.1] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.3] - 2023-11-08\n\n### Added\n\n- Made BUSCO lineage selectable from workflow launch interface\n\n### Changed\n\n- Change BUSCO lineage input parameter name from `Provide lineage for BUSCO (e.g., Vertebrata)` to `Lineage`\n\n\n## [0.2.0] - 2023-11-07\n\n### Added\n\n- Tag filtering for inputs\n- Changed parameters of gfastats for postprocessing of contigs generated with purge_dups. Specfically:\n - \"Terminal overlap selection\" is set to \"Yes\"\n - \"Generated the initial set of paths\" is set to \"No\"\n\n\n## [0.1.1] - 2023-11-01\n\n### Added\n\n- More explicit tags for readability\n\n\n## [0.1] - 2023-10-26\n\n### Added\n\n- Workflow for purging duplication in contigs\n" } ], - "path": "./workflows/VGP-assembly-v2/Purge-duplicate-contigs-VGP6", - "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Primary Assembly (hap1) [fasta] (Generated by the contigging workflow)\n3. Alternate Assembly (hap2) [fasta] (Generated by the contigging workflow)\n4. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n5. 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Bionano data [cmap]\n2. Estimated genome size [txt]\n3. Phased assembly generated by Hifiasm [gfa1]\n\n## Outputs\n\n1. Scaffolds\n2. Non-scaffolded contigs\n3. QC: Assembly statistics\n4. QC: Nx plot\n5. QC: Size plot", + "changelog": "# Changelog\n\n## [0.1.3] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n\n## [0.1.2] 2024-03-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.1.1] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/bionano_scaffold/bionano_scaffold/3.7.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/bionano_scaffold/bionano_scaffold/3.7.0+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1] - 2023-11-01\n\nAddition of the workflow to the iwc repository.\n" } ], - "path": "./workflows/VGP-assembly-v2/Scaffolding-Bionano-VGP7", - "readme": "# Scaffolding with Bionano\n\nScaffolding using Bionano optical map data\n\n## Inputs\n\n1. 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Specifically, it provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality.\n\n### Inputs\n\n- A collection of Hifi long reads in FASTQ format\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl Database of kmer counts\n- GenomeScope\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n\n ![image](https://github.com/galaxyproject/iwc/assets/4291636/565238fc-f8a9-46ac-8b31-6276410fa436)\n", + "changelog": "# Changelog\n\n## [0.1.5] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.4] 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n## [0.1.3] 2023-11-09\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2`\n\n## [0.1.2] - 2023-11-07\n### Changed\n- Added tag filtering for inputs\n\n## [0.1.1] - 2023-10-30\n### Changed\n- Names of the workflow and viles for consistency with other VGP workflows\n- Labels and tags for user readability\n \n## [0.1] - 2021-08-26\n### Added\n- First version of the workflow. \n" } ], - "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-VGP1", - "readme": "# VGP Workflow #1\n\nThis workflow produces a Meryl database and Genomescope outputs that will be used to determine parameters for following workflows, and assess the quality of genome assemblies. 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"Assembly statistics", + "output_name": "output", + "uuid": "87796a13-fdcb-4448-9038-81ac8598a96e" + } + ] + } + }, + "tags": [ + "VGP_curated" + ], + "uuid": "f069b3f3-7cf9-40f9-b452-ee9c21466623", + "version": 1 + }, + "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups in a single haplotype(could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Assembly to purge (e.g. hap1) [fasta] (Generated by the contigging workflow)\n3. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n4. Estimated Genome Size [txt]\n5. Assembly to leave alone (used for merqury statistics) (e.g. hap2) [fasta] (Generated by the contigging workflow)\n6. Name of un-altered assembly\n7. Name of purged assembly\n\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies", + "changelog": "# Changelog\n\n## [0.6] 2024-04-23\n\n### Changed\n\n- Add Merqury histogram output\n- Add Busco gff output\n- Unhide Merqury QV output\n\n## [0.5] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n\n## [0.4] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0`\n\n## [0.2] 2024-02-19\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.5.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1] - 2024-02-07\n\n### Added\n\n- Workflow for purging duplication in contigs in single haplotype\n" } ], - "path": "./workflows/VGP-assembly-v2/Purge-duplicates-one-haplotype-VGP6b", - "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups in a single haplotype(could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Assembly to purge (e.g. hap1) [fasta] (Generated by the contigging workflow)\n3. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n4. Estimated Genome Size [txt]\n5. Assembly to leave alone (used for merqury statistics) (e.g. hap2) [fasta] (Generated by the contigging workflow)\n6. Name of un-altered assembly\n7. Name of purged assembly\n\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. 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\"ConnectedValue\"}, \"which\": {\"which_dataset\": \"first\", \"__current_case__\": 0}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.0.1", + "type": "tool", + "uuid": "a13de545-44b8-444c-b457-c026b6051203", + "when": null, + "workflow_outputs": [ + { + "label": "Pretext Map After HiC scaffolding", + "output_name": "output", + "uuid": "d7fed6f0-7fb1-4a9b-a112-bce5bc04e873" + } + ] + } + }, + "tags": [ + "VGP_curated" + ], + "uuid": "a45c5bd9-6b56-40ff-a9ea-ba420a683f42", + "version": 3 + }, + "readme": "# Scaffolding with HiC data\n\nThis workflow perfoms scaffolding using HiC data with YAHS. It is designed to be run as part of one the VGP analysis trajectories. \nExample of trajectory : \n- VGP1 : Kmer profiling \n- VGP4 : Genome assembly with HiC phasing\n- VGP6 : Purge duplicated haplotigs\n- VGP8 : Scaffolding with HiC\n\n## Inputs\n\n1. Scaffolded assembly [fasta]\n2. Concatenated HiC forward reads [fastq]\n3. Concatenated HiC reverse reads [fastq]\n4. Restriction enzyme sequence [txt]\n5. Estimated genome size [txt]\n\n### Outputs\n\n1. Scaffolds in [fasta] and [gfa] format\n2. QC: Assembly statistics\n3. QC: Nx plot\n4. QC: Size plot\n5. QC: BUSCO report\n6. QC: Pretext Maps before and after scaffolding", + "changelog": "# Changelog\n\n## [0.2.3] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy1`\n\n## [0.2.2] 2024-02-05\n\n### Manual update\n\n- remove tag filtering\n- set \"Show grid\" of Pretext Snapshot to \"yes\"\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy0`\n\n\n## [0.2.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.2] - 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bwa_mem2/bwa_mem2/2.2.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bwa_mem2/bwa_mem2/2.2.1+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bellerophon/bellerophon/1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bellerophon/bellerophon/1.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.1] - 2023-10-26\n\nAdded tags for better visibility of outputs in the history, and exposure of the BUSCO lineage parameter\n\n## [0.1] - 2023-09-27\n\nCreation of the workflow and tests\n\n" } ], - "path": "./workflows/VGP-assembly-v2/Scaffolding-HiC-VGP8", - "readme": "# Scaffolding with HiC data\n\nThis workflow perfoms scaffolding using HiC data with YAHS. 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QC: Pretext Maps before and after scaffolding" + "path": "./workflows/VGP-assembly-v2/Scaffolding-HiC-VGP8" }, { "version": 1.2, @@ -915,11 +40081,3465 @@ "name": "Delphine Lariviere", "orcid": "0000-0001-6421-3484" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "", + "comments": [], + "creator": [ + { + "class": "Organization", + "name": "Galaxy" + }, + { + "class": "Organization", + "name": "VGP", + "url": "https://vertebrategenomeproject.org" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0001-6421-3484", + "name": "Delphine Lariviere" + } + ], + "format-version": "0.1", + "license": "CC-BY-4.0", + "release": "0.1.10", + "name": "Assembly-Hifi-HiC-phasing-VGP4", + "steps": { + "0": { + "annotation": "A simple list containing PacBio data in either fasta or fastq formats.", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "A simple list containing PacBio data in either 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Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n## Outputs\n\n1. Haplotype 1 assembly ([fasta] and [gfa])\n2. Haplotype 2 assembly ([fasta] and [gfa])\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies", + "changelog": "# Changelog\n\n\n\n## [0.1.10] 2024-04-23\n\n### Changed\n\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.9] 2024-04-19\n\n### Manual Updates\n\n- Add the option to provide Homozygous Read coverage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n\n## [0.1.8] 2024-03-25\n\n### Manual update\n\n- Remove tag filtering\n- Add merqury histogram output\n- Add output for cutadapt\n- Output Gff files in Busco \n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n## [0.1.7] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.5] 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.5.0+galaxy0`\n\n## [0.1.4] 2023-11-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.3] - 2023-11-08\n\n- Added tags `hifiasm_Assembly_Haplotype_1` and `hifiasm_Assembly_Haplotype_2` to fasta outputs of hifiasm, so they can be easily identified for feeding to purge_dups workflow\n- Made BUSCO lineages selectable from workflow launch interface\n\n## [0.1.2] - 2023-11-07\n\n- Added input filtering based on tags. 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It provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality. It uses reads from two parental genomes to partition long reads from the offspring into haplotype-specific *k*-mer databases.\n\n### Inputs\n\n- Collection of Hifi long reads [fastq] (Collection)\n- Paternal short-read Illumina sequencing reads [fastq] (Collection)\n- Maternal short-read Illumina sequencing reads [fastq] (Collection)\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl databases of k-mer counts\n - Child\n - Paternal haplotype\n - Maternal haplotype\n- GenomeScope metrics for child and the two parental genomes (three GenomeScope profiles in total)\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n \n ![image](https://github.com/galaxyproject/iwc/assets/4291636/35282f8e-d021-44f6-8e03-7b58b32d6d00)\n", + "changelog": "# Changelog\n\n## [0.1.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.2] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2`\n\n## [0.1] - 2023-10-30\n\n### Added\n- Clearer labels\n\n### Removed\n- Interlacing step that was unneccessary\n- Requirement for paired list inputs for the Illumina parental reads. A dataset collection list is sufficient now.\n- Unnecessary workflow intputs\n\n## [0.1] - 2021-08-26\n### Added\n- First version of the workflow. \n" } ], - "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-trio-VGP2", - "readme": "# VGP Workflow #1\n\nThis workflow collects the metrics on the properties of the genome under consideration by analyzing the *k*-mer frequencies. It provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality. It uses reads from two parental genomes to partition long reads from the offspring into haplotype-specific *k*-mer databases.\n\n### Inputs\n\n- Collection of Hifi long reads [fastq] (Collection)\n- Paternal short-read Illumina sequencing reads [fastq] (Collection)\n- Maternal short-read Illumina sequencing reads [fastq] (Collection)\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl databases of k-mer counts\n - Child\n - Paternal haplotype\n - Maternal haplotype\n- GenomeScope metrics for child and the two parental genomes (three GenomeScope profiles in total)\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n \n ![image](https://github.com/galaxyproject/iwc/assets/4291636/35282f8e-d021-44f6-8e03-7b58b32d6d00)\n" + "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-trio-VGP2" }, { "version": 1.2, @@ -965,11 +44605,3442 @@ "name": "VGP", "url": "https://vertebrategenomeproject.org" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "", + "comments": [], + "creator": [ + { + "class": "Organization", + "name": "Galaxy" + }, + { + "class": "Organization", + "name": "VGP", + "url": "https://vertebrategenomeproject.org" + } + ], + "format-version": "0.1", + "license": "CC-BY-4.0", + "release": "0.1.4", + "name": "Assembly-Hifi-Trio-phasing-VGP5", + "steps": { + "0": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Pacbio Reads Collection : child" + } + ], + "label": "Pacbio Reads Collection : child", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 5.828125, + "top": 188.5546875 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "54f368c3-47cb-4fcf-8271-628becc1051e", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Paternal Illumina reads (hap1)" + } + ], + "label": "Paternal Illumina reads (hap1)", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 9.9375, + "top": 297.7890625 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "4e8847f2-4257-4ccc-a375-edfcbd7451f6", + "when": null, + "workflow_outputs": [] + }, + "2": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Maternal Illumina reads (hap2)" + } + ], + "label": "Maternal Illumina reads (hap2)", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0, + "top": 428.5859375 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "76917fe2-487e-4780-84e7-917615a2e444", + "when": null, + "workflow_outputs": [] + }, + "3": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Meryl Database : Child" + } + ], + "label": "Meryl Database : Child", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 5.828125, + "top": 558.4765625 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\"}", + "tool_version": null, + "type": "data_input", + "uuid": "a67ad2b7-a50f-4e8f-8bb1-a433a7662c45", + "when": null, + "workflow_outputs": [] + }, + "4": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 4, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Hapmer Database : Paternal" + } + ], + "label": "Hapmer Database : Paternal", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 0.625, + "top": 665.9921875 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\"}", + "tool_version": null, + "type": "data_input", + "uuid": "1575eb2b-6dd8-4d11-af33-9e1f8f023c6a", + "when": null, + "workflow_outputs": [] + }, + "5": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 5, + "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Hapmer Database : Maternal" + } + ], + "label": "Hapmer Database : Maternal", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 1.921875, + "top": 774.3828125 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": \"\"}", + "tool_version": null, + "type": "data_input", + "uuid": "3fa39765-f349-4465-a2d1-947fdbad21ba", + "when": null, + "workflow_outputs": [] + }, + "6": { + "annotation": "Defaults to 37 if not specified. 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Hifi long reads [fastq]\n2. Concatenated Illumina reads : Paternal [fastq]\n3. Concatenated Illumina reads : Maternal [fastq]\n4. K-mer database [meryldb]\n5. Paternal hapmer database [meryldb]\n6. Maternal hapmer database [meryldb]\n7. Genome profile summary generated by Genomescope [txt]\n8. Genome model parameters generated by Genomescope [tabular]\n9. Homozygous read coverage (Estimated from the Genomescope model if not provided)\n10. Lineage of the species being assembled\n11. Bloom Filter\n12. Name of first haplotype\n13. Name of second haplotype\n\n## Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. Merqury report for both assemblies\n5. Assembly statistics for both assemblies\n6. Nx Plot for both assemblies\n7. Size plot for both assemblies\n\n\n", + "changelog": "# Changelog\n\n## [0.1.4] 2024-04-22\n\n### Added\n\n- Add Homozygous Read coverage parameter and calculation\n- Expose Lineage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.3] 2024-03-25\n\n### Manual update\n\n- Add gff output to Busco\n- Add histogram output to Merqury\n- Label subworkflows\n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.1] 2023-11-20\n\n- Fix author in dockstore\n\n\n## [0.1] - 2023-09-27\n\nCreation of workflow for Trio assembly. \n\n" } ], - "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-Trio-phasing-VGP5", - "readme": "# Assembly with Hifi reads and Trio Data\n\nGenerate phased assembly based on PacBio Hifi Reads using parental Illumina data for phasing\n\n## Inputs\n\n1. Hifi long reads [fastq]\n2. Concatenated Illumina reads : Paternal [fastq]\n3. Concatenated Illumina reads : Maternal [fastq]\n4. K-mer database [meryldb]\n5. Paternal hapmer database [meryldb]\n6. Maternal hapmer database [meryldb]\n7. Genome profile summary generated by Genomescope [txt]\n8. Genome model parameters generated by Genomescope [tabular]\n9. Homozygous read coverage (Estimated from the Genomescope model if not provided)\n10. Lineage of the species being assembled\n11. Bloom Filter\n12. Name of first haplotype\n13. Name of second haplotype\n\n## Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. Merqury report for both assemblies\n5. Assembly statistics for both assemblies\n6. Nx Plot for both assemblies\n7. 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Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n\n### Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblie\n", + "changelog": "# Changelog\n\n\n## [0.1.5] 2024-04-23\n\n### Changed\n\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.4] 2024-04-19\n\n### Manual Updates\n\n- Add Homozygous Read coverage parameter and calculation\n- Expose Lineage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n## [0.1.3] 2024-03-25\n\n### Manual Updates\n- Add Gff outputs to Busco\n- Add histogram outputs to Merqury\n- Add labels to subworkflows\n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n\n## [0.1.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1] - 2023-09-26\n\nAddition of the workflow to the iwc repository.\n" } ], - "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-only-VGP3", - "readme": "## Contiging Solo w/HiC:\n\nGenerate phased assembly based on PacBio Hifi Reads using HiC data from the same individual for phasing.\n\n\n### Inputs\n\n\n1. Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n\n### Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblie\n" + "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-only-VGP3" }, { "version": 1.2, @@ -1013,11 +51225,355 @@ "orcid": "0000-0003-1323-3762", "url": "https://github.com/kostrykin/" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow performs segmentation and counting of cell nuclei using fluorescence microscopy images. The segmentation step is performed using Otsu thresholding (Otsu, 1979). 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Must be the single image channel, which contains the cell nuclei.", + "name": "input_image" + } + ], + "label": "input_image", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 0, + "top": 123.6936084329719 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "5dd476ec-c0d7-45af-a522-ba6b2ce43880", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/imgteam/2d_simple_filter/ip_filter_standard/0.0.3-3", + "errors": null, + "id": 1, + "input_connections": { + "input": { + "id": 0, + "output_name": "output" + } + }, + "inputs": [], + "label": null, + "name": "Filter 2D image", + "outputs": [ + { + "name": "output", + "type": "tiff" + } + ], + "position": { + "left": 320.6808544907898, + "top": 244.80388558482915 + }, + "post_job_actions": {}, + "tool_id": 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1086.8749834881503, + "top": 370.25000974083935 + }, + "post_job_actions": {}, + "tool_id": "toolshed.g2.bx.psu.edu/repos/imgteam/count_objects/ip_count_objects/0.0.5-2", + "tool_shed_repository": { + "changeset_revision": "b58447a2eed2", + "name": "count_objects", + "owner": "imgteam", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__input_ext\": \"tiff\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.0.5-2", + "type": "tool", + "uuid": "9bda49f1-24ec-42f8-bceb-ab54c56b6624", + "when": null, + "workflow_outputs": [ + { + "label": "objects_count", + "output_name": "output", + "uuid": "fd812c33-336d-4958-9877-b5b5b337f1d1" + } + ] + } + }, + "tags": [], + "uuid": "8c2d765b-2764-4b66-8542-adc2109c24f2", + "version": 10 + }, + "readme": "# Segmentation and counting of cell nuclei in fluorescence microscopy images\n\nThis workflow performs segmentation and counting of cell nuclei using fluorescence microscopy images. The segmentation step is performed using Otsu thresholding (Otsu, 1979). The workflow is based on the tutorial: https://training.galaxyproject.org/training-material/topics/imaging/tutorials/imaging-introduction/tutorial.html\n\n![](test-data/overlay_image.png)\n\n## Inputs\n\n**`input_image`:** The fluorescence microscopy images to be segmented. Must be the single image channel, which contains the cell nuclei.\n\n## Outputs\n\n**`overlay_image`:** An overlay of the original image and the outlines of the segmentated objects, each also annotated with a unique number.\n\n**`objects_count`:** Table with a single column `objects` and a single row (the actual number of objects).\n\n**`label_image`:** The segmentation result (label map, which contains a unique label for each segmented object).\n", + "changelog": "# Changelog\n\n## [0.1] - 2024-02-29\n\n- Creation of workflow for segmentation and counting of cell nuclei in fluorescence microscopy images.\n" } ], - "path": "./workflows/imaging/fluorescence-nuclei-segmentation-and-counting", - "readme": "# Segmentation and counting of cell nuclei in fluorescence microscopy images\n\nThis workflow performs segmentation and counting of cell nuclei using fluorescence microscopy images. The segmentation step is performed using Otsu thresholding (Otsu, 1979). The workflow is based on the tutorial: https://training.galaxyproject.org/training-material/topics/imaging/tutorials/imaging-introduction/tutorial.html\n\n![](test-data/overlay_image.png)\n\n## Inputs\n\n**`input_image`:** The fluorescence microscopy images to be segmented. Must be the single image channel, which contains the cell nuclei.\n\n## Outputs\n\n**`overlay_image`:** An overlay of the original image and the outlines of the segmentated objects, each also annotated with a unique number.\n\n**`objects_count`:** Table with a single column `objects` and a single row (the actual number of objects).\n\n**`label_image`:** The segmentation result (label map, which contains a unique label for each segmented object).\n" + "path": "./workflows/imaging/fluorescence-nuclei-segmentation-and-counting" }, { "version": 1.2, @@ -1036,11 +51592,481 @@ "image": "https://raw.githubusercontent.com/workflow4metabolomics/workflow4metabolomics/master/images/logo/logo_w4m-0.1-black-orange.png", "url": "https://workflow4metabolomics.org/" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow is composed with the XCMS tool R package (Smith, C.A. 2006) able to extract and the metaMS R package (Wehrens, R 2014) for the field of untargeted 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2014)](https://bioconductor.org/packages/release/bioc/html/metaMS.html) for the field of untargeted metabolomics. \n\n\ud83c\udf93 For more information see the [Galaxy Training Network tutorial: Mass spectrometry: GC-MS analysis with metaMS package](https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/gcms/tutorial.html)\n\n## Inputs\n### sampleMetadata\nThe sampleMetadata tabular file corresponds to a table containing information about your samples\n\nA sample metadata file contains various information for each of your raw files:\n- Classes which will be used during the preprocessing steps\n- Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order\n- Different experimental conditions which can be used for statistics\n- Any information about samples that you want to keep, in a column format\n\nThe content of your sample metadata file has to be filled by you, since it is not contained in your raw data. Note that you can either:\n- Upload an existing metadata file\n- Use a template to create one (because it can be painful to get the sample list without misspelling or omission)\n - Generate a template with the `xcms get a sampleMetadata file` tool available in Galaxy\n - Fill it using your favorite table editor (Excel, LibreOffice)\n - Upload it within Galaxy\n\n**Formats:** tab-separated values as tsv, tab, txt, ...\n\n### Mass-spectrometry Dataset Collection\nMass-spectrometry data files gathered in a Galaxy Dataser Collection\n\n**Formats:** open format as mzXML, mzMl, mzData and netCDF\n\n## Main steps\n1. MSnbase readMSData: read the mzXML and prepare for xcms\n2. XCMS findChromPeaks: peak picking\n3. metaMS.runGC: definition of pseudo-spectra\n", + "changelog": "# Changelog\n\nAll notable changes to this project will be documented in this file.\n\n## [0.1] - 2023-11-22\n\nFirst release\n" } ], - "path": "./workflows/metabomics/gcms-metams", - "readme": "# Mass spectrometry: GCMS with metaMS \n\nThis workflow uses the XCMS tool R package [(Smith, C.A. 2006)](https://bioconductor.org/packages/release/bioc/html/xcms.html) to extract, filter, align and fill gaps, and uses the CAMERA R package [(Kuhl, C 2012)](https://bioconductor.org/packages/release/bioc/html/CAMERA.html) to annotate isotopes, adducts and fragments.\n\nThis workflow is composed with the XCMS tool R package [(Smith, C.A. 2006)](https://bioconductor.org/packages/release/bioc/html/xcms.html) to extract and the metaMS R package [(Wehrens, R 2014)](https://bioconductor.org/packages/release/bioc/html/metaMS.html) for the field of untargeted metabolomics. \n\n\ud83c\udf93 For more information see the [Galaxy Training Network tutorial: Mass spectrometry: GC-MS analysis with metaMS package](https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/gcms/tutorial.html)\n\n## Inputs\n### sampleMetadata\nThe sampleMetadata tabular file corresponds to a table containing information about your samples\n\nA sample metadata file contains various information for each of your raw files:\n- Classes which will be used during the preprocessing steps\n- Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order\n- Different experimental conditions which can be used for statistics\n- Any information about samples that you want to keep, in a column format\n\nThe content of your sample metadata file has to be filled by you, since it is not contained in your raw data. 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2012)](https://bioconductor.org/packages/release/bioc/html/CAMERA.html) to annotate isotopes, adducts and fragments.\n\n\ud83c\udf93 For more information see the [Galaxy Training Network tutorial: Mass spectrometry: LC-MS preprocessing with XCMS](https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html)\n\n## Inputs\n### sampleMetadata\nThe sampleMetadata tabular file corresponds to a table containing information about your samples\n\nA sample metadata file contains various information for each of your raw files:\n- Classes which will be used during the preprocessing steps\n- Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order\n- Different experimental conditions which can be used for statistics\n- Any information about samples that you want to keep, in a column format\n\nThe content of your sample metadata file has to be filled by you, since it is not contained in your raw data. Note that you can either:\n- Upload an existing metadata file\n- Use a template to create one (because it can be painful to get the sample list without misspelling or omission)\n - Generate a template with the `xcms get a sampleMetadata file` tool available in Galaxy\n - Fill it using your favorite table editor (Excel, LibreOffice)\n - Upload it within Galaxy\n\n**Formats:** tab-separated values as tsv, tab, txt, ...\n\n### Mass-spectrometry Dataset Collection\nMass-spectrometry data files gathered in a Galaxy Dataser Collection\n\n**Formats:** open format as mzXML, mzMl, mzData and netCDF\n\n## Main steps\n1. MSnbase readMSData: read the mzXML and prepare for xcms\n2. XCMS findChromPeaks: peak picking\n3. XCMS groupChromPeaks: determining shared ions across samples\n4. XCMS adjustRtime: retention time correction\n5. XCMS fillChromPeaks: integrating areas of missing peaks\n6. CAMERA.annotate: annotation\n", + "changelog": "# Changelog\n\nAll notable changes to this project will be documented in this file.\n\n## [1.0] - 2023-11-22\n\nFirst release\n\n" } ], - "path": "./workflows/metabomics/lcms-preprocessing", - "readme": "# Mass spectrometry: LC-MS preprocessing with XCMS \n\nThis workflow uses the XCMS tool R package [(Smith, C.A. 2006)](https://bioconductor.org/packages/release/bioc/html/xcms.html) to extract, filter, align and fill gaps, and uses the CAMERA R package [(Kuhl, C 2012)](https://bioconductor.org/packages/release/bioc/html/CAMERA.html) to annotate isotopes, adducts and fragments.\n\n\ud83c\udf93 For more information see the [Galaxy Training Network tutorial: Mass spectrometry: LC-MS preprocessing with XCMS](https://training.galaxyproject.org/training-material/topics/metabolomics/tutorials/lcms-preprocessing/tutorial.html)\n\n## Inputs\n### sampleMetadata\nThe sampleMetadata tabular file corresponds to a table containing information about your samples\n\nA sample metadata file contains various information for each of your raw files:\n- Classes which will be used during the preprocessing steps\n- Analytical batches which will be useful for a batch correction step, along with sample types (pool/sample) and injection order\n- Different experimental conditions which can be used for statistics\n- Any information about samples that you want to keep, in a column format\n\nThe content of your sample metadata file has to be filled by you, since it is not contained in your raw data. 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molecular\ndynamics simulation with GROMACS.\n\nThis is a simple workflow intended for use as a subworkflow in more complex\nMD workflows. It is used as a subworkflow by the GROMACS MMGBSA and dcTMD\nworkflows. \n", + "changelog": "# Changelog\n\n## [0.1.4] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.3] 2022-05-25\n\n### Changed\n- Changed creator ORCID to absolute URI\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-12-06\n\n### Fixed\n- `.workflowhub.yml`: use `repo-name/dockstore-workflow-name` scheme for workflows.\n- Moved test data inside repo.\n\n## [0.1]\n\n- Initial version of protein-ligand parameterization workflow.\n" } ], - "path": "./workflows/computational-chemistry/protein-ligand-complex-parameterization", - "readme": "# Protein-ligand complex parameterization\n\nParameterizes an input protein (PDB) and ligand (SDF) file prior to molecular\ndynamics simulation with GROMACS.\n\nThis is a simple workflow intended for use as a subworkflow in more complex\nMD workflows. 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calculation\n\nPerform an ensemble of targeted MD simulations of a user-specified size using\nthe GROMACS PULL code and calculate dcTMD free energy and friction profiles\nfor the resulting dissocation pathway. Note that pathway separation is not\nperformed by the workflow; the user is responsible for checking the ensemble themselves.\n\nThe input protein (PDB) and ligand (SDF) files provided are parameterized by\nthe 'Protein-ligand complex parameterization' subworkflow.\n\nNote that the workflow uses a MDP file for configuring the TMD simulations; this\nis packaged alongside the workflow as `tmd.mdp`.\n\n## Citations\n* Steffen Wolf and Gerhard Stock (2018), Targeted Molecular Dynamics Calculations of Free Energy Profiles Using a Nonequilibrium Friction Correction, J. Chem. Theory Comput. doi:10.1021/acs.jctc.8b00835\n* Steffen Wolf, Benjamin Lickert, Simon Bray and Gerhard Stock (2020), Multisecond ligand dissociation dynamics from atomistic simulations, Nat. Commun. doi:10.1038/s41467-020-16655-1\n", + "changelog": "# Changelog\n\n## [0.1.5] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.4] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_setup/gmx_setup/2021.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_setup/gmx_setup/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_solvate/gmx_solvate/2021.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_solvate/gmx_solvate/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_em/gmx_em/2021.3+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_em/gmx_em/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_makendx/gmx_makendx/2021.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_makendx/gmx_makendx/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_sim/gmx_sim/2021.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_sim/gmx_sim/2022+galaxy0`\n\n## [0.1.3] 2022-05-25\n\n### Changed\n- Changed creator ORCID to absolute URI\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-12-06\n\n### Fixed\n- `.workflowhub.yml`: use `repo-name/dockstore-workflow-name` scheme for workflows.\n- Moved test data inside repo.\n\n## [0.1]\n\n- Initial version of GROMACS dcTMD workflow.\n" } ], - "path": "./workflows/computational-chemistry/gromacs-dctmd", - "readme": "# GROMACS dcTMD free energy calculation\n\nPerform an ensemble of targeted MD simulations of a user-specified size using\nthe GROMACS PULL code and calculate dcTMD free energy and friction profiles\nfor the resulting dissocation pathway. Note that pathway separation is not\nperformed by the workflow; the user is responsible for checking the ensemble themselves.\n\nThe input protein (PDB) and ligand (SDF) files provided are parameterized by\nthe 'Protein-ligand complex parameterization' subworkflow.\n\nNote that the workflow uses a MDP file for configuring the TMD simulations; this\nis packaged alongside the workflow as `tmd.mdp`.\n\n## Citations\n* Steffen Wolf and Gerhard Stock (2018), Targeted Molecular Dynamics Calculations of Free Energy Profiles Using a Nonequilibrium Friction Correction, J. Chem. Theory Comput. doi:10.1021/acs.jctc.8b00835\n* Steffen Wolf, Benjamin Lickert, Simon Bray and Gerhard Stock (2020), Multisecond ligand dissociation dynamics from atomistic simulations, Nat. 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An ensemble average is\ncalculated and returned to the user as the final input.\n\nThe input protein (PDB) and ligand (SDF) files provided are parameterized by\nthe 'Protein-ligand complex parameterization' subworkflow.\n", + "changelog": "# Changelog\n\n## [0.1.5] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_setup/gmx_setup/2021.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_setup/gmx_setup/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_editconf/gmx_editconf/2021.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_editconf/gmx_editconf/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_solvate/gmx_solvate/2021.3+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_solvate/gmx_solvate/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_em/gmx_em/2021.3+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_em/gmx_em/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_sim/gmx_sim/2021.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/gmx_sim/gmx_sim/2022+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/chemteam/md_converter/md_converter/1.9.6+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/chemteam/md_converter/md_converter/1.9.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/4.2` was updated to `toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/5.1.0`\n\n## [0.1.4] 2023-11-20\n\n- Fix author in dockstore\n- Fix changeset_revision of gmx_solvate\n\n## [0.1.3] 2022-05-25\n\n### Changed\n- Changed creator ORCID to absolute URI\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-12-06\n\n### Fixed\n- `.workflowhub.yml`: use `repo-name/dockstore-workflow-name` scheme for workflows.\n- Moved test data inside repo.\n\n## [0.1]\n\n- Initial version of GROMACS MMGBSA workflow.\n" } ], - "path": "./workflows/computational-chemistry/gromacs-mmgbsa", - "readme": "# GROMACS MMGBSA free energy calculation\n\nPerform an ensemble of MD simulations of a user-specified size using GROMACS,\nand calculate MMGBSA free energies using AmberTools. An ensemble average is\ncalculated and returned to the user as the final input.\n\nThe input protein (PDB) and ligand (SDF) files provided are parameterized by\nthe 'Protein-ligand complex parameterization' subworkflow.\n" + "path": "./workflows/computational-chemistry/gromacs-mmgbsa" }, { "version": 1.2, @@ -1151,11 +57774,845 @@ "name": "Tim Dudgeon", "orcid": "0000-0001-6879-5194" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Virtual screening of the SARS-CoV-2 main protease with rDock and pose scoring", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-0621-6705", + "name": "Simon Bray" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0001-6879-5194", + "name": "Tim Dudgeon" + } + ], + "format-version": "0.1", + "license": "MIT", + "name": "Fragment-based virtual screening using rDock for docking and SuCOS for pose scoring", + "release": "0.1.5", + "steps": { + "0": { + "annotation": "Number of docking poses to generate per input compound", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Number of docking poses to generate per input compound", + "name": "Number of poses" + } + ], + "label": "Number of poses", + "name": "Input parameter", + "outputs": [], + "position": { + "bottom": 391.3000030517578, + "height": 61.80000305175781, + "left": 144, + "right": 344, + "top": 329.5, + "width": 200, + "x": 144, + "y": 329.5 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "52331e17-340d-4c08-8faf-b83ac383f1ac", + "workflow_outputs": [] + }, + "1": { + "annotation": "PDB file for the receptor protein", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "PDB file for the receptor protein", + "name": "Receptor (PDB)" + } + ], + "label": "Receptor (PDB)", + "name": "Input dataset", + "outputs": [], + "position": { + "bottom": 441.3000030517578, + "height": 61.80000305175781, + "left": -412, + "right": -212, + "top": 379.5, + "width": 200, + "x": -412, + "y": 379.5 + }, + "tool_id": null, + "tool_state": "{\"optional\": false}", + "tool_version": null, + "type": "data_input", + "uuid": "156f4aeb-d160-456a-974e-7884b79cb83a", + "workflow_outputs": [] + }, + "2": { + "annotation": "Fragments in SDF format", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "Fragments in SDF format", + "name": "All fragments (SDF)" + } + ], + "label": "All fragments (SDF)", + "name": "Input dataset", + "outputs": [], + "position": { + "bottom": 633.6999969482422, + "height": 82.19999694824219, + "left": -412, + "right": -212, + "top": 551.5, + "width": 200, + "x": -412, + "y": 551.5 + }, + "tool_id": null, + "tool_state": "{\"optional\": false}", + "tool_version": null, + "type": "data_input", + "uuid": "dd2d3bc0-8138-4e66-b2d9-e5e90e27b659", + "workflow_outputs": [] + }, + "3": { + "annotation": "Parameter for parallelization of docking", + "content_id": null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "Parameter for parallelization of docking", + "name": "Collection size for docking" + } + ], + "label": "Collection size for docking", + "name": "Input parameter", + "outputs": [], + "position": { + "bottom": 790.1000061035156, + "height": 102.60000610351562, + "left": -134, + "right": 66, + "top": 687.5, + "width": 200, + "x": -134, + "y": 687.5 + }, + "tool_id": null, + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "e731045a-b2e3-4766-97b0-173be3f8f098", + "workflow_outputs": [] + }, + "4": { + "annotation": "Value between 0 and 1. 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Poses are filtered by a user-specified SuCOS threshold.\n\nA list of fragments should be specified which will be used to define the cavity\nfor docking, using the 'Frankenstein ligand' technique. For more details, please\nsee https://www.informaticsmatters.com/blog/2018/11/23/cavities-and-frankenstein-molecules.html\n\nCompounds are split into collections and then recombined to allow the workflow\nto be run in a highly parallelized fashion. To specify the level of\nparallelization, use the 'Collection size' parameter.\n", + "changelog": "# Changelog\n\n## [0.1.5] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.4] 2023-02-14\n\n### Fixed\n- Fix the changeset revisions for 2 tool shed repositories\n- Sync version of ``openbabel_compund_convert`` step to newest version\n\n## [0.1.3] 2022-05-25\n\n### Changed\n- Changed creator ORCID to absolute URI\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-12-06\n\n### Fixed\n- `.workflowhub.yml`: use `repo-name/dockstore-workflow-name` scheme for workflows.\n- Moved test data inside repo.\n\n## [0.1]\n\n- Initial version of fragment-based docking and scoring workflow.\n" } ], - "path": "./workflows/computational-chemistry/fragment-based-docking-scoring", - "readme": "# Fragment-based virtual screening with docking and pose scoring\n\nDock a compound library against a target protein with rDock and validate the\nposes generated against a reference fragment using SuCOS to compare the feature\noverlap. Poses are filtered by a user-specified SuCOS threshold.\n\nA list of fragments should be specified which will be used to define the cavity\nfor docking, using the 'Frankenstein ligand' technique. For more details, please\nsee https://www.informaticsmatters.com/blog/2018/11/23/cavities-and-frankenstein-molecules.html\n\nCompounds are split into collections and then recombined to allow the workflow\nto be run in a highly parallelized fashion. To specify the level of\nparallelization, use the 'Collection size' parameter.\n" + "path": "./workflows/computational-chemistry/fragment-based-docking-scoring" }, { "version": 1.2, @@ -1173,11 +58630,1653 @@ "name": "Wolfgang Maier", "orcid": "0000-0002-9464-6640" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes a VCF dataset of variants produced by any of the variant calling workflows in https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling and generates tabular lists of variants by Samples and by Variant, and an overview plot of variants and their allele-frequencies.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-9464-6640", + "name": "Wolfgang Maier" + } + ], + "format-version": "0.1", + "release": "0.1.1", + "license": "MIT", + "name": "Generic variation analysis reporting", + "steps": { + "0": { + "annotation": "Variation data in VCF format. 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1 + }, + "readme": "# COVID-19 sequence analysis on Illumina Amplicon PE data\n\nThis workflow implements an [iVar](https://github.com/andersen-lab/ivar) based analysis similar to\nthe one in [ncov2019-artic-nf](https://github.com/connor-lab/ncov2019-artic-nf), [covid-19-signal](https://github.com/jaleezyy/covid-19-signal/) and the Thiagen [Titan workflow](https://github.com/theiagen/public_health_viral_genomics). These workflows (written in Nextflow, Snakemake and WDL) are widely in use in [COG UK](https://www.cogconsortium.uk/), [CanCOGeN](https://www.genomecanada.ca/en/cancogen) and some US state public health laboratories.\n\nThis workflow is also the subject of a Galaxy Training Network tutorial (currently a [Work in Progress](https://github.com/galaxyproject/training-material/pull/2633)).\nIt differs from [this workflow](https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling) in\nthat it does not use `lofreq` and is aimed at rapid analysis of majority variants and lineage/clade assignment with `pangolin` and `nextclade`.\n\nTODO:\n\n1. Add support for QC using negative and positive controls\n2. Integrate with phylogeny tools including IQTree and UShER (and possibly more).\n", + "changelog": "# Changelog\n\n## [0.3] 2022-11-22\n\n- update all tools:\n - fastp from 0.20.1 to 0.23.2\n - bwa_mem from 0.7.17.1 to 0.7.17.2\n - samtools_stats from 2.0.2 to 2.0.4\n - samtools_view from 1.9 to 1.15.1\n - ivar_trim from 1.3.1 to 1.4.2\n - ivar_variants from 1.3.1 to 1.4.2\n - ivar_consensus from 1.3.1 to 1.4.2\n - multiqc from 1.9 to 1.11\n - pangolin from 3.1.14 to 4.3\n - nextclade from 1.4.1 to 2.7.0\n\n## [0.2.3] 2022-05-25\n\n### Changed\n- Changed creator ORCID to absolute URI\n\n## [0.2.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.2.1] 2021-11-04\n\n### Added\n- Added .workflowhub.yml\n\n## [0.2] - 2021-10-13\n\n### Changed\n\n- Upgrade pangolin to 3.1.14 \n - this is a bugfix release that addresses problems with commas in sequence IDs\n- Upgrade nextclade to 1.4.1\n - nextclade has a new way of dealing with the nextclade database, so it is now downloaded using nextclade itself\n - the latest release supports detecting and reporting frameshifts\n - version 1.4.1 fixes a problem with formatting columns that was present in previous versions\n- A header line is now part of the tabular reports produced by both pangolin and nextclade\n- The aligned primer-trimmed reads BAM and the multi-fasta combined consensus genomes datasets are no longer hidden as part of the workflow execution\n\n## [0.1] - 2021-06-20\n\n- Initial version of SARS-CoV-2 Illumina Amplicon pipeline - iVar based for IWC\n" } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-ivar-analysis", - "readme": "# COVID-19 sequence analysis on Illumina Amplicon PE data\n\nThis workflow implements an [iVar](https://github.com/andersen-lab/ivar) based analysis similar to\nthe one in [ncov2019-artic-nf](https://github.com/connor-lab/ncov2019-artic-nf), [covid-19-signal](https://github.com/jaleezyy/covid-19-signal/) and the Thiagen [Titan workflow](https://github.com/theiagen/public_health_viral_genomics). These workflows (written in Nextflow, Snakemake and WDL) are widely in use in [COG UK](https://www.cogconsortium.uk/), [CanCOGeN](https://www.genomecanada.ca/en/cancogen) and some US state public health laboratories.\n\nThis workflow is also the subject of a Galaxy Training Network tutorial (currently a [Work in Progress](https://github.com/galaxyproject/training-material/pull/2633)).\nIt differs from [this workflow](https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling) in\nthat it does not use `lofreq` and is aimed at rapid analysis of majority variants and lineage/clade assignment with `pangolin` and `nextclade`.\n\nTODO:\n\n1. Add support for QC using negative and positive controls\n2. 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\"is_regex\": \"true\", \"replace_pattern\": \"#CHROM\\\\tPOS\\\\tID\\\\tREF\\\\tALT\\\\tQUAL\\\\tFILTER\\\\tINFO\\\\tFORMAT\\\\tSAMPLE\", \"searchwhere\": {\"searchwhere_select\": \"line\", \"__current_case__\": 0}, \"skip_first_line\": \"false\", \"wholewords\": \"false\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.1.3", + "type": "tool", + "uuid": "0932d832-0ab4-4399-a4eb-a065e7cf1b7a", + "workflow_outputs": [ + { + "label": "annotated_softfiltered_variants", + "output_name": "outfile", + "uuid": "22a290c5-0f48-4140-b759-52ee0b73d1b2" + } + ] + } + }, + "tags": [ + "COVID-19", + "ARTIC", + "ONT", + "covid19.galaxyproject.org" + ], + "uuid": "a1ceaf35-f3d7-452d-b5ed-53a4f429d1cf" + }, + "readme": "COVID-19: variation analysis on ARTIC ONT data\n----------------------------------------------\n\nThis workflow for ONT-sequenced ARTIC data is modeled after the alignment/variant-calling steps of the [ARTIC pipeline](https://artic.readthedocs.io/en/latest/). It performs, essentially, the same steps as that pipeline\u2019s minion command, i.e. read mapping with minimap2 and variant calling with medaka. Like the Illumina ARTIC workflow it uses ivar for primer trimming. Since ONT-sequenced reads have a much higher error rate than Illumina-sequenced reads and are therefor plagued more by false-positive variant calls, this workflow does make no attempt to handle amplicons affected by potential primer-binding site mutations.\n", + "changelog": "# Changelog\n\n## [0.3.2] 2023-11-20\n\n- Fix author in dockstore\n- Use ncbi link instead of googleapis for fastq\n\n## [0.3.1] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.3] 2021-09-22\n\n### Changed\n\nThis version changes the way variants get called and and how key call\nstatistics are calculated:\n\n- Switch to medaka_variant version 1.3.2+galaxy1 for extracting variants from\n medaka consensus data.\n\n This new version of the tool is more robust against input data peculiarities\n at the VCF annotation stage:\n\n * it doesn't fail on empty BAM input\n * it doesn't crash on variant calls of unusually high quality that previously\n resulted in math domain errors when trying to calculate PHRED scores from\n very small error probabilities.\n\n This tool update also means that key INFO fields (DP, DP4, AF) are\n now based on calculations carried out by medaka tools annotate instead of by\n custom code using samtools mpileup. This has the following consequences:\n\n * the tool can now emit variant calls at complex sites with > 1 lengths of\n both the REF and the ALT allele, which were previously dropped\n * the workflow became more complex; to account for shortcomings of medaka\n tools annotate, the variant call statistics of regular variants and of\n primer binding site variants have to be determined in separate runs of the\n tool\n * All key INFO fields (DP, DP4, AF) will change slightly in this version of\n the workflow\n\nThis version also adds some of the changes around trimming of primer sequences,\nwhich have been introduced into version 0.3 of the PE Illumina worflow for\namplicon data before:\n\n- Update ivar trim to version 1.3.1\n- Run ivar trim as the last mapped reads processing step before variant\n calling, i.e., after left-alignment of indels\n\nand:\n\n- Rename the output of the ivar trim step to \"Fully processed reads for\n variant calling (primer-trimmed, realigned reads)\" like the corresponding\n output of the PE Illumina workflow\n- Fix a typo in the allowed input formats for the collection of sequenced\n reads, which caused fastqsanger.gz data to undergo an implicit and\n unnecessary decompression step.\n\n### Added\n\n- Add a step to filter out failed datasets before flattening the Qualimap BamQC\n data for use by MultiQC.\n\n Qualimap BamQC fails on empty BAM input and trying to flatten the resulting\n collection containing failed datasets would cause the invocation of the\n workflow to fail.\n\n## [0.2.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.2]\n\n- Apply the strand-bias filter only after variant annotation with snpEff. By\n producing fully annotated VCFs with and without filtering, downstream\n workflows can easily be switched between filtered/unfiltered input data\n\n## [0.1]\n\n- Initial version of COVID-19: variation analysis on ARTIC ONT data workflow\n" } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-ont-artic-variant-calling", - "readme": "COVID-19: variation analysis on ARTIC ONT data\n----------------------------------------------\n\nThis workflow for ONT-sequenced ARTIC data is modeled after the alignment/variant-calling steps of the [ARTIC pipeline](https://artic.readthedocs.io/en/latest/). It performs, essentially, the same steps as that pipeline\u2019s minion command, i.e. read mapping with minimap2 and variant calling with medaka. Like the Illumina ARTIC workflow it uses ivar for primer trimming. Since ONT-sequenced reads have a much higher error rate than Illumina-sequenced reads and are therefor plagued more by false-positive variant calls, this workflow does make no attempt to handle amplicons affected by potential primer-binding site mutations.\n" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-ont-artic-variant-calling" }, { "version": 1.2, @@ -1302,11 +65119,1746 @@ "name": "Wolfgang Maier", "orcid": "0000-0002-9464-6640" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "The workflow for Illumina-sequenced ARTIC data builds on the RNASeq workflow for paired-end data using the same steps for mapping and variant calling, but adds extra logic for trimming ARTIC primer sequences off reads with the ivar package. 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In addition, this workflow uses ivar also to identify amplicons\naffected by primer-binding site mutations and, if possible, excludes reads\nderived from such \"tainted\" amplicons when calculating allele-frequencies\nof other variants.\n", + "changelog": "# Changelog\n\n## [0.5.2] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.9+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/devteam/samtools_stats/samtools_stats/2.0.2+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/samtools_stats/samtools_stats/2.0.5`\n- `toolshed.g2.bx.psu.edu/repos/iuc/lofreq_indelqual/lofreq_indelqual/2.1.5+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/lofreq_indelqual/lofreq_indelqual/2.1.5+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ivar_trim/ivar_trim/1.3.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ivar_trim/ivar_trim/1.4.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/lofreq_call/lofreq_call/2.1.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/lofreq_call/lofreq_call/2.1.5+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/qualimap_bamqc/qualimap_bamqc/2.2.2d+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/qualimap_bamqc/qualimap_bamqc/2.2.2c+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ivar_removereads/ivar_removereads/1.3.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ivar_removereads/ivar_removereads/1.4.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_annotate/bcftools_annotate/1.10` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_annotate/bcftools_annotate/1.15.1+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n\n## [0.5.1] 2023-11-20\n\n- Fix author in dockstore\n- Use zenodo link instead of googleapis for fastq in test\n- Update output test\n\n## [0.5] - 2022-02-08\n\n### Fixed\n\n- Base selection of variants that should trigger amplicon removal on unbiased\n AF values recalculated from DP4 and DP fields instead of on AF values\n provided by lofreq call.\n\n https://github.com/CSB5/lofreq/issues/80 means that lofreq-calculated AF\n values are lower bounds of true AFs when bases are excluded from calling\n based on base quality. The extent of AF underestimation depends on the\n fraction of bases with sub-threshold (30 for this workflow) base qualities.\n\n By recalculating AFs as (DP4[2] + DP4[3]) / DP we are avoiding this issue.\n From this version on we also add a proper description to the header INFO\n line description of the AF field to be explicit about the meaning of lofreq's\n AF value.\n\n### Changed\n\n- Increase/deactivate the default upper AF threshold for biased amplicon detection\n\n By increasing the default AF threshold to 1.0 amplicon removal now gets\n triggered by default for all primer binding site mutations with unbiased\n (see AF discussion above) AF > 0.1.\n\n This change is intended to allow removal of amplicons resulting from even\n trace amounts of contamination when the intended target of the amplicon\n primers drops out because of mutations severely impacting primer binding.\n The expectation is that this would either remove contamination-contributed\n variants (like contributed by traces of delta virus in omicron preparations\n in omicron-triggered amplicon dropout regions), or at least cause them\n getting flagged as AmpliconBias calls at the VCF level.\n The exact consequences of this change need to be evaluated, but users can\n restore the previous behavior by reducing the upper AF threshold back to 0.9,\n which will reduce the extent of attempted amplicon removals substantially.\n\n- Make the amplicon bias correction more robust and better interoperable with\n the [Reporting workflow](https://github.com/iwc-workflows/sars-cov-2-variation-reporting).\n\n First and second (after amplicon removal) round of variant calling are now\n carried out with identical lofreq parameter settings.\n bcftools annotate is then used to carry over the bias-corrected call stats to\n the variant calls obtained in the first round. At the same time, both variant\n call lists are filtered with identical DP and DP_ALT filters and stats of\n filter-passing variants from the first round that fail to pass those filters\n after the second round of calling aretransferred back to the initial\n bcftools annotate output.\n If the DP and DP_ALT thresholds are chosen as in the Reporting workflow (as\n is the case with the default settings), this ensures that no initially called\n variant gets lost as a consequence of amplicon bias correction and that no\n initially filter-passing variant gets filtered out after correction.\n The AmpliconBias INFO flag is used to mark all such variants, for which\n amplicon bias correction was skipped to rescue the call.\n\n- Upgrade the Galaxy wrapper versions of ivar trim and ivar removereads.\n\n This makes it easy for users to calculate primer amplicon info from suitable\n primer scheme bed files instead of passing the info as a separate file.\n This workflow sticks to the previous behavior to avoid new requirements on\n primer names.\n- Upgrade fastp to 0.23.2.\n This update restores plots contained in the tools html output, should\n provide better performance for compressed input data, but also has a moderate\n effect on trimming results.\n- Upgrade other tools to their latest versions or wrapper versions:\n\n - bwa_mem to wrapper version 0.7.17.2\n - lofreq_call to wrapper version 2.1.5+galaxy1\n - multiqc to version 1.11\n\n None of these are expected to change the variant output produced by the\n workflow.\n\n### Added\n\n- Add a step to filter out failed datasets before flattening the Qualimap BamQC\n data for use by MultiQC.\n\n Qualimap BamQC fails on empty BAM input and trying to flatten the resulting\n collection containing failed datasets would cause the invocation of the\n workflow to fail.\n\n## [0.4.2] 2021-12-13\n\n### Added\n\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.4.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.4] - 2021-06-16\n\n### Changed\n\n- Upgrade multiqc to 1.9+galaxy1\n\n## [0.3] - 2021-05-19\n\n### Changed\n\nThis version brings a number of tweaks to the ivar-dependent steps of the\nworkflow. Together, these are expected to make variant allele frequency\ncalculations more precise, in general, and robust in the face of an increasing\nnumber of variants at primer binding sites:\n\n- Upgrade ivar from version 1.2.2 to 1.3.1\n This affects ivar trim and ivar removereads\n- Use the newly introduced -f option of ivar trim to exclude read pairs from\n further analysis that extend beyond amplicon boundaries.\n This change should be benefitial for accurate AF calculations in general,\n but in particular for corrected AF values after removal of biased amplicons,\n where aberrant read pairs often represent a larger fraction of the remaining\n reads.\n- Run ivar trim only after realignment and addition of indel qualities by\n lofeq. This should make sure that indels close to primer sequences are\n seen as read-internal events.\n- Turn the lower and upper thresholds for variant AF that triggers readremoval\n into workflow input parameters and adjust their defaults to trigger read\n removal only in more obvious cases of non-fixed variants.\n- Require a minimum depth of coverage for recalled variants after read removal\n of 20 to ensure reliable AF values.\n This change also prevents situations where variants are recalled successfully\n after read removal, but are later excluded from variant reports generated by\n the reporting workflow due to that workflow's min_dp_alt >= 10 filter.\n\n## [0.2]\n\n### Changed\n\n- Turn the AmpliconRemoval variant FILTER into an AmpliconBias INFO flag\n- Apply the strand-bias filter only after variant annotation with snpEff. By\n producing fully annotated VCFs with and without filtering, downstream\n workflows can easily be switched between filtered/unfiltered input data\n\n### Fixed\n\n- Make sure the header information about the added flag gets propagated to the\n final VCF\n\n## [0.1]\n\n- Initial version of COVID-19: variation analysis on ARTIC PE data workflow\n" } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling", - "readme": "COVID-19: variation analysis on ARTIC PE data\n---------------------------------------------\n\nThe workflow for Illumina-sequenced ampliconic data builds on the RNASeq workflow\nfor paired-end data using the same steps for mapping and variant calling, but\nadds extra logic for trimming amplicon primer sequences off reads with the ivar\npackage. In addition, this workflow uses ivar also to identify amplicons\naffected by primer-binding site mutations and, if possible, excludes reads\nderived from such \"tainted\" amplicons when calculating allele-frequencies\nof other variants.\n" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-pe-illumina-artic-variant-calling" }, { "version": 1.2, @@ -1324,11 +66876,1881 @@ "name": "Wolfgang Maier", "orcid": "0000-0002-9464-6640" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes a VCF dataset of variants produced by any of the *-variant-calling workflows in https://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling and generates tabular lists of variants by Samples and by Variant, and an overview plot of variants and their allele-frequencies.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-9464-6640", + "name": "Wolfgang Maier" + } + ], + "format-version": "0.1", + "license": "MIT", + "name": "COVID-19: variation analysis reporting", + "release": "0.3.3", + "steps": { + "0": { + "annotation": "Variation data in VCF format. 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"1.0+galaxy3", + "type": "tool", + "uuid": "583b8d59-2cc0-468e-a0b7-3b1a788c7613", + "when": null, + "workflow_outputs": [ + { + "label": "variant_frequency_plot", + "output_name": "outfile", + "uuid": "986f1d1a-02c0-4d91-9f6e-a09a088732ee" + } + ] + } + }, + "tags": [ + "COVID-19", + "covid19.galaxyproject.org" + ], + "uuid": "b08c744d-7c61-4b58-ac5f-4b5886c3c643" + }, + "readme": "COVID-19: variation analysis reporting\n--------------------------------------\n\nThis workflow takes VCF datasets of variants produced by any of the\n\"*-variant-calling\" workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling\nand generates tabular reports of variants by samples and by variant, along with\nan overview plot of variants and their allele-frequencies across all samples.\n", + "changelog": "# Changelog\n\n## [0.3.2] 2023-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.3.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.3] 2022-10-13\n\n### Changed\n\n- Upgraded to new, more flexible version of column_maker tool.\n\n This change allows a simplification of the workflow, which now uses two\n steps less for producing identical results.\n\n- Upgraded to latest version of tp_find_and_replace tool, which can handle\n multiple substitutions per tool run. Saves another step in the workflow.\n\n- Upgraded datamash to its latest tool wrapper version.\n\nThese changes should not have any effects on results except this one:\n\n- the AFcaller column of the \"Combined Variant Report by Sample\" could\n previously contain values in scientific notation for very low allele\n frequencies (< 0.001). In the new version all values in the column will be\n reported consistently in regular floating point format.\n\n## [0.2] 2022-02-11\n\n### Changed\n\n- Altered the exact meaning of the user-supplied AF and DP_ALT thresholds\n\n The AF threshold is now compared against (DP4[2] + DP4[3]) / DP, i.e. the\n unbiased AF based on all bases at the site instead of against the AF reported\n by the variant caller (which in the case of lofreq would consider only\n variant-supporting bases >= the caller's --min-bq in the numerator).\n\n Conversely, the DP_ALT threshold is now compared against DP * AF (as reported\n by the variant caller), i.e. in the case of lofreq as the caller will\n consider only bases with >= --min-bq base quality.\n\n- Reported AF values in the by-sample and the by-variant reports are now\n unbiased AF values calculated from (DP4[2] + DP4[3]) / DP as explained above.\n\n The by-sample report reports the original AF value provided by the variant\n caller in an additional AFcaller column.\n\n- Tile colors in the variant frequency summary plot are now based on unbiased\n AF values.\n\n- An extra step removing potential called variants with a caller-reported\n DP of 0 has been added to avoid division by zero errors in the calculation\n of unbiased AF values.\n\n### Fixed\n\n- Reverted the autoupdated wrapper version change for the snpsift tools\n\n The autoupdate script had problems sorting their non-standard version strings\n correctly and downgraded these wrappers instead of upgrading them\n\n- Made sure only a single changeset revision of the text_processing tools is\n used in the workflow.\n\n## [0.1.3] 2022-02-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/snpsift/snpSift_filter/4.3+t.galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/snpsift/snpSift_filter/4.3.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/snpsift/snpSift_extractFields/4.3+t.galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/snpsift/snpSift_extractFields/4.3.0`\n- `toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/4.2` was updated to `toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/5.1.0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/column_maker/Add_a_column1/1.5` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/column_maker/Add_a_column1/1.6`\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.1]\n\n- Initial version of COVID-19: variation analysis reporting\n" } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-variation-reporting", - "readme": "COVID-19: variation analysis reporting\n--------------------------------------\n\nThis workflow takes VCF datasets of variants produced by any of the\n\"*-variant-calling\" workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling\nand generates tabular reports of variants by samples and by variant, along with\nan overview plot of variants and their allele-frequencies across all samples.\n" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-variation-reporting" }, { "version": 1.2, @@ -1346,10 +68768,1242 @@ "name": "Wolfgang Maier", "orcid": "0000-0002-9464-6640" } - ] + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Build a consensus sequence from FILTER PASS variants with intrasample allele-frequency above a configurable consensus threshold.\nHard-mask regions with low coverage (but not consensus variants within them) and ambiguous sites.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-9464-6640", + "name": "Wolfgang Maier" + } + ], + "format-version": "0.1", + "license": "MIT", + "name": "COVID-19: consensus construction", + "release": "0.4.2", + "steps": { + "0": { + "annotation": "Collection of VCFs produced by upstream workflows for variation analysis", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Collection of VCFs produced by upstream workflows for variation analysis", + "name": "Variant calls" + } + ], + "label": "Variant calls", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 0.0, + "top": 306.13330078125 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "fca4e710-87a7-4cb6-9ff1-f9a8dc84ca37", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Only variant calls with an allele-frequency greater this value will be considered consensus variants.", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "Only variant calls with an allele-frequency greater this value will be considered consensus variants.", + "name": "min-AF for consensus variant" + } + ], + "label": "min-AF for consensus variant", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0.45001220703125, + "top": 469.0 + }, + "tool_id": null, + "tool_state": "{\"default\": 0.75, \"parameter_type\": \"float\", \"optional\": true}", + "tool_version": null, + "type": "parameter_input", + "uuid": "52664bd7-b500-40a1-935b-8ac6df7003e5", + "when": null, + "workflow_outputs": [ + { + "label": "consensus_af_threshold", + "output_name": "output", + "uuid": "0d802d31-bb4c-41e3-8e84-c1d99b914ee9" + } + ] + }, + "2": { + "annotation": "Variant calls with an allele frequency higher than this value, but lower than the AF threshold for consensus variants will be considered questionable and the respective sites be masked (with Ns) in the consensus sequence.", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ + { + "description": "Variant calls with an allele frequency higher than this value, but lower than the AF threshold for consensus variants will be considered questionable and the respective sites be masked (with Ns) in the consensus sequence.", + "name": "min-AF for failed variants" + } + ], + "label": "min-AF for failed variants", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0.45001220703125, + "top": 640.6500244140625 + }, + "tool_id": null, + "tool_state": "{\"default\": 0.25, \"parameter_type\": \"float\", \"optional\": true}", + "tool_version": null, + "type": "parameter_input", + "uuid": "a2a15cce-94ec-4a76-a3ff-3ea898e9c678", + "when": null, + "workflow_outputs": [ + { + "label": "non_consensus_af_threshold", + "output_name": "output", + "uuid": "16c62493-ad4b-46da-8790-a8094d01a130" + } + ] + }, + "3": { + "annotation": "Fully processed BAMs as generated by upstream workflows for variation analysis. 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construction\n--------------------------------\n\nThis workflow aims at generating reliable consensus sequences from variant\ncalls according to transparent criteria that capture at least some of the\ncomplexity of variant calling.\n\nIt takes a collection of VCFs (with DP and DP4 INFO fields) and a collection of\nthe corresponding aligned reads (for the purpose of calculating genome-wide\ncoverage) such as produced by any of the variant calling workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling\nand generates a collection of viral consensus sequences and a multisample FASTA\nof all these sequences.\n\nEach consensus sequence is guaranteed to capture all called, filter-passing (as\nper the FILTER column of the VCF input) variants found in the VCF of its sample\nthat reach a user-defined consensus allele frequency threshold.\n\nFilter-failing variants and variants below a second user-defined minimal\nallele frequency threshold will be ignored.\n\nGenomic positions of filter-passing variants with an allele frequency in\nbetween the two thresholds will be hard-masked (with N) in the consensus\nsequence of their sample.\n\nGenomic positions with a coverage (calculated from the read alignments input)\nbelow another user-defined threshold will be hard-masked, too, unless they are\nconsensus variant sites.\n", + "changelog": "# Changelog\n\n## [0.4.2] 2024-03-06\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.29.2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.30.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_consensus/bcftools_consensus/1.15.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_consensus/bcftools_consensus/1.15.1+galaxy3`\n\n## [0.4.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.4] 2022-10-21\n\n### Fixed\n- Restored original functionality that was dropped accidentally in release 0.2:\n\n when there are zero consensus variants to be integrated into the reference\n genome (input VCF with no variants), bcftools consensus 1.10 would silently\n skip processing of that sequence *including the incorpartion of masking\n regions* into the final consensus genome. As a result, a genome covered by\n few or no reads at all would have its consensus sequence reported as\n all-reference instead of all Ns.\n The initial release of the workflow worked around this problem by\n pre-masking the reference before passing it to bcftools consensus, but the\n corresponding step was dropped as seemingly redundant in release 0.2.\n\n With v1.14, the edge case behavior with zero variants in the input VCF has\n been fixed as a bug in bcftools consensus\n (https://github.com/samtools/bcftools/issues/1592)\n so the workflow fix in this release consists of a simple update to bcftools\n consensus 1.15.1.\n\n### Changed\n- Upgraded to new, more flexible version of column_maker tool.\n\n This change allows a simplification of the workflow, which now uses five\n steps less for producing identical results.\n\n- Updated bcftools consensus to v1.15.1.\n\n## [0.3] 2022-02-02\n\n### Fixed\n- Apply AF thresholds on unbiased AF values recalculated from DP4 and DP fields\n instead of on AF values provided by the variant caller to ensure proper\n variant gating (into consensus and ambiguous variants) for lofreq-called\n data.\n\n https://github.com/CSB5/lofreq/issues/80 means that lofreq-calculated AF\n values are lower bounds of true AFs when bases are excluded from calling\n based on base quality. The extent of AF underestimation depends on the\n fraction of bases with sub-threshold (30 for this workflow) base qualities.\n\n By recalculating AFs as (DP4[2] + DP4[3]) / DP we avoid this issue for\n variant calls generated by lofreq. For variants called with Galaxy's medaka\n consensus/variant wrappers, original AFs are computed with the exact same\n formula so the recalculation by the workflow does not affect variant gating\n in that case.\n\n### Changed\n- Increase the default for consensus variant allele frequency threshold to 0.75.\n Correct calculation of unbiased AF values increases the typical AF of\n consensus variants more than enough to justify the change.\n- The following tools are updated to their latest wrapper versions or revisions:\n\n - bcftools_consensus\n - collapse_collections\n - the gops subtract and merge tools\n - snpsift\n\n None of these updates are expected to impact the generated consensus\n sequences.\n\n## [0.2.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.2.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.2] - 2021-04-30\n\n### Changed\n- Lower the default for consensus variant allele frequency threshold to 0.7\n (from 0.8).\n This was empirically determined to capture a relevant number of variants at\n sites that are problematic to call.\n- Increase the default variant allele frequency threshold for ambiguous sites\n to 0.25 (from 0.2) to obtain somewhat cleaner consensus sequences.\n- Use *SnpSift extract*, instead of *VCFtoTab-delimited* followed by *Cut*, to\n generate required tabular views of variants in one step.\n- Eliminate the use of *bedtools MaskFastaBed*, which was redundant with\n specifying masking regions directly at the *bcftools consensus* step.\n- Reduce the number of processing steps further by changing result dataset\n types through post-job actions appropriately to avoid implicit conversions,\n and by avoiding a redundant *SnpSift filter* step.\n\n### Fixed\n- Deletions are now reliably incorporated into the consensus sequence.\n Before they were, in most cases, N-masked because of low coverage in the\n deleted region.\n- Generally, each consensus sequence is now guaranteed to capture all consensus\n variants of its samples as stated in the README, independent of it residing\n in low-coverage regions or not.\n\n## [0.1]\n\n- Initial version of COVID-19: consensus construction\n" } ], - "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-consensus-from-variation", - "readme": "COVID-19: consensus construction\n--------------------------------\n\nThis workflow aims at generating reliable consensus sequences from variant\ncalls according to transparent criteria that capture at least some of the\ncomplexity of variant calling.\n\nIt takes a collection of VCFs (with DP and DP4 INFO fields) and a collection of\nthe corresponding aligned reads (for the purpose of calculating genome-wide\ncoverage) such as produced by any of the variant calling workflows in\nhttps://github.com/galaxyproject/iwc/tree/main/workflows/sars-cov-2-variant-calling\nand generates a collection of viral consensus sequences and a multisample FASTA\nof all these sequences.\n\nEach consensus sequence is guaranteed to capture all called, filter-passing (as\nper the FILTER column of the VCF input) variants found in the VCF of its sample\nthat reach a user-defined consensus allele frequency threshold.\n\nFilter-failing variants and variants below a second user-defined minimal\nallele frequency threshold will be ignored.\n\nGenomic positions of filter-passing variants with an allele frequency in\nbetween the two thresholds will be hard-masked (with N) in the consensus\nsequence of their sample.\n\nGenomic positions with a coverage (calculated from the read alignments input)\nbelow another user-defined threshold will be hard-masked, too, unless they are\nconsensus variant sites.\n" + "path": "./workflows/sars-cov-2-variant-calling/sars-cov-2-consensus-from-variation" } ] \ No newline at end of file From 87fda6b23454f7fbdceacae1b6a73259f1682dd1 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 09/74] Show description on listing, fix title --- showcase/src/components/WorkflowList.vue | 21 ++++++++++++++------- showcase/src/pages/index.astro | 4 ++-- 2 files changed, 16 insertions(+), 9 deletions(-) diff --git a/showcase/src/components/WorkflowList.vue b/showcase/src/components/WorkflowList.vue index d9b4b2cbc..8e7130ab8 100644 --- a/showcase/src/components/WorkflowList.vue +++ b/showcase/src/components/WorkflowList.vue @@ -1,9 +1,11 @@ @@ -13,16 +15,21 @@ grid-template-columns: repeat(3, 1fr); gap: 10px; } +.grid-item { + border: 1px solid #ccc; + border-radius: 4px; + padding: 10px; + box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1); +} \ No newline at end of file diff --git a/showcase/src/pages/index.astro b/showcase/src/pages/index.astro index 8a6ab9028..4207bcec1 100644 --- a/showcase/src/pages/index.astro +++ b/showcase/src/pages/index.astro @@ -5,10 +5,10 @@ import WorkflowList from "../components/WorkflowList.vue"; import { Debug } from 'astro:components'; --- - +

    Intergalactic Workflow Commission Gallery

    - +
    From 7ef96998af286f60acb986515dec1d9f4e92f2f4 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 10/74] Add astro/tailwind --- astro.config.mjs | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 astro.config.mjs diff --git a/astro.config.mjs b/astro.config.mjs new file mode 100644 index 000000000..0a5f36a87 --- /dev/null +++ b/astro.config.mjs @@ -0,0 +1,7 @@ +import { defineConfig } from 'astro/config'; +import tailwind from "@astrojs/tailwind"; + +// https://astro.build/config +export default defineConfig({ + integrations: [tailwind()] +}); \ No newline at end of file From 59f3a55fa43680abdebff7f0f9ac394ed2d9dace Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 11/74] Basic astro working, try nuxt now --- showcase/astro.config.mjs | 5 +- showcase/package-lock.json | 1178 ++++++++++++++++- showcase/package.json | 2 + showcase/src/components/WorkflowList.vue | 39 +- showcase/src/layouts/Layout.astro | 2 + showcase/src/pages/index.astro | 6 +- .../{workflows => workflow}/[...slug].astro | 4 +- showcase/src/styles/tailwind.css | 105 ++ showcase/tailwind.config.mjs | 56 + workflow_manifest.json | 2 +- 10 files changed, 1380 insertions(+), 19 deletions(-) rename showcase/src/pages/{workflows => workflow}/[...slug].astro (92%) create mode 100644 showcase/src/styles/tailwind.css create mode 100644 showcase/tailwind.config.mjs diff --git a/showcase/astro.config.mjs b/showcase/astro.config.mjs index 2ff3bdcfc..03021b498 100644 --- a/showcase/astro.config.mjs +++ b/showcase/astro.config.mjs @@ -1,8 +1,9 @@ import { defineConfig } from 'astro/config'; - import vue from "@astrojs/vue"; +import tailwind from "@astrojs/tailwind"; + // https://astro.build/config export default defineConfig({ - integrations: [vue()] + integrations: [vue(), tailwind()] }); \ No newline at end of file diff --git a/showcase/package-lock.json b/showcase/package-lock.json index 987ee4a18..7468a329a 100644 --- a/showcase/package-lock.json +++ b/showcase/package-lock.json @@ -9,12 +9,25 @@ "version": "0.0.1", "dependencies": { "@astrojs/check": "^0.7.0", + "@astrojs/tailwind": "^5.1.0", "@astrojs/vue": "^4.2.0", "astro": "^4.8.6", + "tailwindcss": "^3.4.3", "typescript": "^5.4.5", "vue": "^3.4.27" } }, + "node_modules/@alloc/quick-lru": { + "version": "5.2.0", + "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz", + "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==", + "engines": { + "node": ">=10" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/@ampproject/remapping": { "version": "2.3.0", "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz", @@ -137,6 +150,20 @@ "node": "^18.17.1 || ^20.3.0 || >=21.0.0" } }, + "node_modules/@astrojs/tailwind": { + "version": "5.1.0", + "resolved": "https://registry.npmjs.org/@astrojs/tailwind/-/tailwind-5.1.0.tgz", + "integrity": "sha512-BJoCDKuWhU9FT2qYg+fr6Nfb3qP4ShtyjXGHKA/4mHN94z7BGcmauQK23iy+YH5qWvTnhqkd6mQPQ1yTZTe9Ig==", + "dependencies": { + "autoprefixer": "^10.4.15", + "postcss": "^8.4.28", + "postcss-load-config": "^4.0.2" + }, + "peerDependencies": { + "astro": "^3.0.0 || ^4.0.0", + "tailwindcss": "^3.0.24" + } + }, "node_modules/@astrojs/telemetry": { "version": "3.1.0", "resolved": "https://registry.npmjs.org/@astrojs/telemetry/-/telemetry-3.1.0.tgz", @@ -1505,6 +1532,43 @@ "url": "https://opencollective.com/libvips" } }, + "node_modules/@isaacs/cliui": { + "version": "8.0.2", + "resolved": "https://registry.npmjs.org/@isaacs/cliui/-/cliui-8.0.2.tgz", + "integrity": "sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==", + "dependencies": { + "string-width": "^5.1.2", + "string-width-cjs": "npm:string-width@^4.2.0", + "strip-ansi": "^7.0.1", + "strip-ansi-cjs": "npm:strip-ansi@^6.0.1", + "wrap-ansi": "^8.1.0", + "wrap-ansi-cjs": "npm:wrap-ansi@^7.0.0" + }, + "engines": { + "node": ">=12" + } + }, + "node_modules/@isaacs/cliui/node_modules/emoji-regex": { + "version": "9.2.2", + "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-9.2.2.tgz", + "integrity": "sha512-L18DaJsXSUk2+42pv8mLs5jJT2hqFkFE4j21wOmgbUqsZ2hL72NsUU785g9RXgo3s0ZNgVl42TiHp3ZtOv/Vyg==" + }, + "node_modules/@isaacs/cliui/node_modules/string-width": { + "version": "5.1.2", + "resolved": "https://registry.npmjs.org/string-width/-/string-width-5.1.2.tgz", + "integrity": "sha512-HnLOCR3vjcY8beoNLtcjZ5/nxn2afmME6lhrDrebokqMap+XbeW8n9TXpPDOqdGK5qcI3oT0GKTW6wC7EMiVqA==", + "dependencies": { + "eastasianwidth": "^0.2.0", + "emoji-regex": "^9.2.2", + "strip-ansi": "^7.0.1" + }, + "engines": { + "node": ">=12" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/@jridgewell/gen-mapping": { "version": "0.3.5", "resolved": "https://registry.npmjs.org/@jridgewell/gen-mapping/-/gen-mapping-0.3.5.tgz", @@ -1580,6 +1644,15 @@ "node": ">= 8" } }, + "node_modules/@pkgjs/parseargs": { + "version": "0.11.0", + "resolved": "https://registry.npmjs.org/@pkgjs/parseargs/-/parseargs-0.11.0.tgz", + "integrity": "sha512-+1VkjdD0QBLPodGrJUeqarH8VAIvQODIbwh9XpP5Syisf7YoQgsJKPNFoqqLQlu+VQ/tVSshMR6loPMn8U+dPg==", + "optional": true, + "engines": { + "node": ">=14" + } + }, "node_modules/@polka/url": { "version": "1.0.0-next.25", "resolved": "https://registry.npmjs.org/@polka/url/-/url-1.0.0-next.25.tgz", @@ -2329,6 +2402,11 @@ "node": ">=4" } }, + "node_modules/any-promise": { + "version": "1.3.0", + "resolved": "https://registry.npmjs.org/any-promise/-/any-promise-1.3.0.tgz", + "integrity": "sha512-7UvmKalWRt1wgjL1RrGxoSJW/0QZFIegpeGvZG9kjp8vrRu55XTHbwnqq2GpXm9uLbcuhxm3IqX9OB4MZR1b2A==" + }, "node_modules/anymatch": { "version": "3.1.3", "resolved": "https://registry.npmjs.org/anymatch/-/anymatch-3.1.3.tgz", @@ -2341,6 +2419,11 @@ "node": ">= 8" } }, + "node_modules/arg": { + "version": "5.0.2", + "resolved": "https://registry.npmjs.org/arg/-/arg-5.0.2.tgz", + "integrity": "sha512-PYjyFOLKQ9y57JvQ6QLo8dAgNqswh8M1RMJYdQduT6xbWSgK36P/Z/v+p888pM69jMMfS8Xd8F6I1kQ/I9HUGg==" + }, "node_modules/argparse": { "version": "2.0.1", "resolved": "https://registry.npmjs.org/argparse/-/argparse-2.0.1.tgz", @@ -2444,6 +2527,42 @@ "sharp": "^0.33.3" } }, + "node_modules/autoprefixer": { + "version": "10.4.19", + "resolved": "https://registry.npmjs.org/autoprefixer/-/autoprefixer-10.4.19.tgz", + "integrity": "sha512-BaENR2+zBZ8xXhM4pUaKUxlVdxZ0EZhjvbopwnXmxRUfqDmwSpC2lAi/QXvx7NRdPCo1WKEcEF6mV64si1z4Ew==", + "funding": [ + { + "type": "opencollective", + "url": "https://opencollective.com/postcss/" + }, + { + "type": "tidelift", + "url": "https://tidelift.com/funding/github/npm/autoprefixer" + }, + { + "type": "github", + "url": "https://github.com/sponsors/ai" + } + ], + "dependencies": { + "browserslist": "^4.23.0", + "caniuse-lite": "^1.0.30001599", + "fraction.js": "^4.3.7", + "normalize-range": "^0.1.2", + "picocolors": "^1.0.0", + "postcss-value-parser": "^4.2.0" + }, + "bin": { + "autoprefixer": "bin/autoprefixer" + }, + "engines": { + "node": "^10 || ^12 || >=14" + }, + "peerDependencies": { + "postcss": "^8.1.0" + } + }, "node_modules/axobject-query": { "version": "4.0.0", "resolved": "https://registry.npmjs.org/axobject-query/-/axobject-query-4.0.0.tgz", @@ -2461,6 +2580,11 @@ "url": "https://github.com/sponsors/wooorm" } }, + "node_modules/balanced-match": { + "version": "1.0.2", + "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz", + "integrity": "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==" + }, "node_modules/base-64": { "version": "1.0.0", "resolved": "https://registry.npmjs.org/base-64/-/base-64-1.0.0.tgz", @@ -2530,6 +2654,14 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/brace-expansion": { + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.1.tgz", + "integrity": "sha512-XnAIvQ8eM+kC6aULx6wuQiwVsnzsi9d3WxzV3FpWTGA19F621kwdbsAcFKXgKUHZWsy+mY6iL1sHTxWEFCytDA==", + "dependencies": { + "balanced-match": "^1.0.0" + } + }, "node_modules/braces": { "version": "3.0.3", "resolved": "https://registry.npmjs.org/braces/-/braces-3.0.3.tgz", @@ -2597,6 +2729,14 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/camelcase-css": { + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/camelcase-css/-/camelcase-css-2.0.1.tgz", + "integrity": "sha512-QOSvevhslijgYwRx6Rv7zKdMF8lbRmx+uQGx2+vDc+KI/eBnsy9kit5aj23AgGu3pa4t9AgwbnXWqS+iOY+2aA==", + "engines": { + "node": ">= 6" + } + }, "node_modules/caniuse-lite": { "version": "1.0.30001620", "resolved": 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"https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==" }, + "yaml": { + "version": "2.4.2", + "resolved": "https://registry.npmjs.org/yaml/-/yaml-2.4.2.tgz", + "integrity": "sha512-B3VqDZ+JAg1nZpaEmWtTXUlBneoGx6CPM9b0TENK6aoSu5t73dItudwdgmi6tHlIZZId4dZ9skcAQ2UbcyAeVA==" + }, "yargs": { "version": "17.7.2", "resolved": "https://registry.npmjs.org/yargs/-/yargs-17.7.2.tgz", diff --git a/showcase/package.json b/showcase/package.json index 812a52d2c..9fe50a501 100644 --- a/showcase/package.json +++ b/showcase/package.json @@ -11,8 +11,10 @@ }, "dependencies": { "@astrojs/check": "^0.7.0", + "@astrojs/tailwind": "^5.1.0", "@astrojs/vue": "^4.2.0", "astro": "^4.8.6", + "tailwindcss": "^3.4.3", "typescript": "^5.4.5", "vue": "^3.4.27" } diff --git a/showcase/src/components/WorkflowList.vue b/showcase/src/components/WorkflowList.vue index 8e7130ab8..a7e081cea 100644 --- a/showcase/src/components/WorkflowList.vue +++ b/showcase/src/components/WorkflowList.vue @@ -2,34 +2,55 @@
    \ No newline at end of file diff --git a/showcase/src/layouts/Layout.astro b/showcase/src/layouts/Layout.astro index 7b552be19..38f3da107 100644 --- a/showcase/src/layouts/Layout.astro +++ b/showcase/src/layouts/Layout.astro @@ -1,4 +1,6 @@ --- +import "../styles/tailwind.css"; + interface Props { title: string; } diff --git a/showcase/src/pages/index.astro b/showcase/src/pages/index.astro index 4207bcec1..4481d541a 100644 --- a/showcase/src/pages/index.astro +++ b/showcase/src/pages/index.astro @@ -2,7 +2,7 @@ import Layout from '../layouts/Layout.astro'; import manifest from '../data/workflow_manifest.json'; import WorkflowList from "../components/WorkflowList.vue"; -import { Debug } from 'astro:components'; + --- @@ -16,10 +16,8 @@ import { Debug } from 'astro:components'; main { margin: auto; padding: 1rem; - width: 800px; - max-width: calc(100% - 2rem); + max-width: calc(100% - 8rem); color: white; - font-size: 20px; line-height: 1.6; } .astro-a { diff --git a/showcase/src/pages/workflows/[...slug].astro b/showcase/src/pages/workflow/[...slug].astro similarity index 92% rename from showcase/src/pages/workflows/[...slug].astro rename to showcase/src/pages/workflow/[...slug].astro index f586574cb..0cfed24d7 100644 --- a/showcase/src/pages/workflows/[...slug].astro +++ b/showcase/src/pages/workflow/[...slug].astro @@ -8,10 +8,10 @@ export const getStaticPaths = async () => { const paths = manifest.map((workflow) => { // Extract the slug from the workflow path const slug = workflow.path.replace('./workflows/', ''); - return { params: { slug: slug } }; + return { params: { slug: slug.split('/') } }; }); - return paths; + return { paths }; }; // Define getStaticProps to fetch data for each page diff --git a/showcase/src/styles/tailwind.css b/showcase/src/styles/tailwind.css new file mode 100644 index 000000000..5c32a7c59 --- /dev/null +++ b/showcase/src/styles/tailwind.css @@ -0,0 +1,105 @@ +/* @import "./prose.css"; */ +@tailwind base; +@tailwind components; +@tailwind utilities; + + +@layer components { + .button { + @apply font-sans inline-flex h-14 items-center justify-center gap-4 rounded-full border border-astro-gray-100 px-10 text-center text-base font-medium leading-none tracking-wide text-white no-underline transition hover:bg-white/10; + } + + .button.button-primary { + @apply border-none bg-blue-purple-gradient text-white hover:bg-blue-purple-gradient hover:brightness-75; + } + + .button.button-white { + @apply border-none bg-astro-gray-100 text-astro-blue hover:brightness-75; + } + + .button.button-sm { + @apply h-10 gap-2 px-6 text-sm tracking-wide; + } + .button.button-xs { + @apply h-6 gap-2 px-3 text-xs tracking-wide; + } +} + +@layer utilities { + /* Hide scrollbar for Chrome, Safari and Opera */ + .no-scrollbar::-webkit-scrollbar { + display: none; + } + /* Hide scrollbar for IE, Edge and Firefox */ + .no-scrollbar { + -ms-overflow-style: none; /* IE and Edge */ + scrollbar-width: none; /* Firefox */ + } +} + +@layer typography { + :root { + --sans-weight-normal: 200; + --sans-weight-bold: 600; + --sans-wght: "wght" var(--sans-weight); + --sans-case: "case" on; + --sans-ss03: "ss03" on; + --sans-cpsp: "cpsp" on; + --sans-cv03: "cv03" on; + --sans-cv04: "cv04" on; + --sans-cv05: "cv05" on; + --sans-cv06: "cv06" on; + + --mono-style-italic: "ital" 1; + --mono-style-normal: "ital" 0; + --mono-calt: "calt" on; + --mono-zero: "zero" on; + --mono-style: var(--mono-style-normal); + --mono-ital: var(--mono-style); + + --heading-style-normal: "slnt" 0; + --heading-style-italic: "slnt" 8; + --heading-weight-light: 290; + --heading-weight-normal: 380; + --heading-weight-bold: 475; + --heading-weight: var(--heading-weight-light); + --heading-style: var(--heading-style-normal); + --heading-wght: "wght" var(--heading-weight); + --heading-salt: "salt" on; + --heading-ss06: "ss06" on; + --heading-ss11: "ss11" on; + --heading-cv09: "cv09" on; + --heading-liga: "liga" on; + --heading-calt: "calt" on; + } + + .font-italic { + --mono-style: var(--mono-style-italic); + --heading-style: var(--mono-style-normal); + } + + .font-strong { + --sans-weight: var(--sans-weight-bold); + --heading-weight: var(--heading-weight-bold); + } + + .font-sans { + font-family: Inter, inter-fallback, system-ui, sans-serif; + font-variation-settings: var(--sans-wght); + font-feature-settings: var(--sans-case), var(--sans-ss03), var(--sans-cpsp), var(--sans-cv03), + var(--cv04), var(--cv05), var(--cv06); + } + + .font-mono { + font-family: MDIO, md-io-fallback, monospace; + font-variation-settings: var(--mono-ital); + font-feature-settings: var(--mono-calt), var(--mono-zero); + } + + .font-heading { + font-family: Obviously, obviously-fallback, system-ui, sans-serif; + font-variation-settings: var(--heading-wdth), var(--heading-wght), var(--heading-slnt); + font-feature-settings: var(--heading-salt), var(--heading-ss06), var(--heading-ss11), + var(--heading-cv09), var(--heading-liga), var(--heading-calt); + } +} \ No newline at end of file diff --git a/showcase/tailwind.config.mjs b/showcase/tailwind.config.mjs new file mode 100644 index 000000000..c95fb5f5b --- /dev/null +++ b/showcase/tailwind.config.mjs @@ -0,0 +1,56 @@ +/** @type {import('tailwindcss').Config} */ +export default { + content: ['./src/**/*.{astro,html,js,jsx,md,mdx,svelte,ts,tsx,vue}'], + theme: { + theme: { + fontFamily: {}, + extend: { + colors: { + black: "#0D0F14", + // TODO: replace with brand off-white color + white: "#ffffff", + "astro-gray": { + 100: "#F2F6FA", + 200: "#BFC1C9", + 300: "#858B98", + 400: "#545864", + 500: "#343841", + 600: "#23262D", + 700: "#17191E", + }, + "astro-blue": "#3245FF", + "astro-purple": "#BC52EE", + "astro-purple-dark": "#3F224D", + "astro-red": "#D83333", + "astro-pink": { + light: "#E8C4F9", + DEFAULT: "#F041FF", + }, + "astro-orange": "#F8E42E", + "astro-yellow": "#FF7D54", + "astro-hover": "#E8C4F9", + }, + backgroundImage: { + "blue-purple-gradient": "linear-gradient(83.21deg, #3245FF 0%, #B845ED 100%)", + "blue-green-gradient": "linear-gradient(247.23deg, #4AF2C8 0%, #2F4CB3 100%)", + "red-pink-gradient": "linear-gradient(66.77deg, #D83333 0%, #F041FF 100%)", + "orange-yellow-gradient": "linear-gradient(266.93deg, #F8E42E 0%, #FF7D54 100%)", + }, + height: { + header: "5rem", + }, + lineHeight: { + prose: "1.8125", + }, + maxWidth: { + prose: "768px", + }, + zIndex: { + blur: "-1", + grid: "-2", + }, + }, + }, + }, + plugins: [], +} diff --git a/workflow_manifest.json b/workflow_manifest.json index f5caaffeb..26604517b 100644 --- a/workflow_manifest.json +++ b/workflow_manifest.json @@ -298,7 +298,7 @@ "changelog": "# Changelog\n\n## [0.1.13] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.1.12] 2024-04-16\n\n### Changed\n\n- Remove unnecessary param_value_from_file step and directly pass file with identifiers to fasterqdump\n\n## [0.1.11] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.1.10] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.1.9] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1.8] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.1.7] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n\n## [0.1.6] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3`\n\n## [0.1.5] 2023-09-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1`\n\n## [0.1.4] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0`\n\n## [0.1.3] 2022-02-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1`\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.1] - 2021-06-23\n\n### Added\n\n- Initial version of Parallel Accession Download workflow.\n" } ], - "path": "./workflows/data-fetching/parallel-accession-download" + "path": "./workflows/data-fetching" }, { "version": 1.2, From 8f4553d130d10a280712336e2fcb7d2b934668c2 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 12/74] Stage to astro --- showcase/src/env.d.ts | 1 - {showcase => showcase_astro}/.gitignore | 0 {showcase => showcase_astro}/README.md | 0 {showcase => showcase_astro}/astro.config.mjs | 0 {showcase => showcase_astro}/package-lock.json | 0 {showcase => showcase_astro}/package.json | 0 {showcase => showcase_astro}/public/favicon.svg | 0 {showcase => showcase_astro}/src/components/Card.astro | 0 {showcase => showcase_astro}/src/components/WorkflowDetail.vue | 0 {showcase => showcase_astro}/src/components/WorkflowList.vue | 0 {showcase => showcase_astro}/src/data/workflow_manifest.json | 0 showcase_astro/src/env.d.ts | 1 + {showcase => showcase_astro}/src/layouts/Layout.astro | 0 {showcase => showcase_astro}/src/pages/index.astro | 0 {showcase => showcase_astro}/src/pages/workflow/[...slug].astro | 0 {showcase => showcase_astro}/src/styles/tailwind.css | 0 {showcase => showcase_astro}/tailwind.config.mjs | 0 {showcase => showcase_astro}/tsconfig.json | 0 18 files changed, 1 insertion(+), 1 deletion(-) delete mode 100644 showcase/src/env.d.ts rename {showcase => showcase_astro}/.gitignore (100%) rename {showcase => showcase_astro}/README.md (100%) rename {showcase => showcase_astro}/astro.config.mjs (100%) rename {showcase => showcase_astro}/package-lock.json (100%) rename {showcase => showcase_astro}/package.json (100%) rename {showcase => showcase_astro}/public/favicon.svg (100%) rename {showcase => showcase_astro}/src/components/Card.astro (100%) rename {showcase => showcase_astro}/src/components/WorkflowDetail.vue (100%) rename {showcase => showcase_astro}/src/components/WorkflowList.vue (100%) rename {showcase => showcase_astro}/src/data/workflow_manifest.json (100%) create mode 100644 showcase_astro/src/env.d.ts rename {showcase => showcase_astro}/src/layouts/Layout.astro (100%) rename {showcase => showcase_astro}/src/pages/index.astro (100%) rename {showcase => showcase_astro}/src/pages/workflow/[...slug].astro (100%) rename {showcase => showcase_astro}/src/styles/tailwind.css (100%) rename {showcase => showcase_astro}/tailwind.config.mjs (100%) rename {showcase => showcase_astro}/tsconfig.json (100%) diff --git a/showcase/src/env.d.ts b/showcase/src/env.d.ts deleted file mode 100644 index f964fe0cf..000000000 --- a/showcase/src/env.d.ts +++ /dev/null @@ -1 +0,0 @@ -/// diff --git a/showcase/.gitignore b/showcase_astro/.gitignore similarity index 100% rename from showcase/.gitignore rename to showcase_astro/.gitignore diff --git a/showcase/README.md b/showcase_astro/README.md similarity index 100% rename from showcase/README.md rename to showcase_astro/README.md diff --git a/showcase/astro.config.mjs b/showcase_astro/astro.config.mjs similarity index 100% rename from showcase/astro.config.mjs rename to showcase_astro/astro.config.mjs diff --git a/showcase/package-lock.json b/showcase_astro/package-lock.json similarity index 100% rename from showcase/package-lock.json rename to showcase_astro/package-lock.json diff --git a/showcase/package.json b/showcase_astro/package.json similarity index 100% rename from showcase/package.json rename to showcase_astro/package.json diff --git a/showcase/public/favicon.svg b/showcase_astro/public/favicon.svg similarity index 100% rename from showcase/public/favicon.svg rename to showcase_astro/public/favicon.svg diff --git a/showcase/src/components/Card.astro b/showcase_astro/src/components/Card.astro similarity index 100% rename from showcase/src/components/Card.astro rename to showcase_astro/src/components/Card.astro diff --git a/showcase/src/components/WorkflowDetail.vue b/showcase_astro/src/components/WorkflowDetail.vue similarity index 100% rename from showcase/src/components/WorkflowDetail.vue rename to showcase_astro/src/components/WorkflowDetail.vue diff --git a/showcase/src/components/WorkflowList.vue b/showcase_astro/src/components/WorkflowList.vue similarity index 100% rename from showcase/src/components/WorkflowList.vue rename to showcase_astro/src/components/WorkflowList.vue diff --git a/showcase/src/data/workflow_manifest.json b/showcase_astro/src/data/workflow_manifest.json similarity index 100% rename from showcase/src/data/workflow_manifest.json rename to showcase_astro/src/data/workflow_manifest.json diff --git a/showcase_astro/src/env.d.ts b/showcase_astro/src/env.d.ts new file mode 100644 index 000000000..8c34fb45e --- /dev/null +++ b/showcase_astro/src/env.d.ts @@ -0,0 +1 @@ +/// \ No newline at end of file diff --git a/showcase/src/layouts/Layout.astro b/showcase_astro/src/layouts/Layout.astro similarity index 100% rename from showcase/src/layouts/Layout.astro rename to showcase_astro/src/layouts/Layout.astro diff --git a/showcase/src/pages/index.astro b/showcase_astro/src/pages/index.astro similarity index 100% rename from showcase/src/pages/index.astro rename to showcase_astro/src/pages/index.astro diff --git a/showcase/src/pages/workflow/[...slug].astro b/showcase_astro/src/pages/workflow/[...slug].astro similarity index 100% rename from showcase/src/pages/workflow/[...slug].astro rename to showcase_astro/src/pages/workflow/[...slug].astro diff --git a/showcase/src/styles/tailwind.css b/showcase_astro/src/styles/tailwind.css similarity index 100% rename from showcase/src/styles/tailwind.css rename to showcase_astro/src/styles/tailwind.css diff --git a/showcase/tailwind.config.mjs b/showcase_astro/tailwind.config.mjs similarity index 100% rename from showcase/tailwind.config.mjs rename to showcase_astro/tailwind.config.mjs diff --git a/showcase/tsconfig.json b/showcase_astro/tsconfig.json similarity index 100% rename from showcase/tsconfig.json rename to showcase_astro/tsconfig.json From ddafa84ed2c233d6f7b5ac92e179fc83c6f3a964 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 13/74] Init nuxt --- showcase_nuxt/.gitignore | 24 + showcase_nuxt/README.md | 75 + showcase_nuxt/app.vue | 5 + showcase_nuxt/nuxt.config.ts | 4 + showcase_nuxt/package-lock.json | 10776 +++++++++++++++++++++++++++ showcase_nuxt/package.json | 17 + showcase_nuxt/public/favicon.ico | Bin 0 -> 4286 bytes showcase_nuxt/server/tsconfig.json | 3 + showcase_nuxt/tsconfig.json | 4 + 9 files changed, 10908 insertions(+) create mode 100644 showcase_nuxt/.gitignore create mode 100644 showcase_nuxt/README.md create mode 100644 showcase_nuxt/app.vue create mode 100644 showcase_nuxt/nuxt.config.ts create mode 100644 showcase_nuxt/package-lock.json create mode 100644 showcase_nuxt/package.json create mode 100644 showcase_nuxt/public/favicon.ico create mode 100644 showcase_nuxt/server/tsconfig.json create mode 100644 showcase_nuxt/tsconfig.json diff --git a/showcase_nuxt/.gitignore b/showcase_nuxt/.gitignore new file mode 100644 index 000000000..4a7f73a2e --- /dev/null +++ b/showcase_nuxt/.gitignore @@ -0,0 +1,24 @@ +# Nuxt dev/build outputs +.output +.data +.nuxt +.nitro +.cache +dist + +# Node dependencies +node_modules + +# Logs +logs +*.log + +# Misc +.DS_Store +.fleet +.idea + +# Local env files +.env +.env.* +!.env.example diff --git a/showcase_nuxt/README.md b/showcase_nuxt/README.md new file mode 100644 index 000000000..f5db2a2db --- /dev/null +++ b/showcase_nuxt/README.md @@ -0,0 +1,75 @@ +# Nuxt 3 Minimal Starter + +Look at the [Nuxt 3 documentation](https://nuxt.com/docs/getting-started/introduction) to learn more. + +## Setup + +Make sure to install the dependencies: + +```bash +# npm +npm install + +# pnpm +pnpm install + +# yarn +yarn install + +# bun +bun install +``` + +## Development Server + +Start the development server on `http://localhost:3000`: + +```bash +# npm +npm run dev + +# pnpm +pnpm run dev + +# yarn +yarn dev + +# bun +bun run dev +``` + +## Production + +Build the application for production: + +```bash +# npm +npm run build + +# pnpm +pnpm run build + +# yarn +yarn build + +# bun +bun run build +``` + +Locally preview production build: + +```bash +# npm +npm run preview + +# pnpm +pnpm run preview + +# yarn +yarn preview + +# bun +bun run preview +``` + +Check out the [deployment documentation](https://nuxt.com/docs/getting-started/deployment) for more information. diff --git a/showcase_nuxt/app.vue b/showcase_nuxt/app.vue new file mode 100644 index 000000000..a495b7573 --- /dev/null +++ b/showcase_nuxt/app.vue @@ -0,0 +1,5 @@ + diff --git a/showcase_nuxt/nuxt.config.ts b/showcase_nuxt/nuxt.config.ts new file mode 100644 index 000000000..8851e7746 --- /dev/null +++ b/showcase_nuxt/nuxt.config.ts @@ -0,0 +1,4 @@ +// https://nuxt.com/docs/api/configuration/nuxt-config +export default defineNuxtConfig({ + devtools: { enabled: true } +}) diff --git a/showcase_nuxt/package-lock.json b/showcase_nuxt/package-lock.json new file mode 100644 index 000000000..c76fedd01 --- /dev/null +++ b/showcase_nuxt/package-lock.json @@ -0,0 +1,10776 @@ +{ + "name": "nuxt-app", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "nuxt-app", + "hasInstallScript": true, + "dependencies": { + "nuxt": "^3.11.2", + "vue": "^3.4.27", + "vue-router": "^4.3.2" + } + }, + "node_modules/@ampproject/remapping": { + "version": "2.3.0", + "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz", + "integrity": "sha512-30iZtAPgz+LTIYoeivqYo853f02jBYSd5uGnGpkFV0M3xOt9aN73erkgYAmZU43x4VfqcnLxW9Kpg3R5LC4YYw==", + "dependencies": { + "@jridgewell/gen-mapping": "^0.3.5", + "@jridgewell/trace-mapping": "^0.3.24" + }, + "engines": { + "node": ">=6.0.0" + } + }, + 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"preview": "nuxt preview", + "postinstall": "nuxt prepare" + }, + "dependencies": { + "nuxt": "^3.11.2", + "vue": "^3.4.27", + "vue-router": "^4.3.2" + } +} diff --git a/showcase_nuxt/public/favicon.ico b/showcase_nuxt/public/favicon.ico new file mode 100644 index 0000000000000000000000000000000000000000..18993ad91cfd43e03b074dd0b5cc3f37ab38e49c GIT binary patch literal 4286 zcmeHLOKuuL5PjK%MHWVi6lD zOGiREbCw`xmFozJ^aNatJY>w+g ze6a2@u~m#^BZm@8wco9#Crlli0uLb^3E$t2-WIc^#(?t)*@`UpuofJ(Uyh@F>b3Ph z$D^m8Xq~pTkGJ4Q`Q2)te3mgkWYZ^Ijq|hkiP^9`De={bQQ%heZC$QU2UpP(-tbl8 zPWD2abEew;oat@w`uP3J^YpsgT%~jT(Dk%oU}sa$7|n6hBjDj`+I;RX(>)%lm_7N{+B7Mu%H?422lE%MBJH!!YTN2oT7xr>>N-8OF$C&qU^ z>vLsa{$0X%q1fjOe3P1mCv#lN{xQ4_*HCSAZjTb1`}mlc+9rl8$B3OP%VT@mch_~G z7Y+4b{r>9e=M+7vSI;BgB?ryZDY4m>&wcHSn81VH1N~`0gvwH{ z8dv#hG|OK`>1;j7tM#B)Z7zDN?{6=dUal}$e Date: Tue, 10 Sep 2024 08:24:39 -0400 Subject: [PATCH 14/74] nuxtui --- showcase_nuxt/app.config.ts | 6 + showcase_nuxt/app.vue | 14 +- showcase_nuxt/nuxt.config.ts | 5 +- showcase_nuxt/package-lock.json | 1438 ++++++++++++++++++++++++++++++- showcase_nuxt/package.json | 1 + 5 files changed, 1442 insertions(+), 22 deletions(-) create mode 100644 showcase_nuxt/app.config.ts diff --git a/showcase_nuxt/app.config.ts b/showcase_nuxt/app.config.ts new file mode 100644 index 000000000..d46d1f55b --- /dev/null +++ b/showcase_nuxt/app.config.ts @@ -0,0 +1,6 @@ +export default defineAppConfig({ + ui: { + primary: 'green', + gray: 'neutral', + } +}) \ No newline at end of file diff --git a/showcase_nuxt/app.vue b/showcase_nuxt/app.vue index a495b7573..0334834a7 100644 --- a/showcase_nuxt/app.vue +++ b/showcase_nuxt/app.vue @@ -1,5 +1,15 @@ diff --git a/showcase_nuxt/nuxt.config.ts b/showcase_nuxt/nuxt.config.ts index 8851e7746..0f3b8879d 100644 --- a/showcase_nuxt/nuxt.config.ts +++ b/showcase_nuxt/nuxt.config.ts @@ -1,4 +1,5 @@ // https://nuxt.com/docs/api/configuration/nuxt-config export default defineNuxtConfig({ - devtools: { enabled: true } -}) + devtools: { enabled: true }, + modules: ["@nuxt/ui"] +}) \ No newline at end of file diff --git a/showcase_nuxt/package-lock.json b/showcase_nuxt/package-lock.json index c76fedd01..ac9a0126b 100644 --- a/showcase_nuxt/package-lock.json +++ b/showcase_nuxt/package-lock.json @@ -7,11 +7,23 @@ "name": "nuxt-app", "hasInstallScript": true, "dependencies": { + "@nuxt/ui": "^2.16.0", "nuxt": "^3.11.2", "vue": "^3.4.27", "vue-router": "^4.3.2" } }, + "node_modules/@alloc/quick-lru": { + "version": "5.2.0", + "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz", + "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==", + "engines": { + "node": ">=10" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/@ampproject/remapping": { "version": "2.3.0", "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz", @@ -28,7 +40,6 @@ "version": "0.1.1", 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a/showcase_nuxt/package.json +++ b/showcase_nuxt/package.json @@ -10,6 +10,7 @@ "postinstall": "nuxt prepare" }, "dependencies": { + "@nuxt/ui": "^2.16.0", "nuxt": "^3.11.2", "vue": "^3.4.27", "vue-router": "^4.3.2" From bfcb3800e3ed11cd7e17d5c66f686d1473066d22 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:40 -0400 Subject: [PATCH 15/74] Basic nuxt version --- showcase_nuxt/app.vue | 23 +- showcase_nuxt/components/WorkflowList.vue | 26 + showcase_nuxt/nuxt.config.ts | 6 +- showcase_nuxt/package-lock.json | 1923 ++++- showcase_nuxt/package.json | 1 + showcase_nuxt/pages/index.vue | 12 + showcase_nuxt/pages/workflow/[id].vue | 15 + showcase_nuxt/public/workflow_manifest.json | 1 + showcase_nuxt/yarn.lock | 7135 +++++++++++++++++++ 9 files changed, 9087 insertions(+), 55 deletions(-) create mode 100644 showcase_nuxt/components/WorkflowList.vue create mode 100644 showcase_nuxt/pages/index.vue create mode 100644 showcase_nuxt/pages/workflow/[id].vue create mode 120000 showcase_nuxt/public/workflow_manifest.json create mode 100644 showcase_nuxt/yarn.lock diff --git a/showcase_nuxt/app.vue b/showcase_nuxt/app.vue index 0334834a7..c03fc8328 100644 --- a/showcase_nuxt/app.vue +++ b/showcase_nuxt/app.vue @@ -1,15 +1,14 @@ diff --git a/showcase_nuxt/components/WorkflowList.vue b/showcase_nuxt/components/WorkflowList.vue new file mode 100644 index 000000000..84e9321c2 --- /dev/null +++ b/showcase_nuxt/components/WorkflowList.vue @@ -0,0 +1,26 @@ + + + + + \ No newline at end of file diff --git a/showcase_nuxt/nuxt.config.ts b/showcase_nuxt/nuxt.config.ts index 0f3b8879d..b10a09dd4 100644 --- a/showcase_nuxt/nuxt.config.ts +++ b/showcase_nuxt/nuxt.config.ts @@ -1,5 +1,9 @@ +import { defineNuxtConfig } from 'nuxt/config'; +import path from 'path' +import { promises as fs } from 'fs' + // https://nuxt.com/docs/api/configuration/nuxt-config export default defineNuxtConfig({ devtools: { enabled: true }, - modules: ["@nuxt/ui"] + modules: ["@nuxt/ui", "@nuxt/content"], }) \ No newline at end of file diff --git a/showcase_nuxt/package-lock.json b/showcase_nuxt/package-lock.json index ac9a0126b..4fa05ea31 100644 --- a/showcase_nuxt/package-lock.json +++ b/showcase_nuxt/package-lock.json @@ -7,6 +7,7 @@ "name": "nuxt-app", "hasInstallScript": true, "dependencies": { + "@nuxt/content": "^2.12.1", "@nuxt/ui": "^2.16.0", "nuxt": "^3.11.2", "vue": "^3.4.27", @@ -1721,6 +1722,40 @@ "node": "^16.13.0 || >=18.0.0" } }, + "node_modules/@nuxt/content": { + "version": "2.12.1", + "resolved": "https://registry.npmjs.org/@nuxt/content/-/content-2.12.1.tgz", + "integrity": "sha512-xW4xjyYm6zqglb17Tu0J+rpKUV1PF9zp6SLu1lopylFnerdyImtce84206HT6Zd/DJgivKtoW4dyyJn0ZaSqCQ==", + "dependencies": { + "@nuxt/kit": "^3.10.3", + "@nuxtjs/mdc": "^0.6.1", + "@vueuse/core": "^10.9.0", + "@vueuse/head": "^2.0.0", + "@vueuse/nuxt": "^10.9.0", + "consola": "^3.2.3", + "defu": "^6.1.4", + "destr": "^2.0.3", + "json5": "^2.2.3", + "knitwork": "^1.0.0", + "listhen": "^1.7.2", + "mdast-util-to-string": "^4.0.0", + "mdurl": "^2.0.0", + "micromark": "^4.0.0", + "micromark-util-sanitize-uri": "^2.0.0", + "micromark-util-types": "^2.0.0", + "minisearch": "^6.3.0", + "ohash": "^1.1.3", + "pathe": "^1.1.2", + "scule": "^1.3.0", + "shiki": "^1.1.7", + "slugify": "^1.6.6", + "socket.io-client": "^4.7.4", + "ufo": "^1.4.0", + "unist-util-stringify-position": "^4.0.0", + "unstorage": "^1.10.1", + "ws": "^8.16.0" + } + }, "node_modules/@nuxt/devalue": { "version": "2.0.2", "resolved": "https://registry.npmjs.org/@nuxt/devalue/-/devalue-2.0.2.tgz", @@ -1984,6 +2019,48 @@ "semver": "^7.6.0" } }, + "node_modules/@nuxtjs/mdc": { + "version": "0.6.1", + "resolved": "https://registry.npmjs.org/@nuxtjs/mdc/-/mdc-0.6.1.tgz", + "integrity": "sha512-zS5QK7DZ/SBrjqQX1DOy7GnxKy+wbj2+LvooefOWmQqHfLTAqJLVIjuv/BmKnQWiRCq19+uysys3iY42EoY5/A==", + "dependencies": { + "@nuxt/kit": "^3.10.3", + "@shikijs/transformers": "^1.1.7", + "@types/hast": "^3.0.4", + "@types/mdast": 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"3.23.8" + resolved "https://registry.yarnpkg.com/zod/-/zod-3.23.8.tgz#e37b957b5d52079769fb8097099b592f0ef4067d" + integrity sha512-XBx9AXhXktjUqnepgTiE5flcKIYWi/rme0Eaj+5Y0lftuGBq+jyRu/md4WnuxqgP1ubdpNCsYEYPxrzVHD8d6g== + +zwitch@^2.0.0, zwitch@^2.0.4: + version "2.0.4" + resolved "https://registry.yarnpkg.com/zwitch/-/zwitch-2.0.4.tgz#c827d4b0acb76fc3e685a4c6ec2902d51070e9d7" + integrity sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A== From fe5a861fd8d087962c15f3bef02640f31fe654a3 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:40 -0400 Subject: [PATCH 17/74] Regnerate workflow_manifest. Note: No README.md at ./workflows/VGP-assembly-v2/Assembly-decontamination-VGP9/README.md No README.md at ./workflows/VGP-assembly-v2/Mitogenome-assembly-VGP0/README.md No CHANGELOG.md at ./workflows/VGP-assembly-v2/Mitogenome-assembly-VGP0/CHANGELOG.md Check organization of vgp-assembly-v2 --- workflow_manifest.json | 48299 ++++++++++++++++++++++++++------------- 1 file changed, 32923 insertions(+), 15376 deletions(-) diff --git a/workflow_manifest.json b/workflow_manifest.json index 26604517b..96f5a8359 100644 --- a/workflow_manifest.json +++ b/workflow_manifest.json @@ -38,7 +38,7 @@ ], "format-version": "0.1", "license": "MIT", - "release": "0.1.13", + "release": "0.1.14", "name": "Parallel Accession Download", "steps": { "0": { @@ -70,7 +70,7 @@ }, "1": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2", "errors": null, "id": 1, "input_connections": { @@ -104,15 +104,15 @@ "output_name": "list_output_txt" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2", "tool_shed_repository": { - "changeset_revision": "baabc30154cd", + "changeset_revision": "2dae863c8f42", "name": "split_file_to_collection", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"split_parms\": {\"select_ftype\": \"txt\", \"__current_case__\": 5, \"input\": {\"__class__\": \"ConnectedValue\"}, \"select_mode\": {\"mode\": \"chunk\", \"__current_case__\": 0, \"chunksize\": \"1\"}, \"newfilenames\": \"split_file\", \"select_allocate\": {\"allocate\": \"byrow\", \"__current_case__\": 2}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "0.5.1", + "tool_version": "0.5.2", "type": "tool", "uuid": "f8d776ff-e1ba-4bde-9b4b-392d825fd2b7", "when": null, @@ -120,7 +120,7 @@ }, "2": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.1+galaxy0", "errors": null, "id": 2, "input_connections": { @@ -181,15 +181,15 @@ "output_name": "output_collection_other" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.1+galaxy0", "tool_shed_repository": { - "changeset_revision": "f8054ea1c365", + "changeset_revision": "516a54ddf218", "name": "sra_tools", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"adv\": {\"seq_defline\": \"@$sn/$ri\", \"minlen\": null, \"split\": \"--split-3\", \"skip_technical\": true}, \"input\": {\"input_select\": \"file_list\", \"__current_case__\": 2, \"file_list\": {\"__class__\": \"ConnectedValue\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "3.1.0+galaxy1", + "tool_version": "3.1.1+galaxy0", "type": "tool", "uuid": "4d328e7b-df7d-4d3e-a60f-1ea12925f317", "when": null, @@ -295,10 +295,10 @@ "version": 10 }, "readme": "# Parallel Accession Download\n\nDownloads fastq files for sequencing run accessions provided in a text file\nusing fasterq-dump. Creates one job per listed run accession, and is therefore\nmuch faster and more robust to errors when many accessions need to be\ndownloaded.\n", - "changelog": "# Changelog\n\n## [0.1.13] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.1.12] 2024-04-16\n\n### Changed\n\n- Remove unnecessary param_value_from_file step and directly pass file with identifiers to fasterqdump\n\n## [0.1.11] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.1.10] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.1.9] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1.8] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.1.7] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n\n## [0.1.6] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3`\n\n## [0.1.5] 2023-09-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1`\n\n## [0.1.4] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0`\n\n## [0.1.3] 2022-02-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1`\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.1] - 2021-06-23\n\n### Added\n\n- Initial version of Parallel Accession Download workflow.\n" + "changelog": "# Changelog\n\n## [0.1.14] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.1+galaxy0`\n\n## [0.1.13] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.1.12] 2024-04-16\n\n### Changed\n\n- Remove unnecessary param_value_from_file step and directly pass file with identifiers to fasterqdump\n\n## [0.1.11] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.1.10] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.1.9] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1.8] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.1.7] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n\n## [0.1.6] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3`\n\n## [0.1.5] 2023-09-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy1`\n\n## [0.1.4] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy0`\n\n## [0.1.3] 2022-02-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/2.11.0+galaxy1`\n\n## [0.1.2] 2021-12-13\n\n### Added\n- Added GitHub Actions workflow. No functional changes.\n\n## [0.1.1] 2021-07-23\n\n### Added\n\nAdded RO-Crate metadata file. No functional changes.\n\n## [0.1] - 2021-06-23\n\n### Added\n\n- Initial version of Parallel Accession Download workflow.\n" } ], - "path": "./workflows/data-fetching" + "path": "./workflows/data-fetching/parallel-accession-download" }, { "version": 1.2, @@ -346,7 +346,7 @@ } ], "format-version": "0.1", - "release": "0.5", + "release": "0.7", "license": "MIT", "name": "sra_manifest_to_concatenated_fastqs_parallel", "steps": { @@ -647,7 +647,7 @@ }, "8": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2", "errors": null, "id": 8, "input_connections": { @@ -681,15 +681,15 @@ "output_name": "list_output_tab" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2", "tool_shed_repository": { - "changeset_revision": "baabc30154cd", + "changeset_revision": "2dae863c8f42", "name": "split_file_to_collection", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"split_parms\": {\"select_ftype\": \"tabular\", \"__current_case__\": 0, \"input\": {\"__class__\": \"ConnectedValue\"}, \"top\": \"1\", \"split_by\": {\"select_split_by\": \"col\", \"__current_case__\": 0, \"id_col\": \"1\", \"match_regex\": \"(.*)\", \"sub_regex\": \"\\\\1\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "0.5.1", + "tool_version": "0.5.2", "type": "tool", "uuid": "4a1ad675-4291-4001-a748-d009299f9d40", "when": null, @@ -697,7 +697,7 @@ }, "9": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.1+galaxy0", "errors": null, "id": 9, "input_connections": { @@ -758,15 +758,15 @@ "output_name": "output_collection_other" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.1+galaxy0", "tool_shed_repository": { - "changeset_revision": "f8054ea1c365", + "changeset_revision": "516a54ddf218", "name": "sra_tools", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"adv\": {\"seq_defline\": \"@$sn/$ri\", \"minlen\": null, \"split\": \"--split-3\", \"skip_technical\": true}, \"input\": {\"input_select\": \"file_list\", \"__current_case__\": 2, \"file_list\": {\"__class__\": \"ConnectedValue\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "3.1.0+galaxy1", + "tool_version": "3.1.1+galaxy0", "type": "tool", "uuid": "fa409017-1eea-4426-83f6-22a10b9f762c", "when": null, @@ -948,7 +948,7 @@ }, "14": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2", + "content_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.3", "errors": null, "id": 14, "input_connections": { @@ -984,15 +984,15 @@ "output_name": "paired_output" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.3", "tool_shed_repository": { - "changeset_revision": "5b2cc63d7a21", + "changeset_revision": "5b1b635232ed", "name": "concatenate_multiple_datasets", "owner": "artbio", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"__input_ext\": \"fastqsanger.gz\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"dataset_names\": false, \"global_condition\": {\"input_type\": \"paired_collection\", \"__current_case__\": 1, \"inputs\": {\"__class__\": \"ConnectedValue\"}, \"paired_cat_type\": \"by_strand\"}, \"headers\": \"0\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "1.4.2", + "tool_version": "1.4.3", "type": "tool", "uuid": "37b6fecb-1c87-4c41-8598-95d43b418ee0", "when": null, @@ -1006,7 +1006,7 @@ }, "15": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2", + "content_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.3", "errors": null, "id": 15, "input_connections": { @@ -1042,15 +1042,15 @@ "output_name": "out_file1" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.3", "tool_shed_repository": { - "changeset_revision": "5b2cc63d7a21", + "changeset_revision": "5b1b635232ed", "name": "concatenate_multiple_datasets", "owner": "artbio", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"__input_ext\": \"fastqsanger.gz\", \"chromInfo\": \"/opt/galaxy/tool-data/shared/ucsc/chrom/?.len\", \"dataset_names\": false, \"global_condition\": {\"input_type\": \"singles\", \"__current_case__\": 0, \"inputs\": {\"__class__\": \"ConnectedValue\"}}, \"headers\": \"0\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "1.4.2", + "tool_version": "1.4.3", "type": "tool", "uuid": "49a70885-3374-4680-bbd2-ad57b8be543d", "when": null, @@ -1068,7 +1068,7 @@ "version": 3 }, "readme": "# SRA manifest to concatenated fastqs\n\nThis workflow takes as input a SRA manifest from SRA Run Selector (or a tabular with a header line), downloads all sequencing run data from the SRA and arranges it into per-sample fastq or pairs of fastq datasets.\n\nIt will work out the relationship between runs and samples from the user-indicated run and sample columns in the input and will concatenate sequencing run data as needed to obtain per-sample datasets.\n\n## Input dataset\n\n- The workflow needs a single tabular input dataset, which is supposed to list SRA run identifiers in one column and sample names in another, and which needs to have a header line.\n- SRA manifests obtained via the SRA Run Selector and turned into tabular format represent valid input.\n\n## Input values\n\n- Column number with SRA run ID\n\n For manifests obtained through the SRA Run Selector this is column 1\n\n- Column number with sample names\n\n The number of the column that should be used to assign sequencing runs to samples\n The names in the column will also serve as the labels of datasets in the output collection.\n For manifests obtained through the SRA Run Selector suitable columns might be number 6 (BioSample), 16 (Experiment) or 36 (Sample Name).\n\n## Processing\n\n- The workflow downloads sequencing run data in fastq format with fasterqdump (one job per SRA run ID).\n- Run data gets concatenated if it comes from the same sample.\n\n## Outputs\n\n- There are 2 outputs, one with paired-end datasets, one with single-read datasets.\n\n## Limitations\n\n- Special characters in sample names (anything that is not an English alphabet character, digit, underscore, dash, space, dot or comma (`[a-zA-Z0-9_\\- \\.,]`) will be converted to dashes (`-`).\n", - "changelog": "# Changelog\n\n## [0.5] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.3] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.2.4] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.2.3] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n\n## [0.2.2] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.2.1] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.1` was updated to `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2`\n\n## [0.1] 2023-10-23\nFirst release.\n" + "changelog": "# Changelog\n\n## [0.7] 2024-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2` was updated to `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.3`\n\n## [0.6] 2024-06-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.1+galaxy0`\n\n## [0.5] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy1`\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.1.0+galaxy0`\n\n## [0.3] 2024-03-11\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.10+galaxy0`\n\n## [0.2.4] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.2.3] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n\n## [0.2.2] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.2.1] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy1`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.5+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/sra_tools/fasterq_dump/3.0.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.1` was updated to `toolshed.g2.bx.psu.edu/repos/artbio/concatenate_multiple_datasets/cat_multi_datasets/1.4.2`\n\n## [0.1] 2023-10-23\nFirst release.\n" } ], "path": "./workflows/data-fetching/sra-manifest-to-concatenated-fastqs" @@ -1093,6 +1093,7 @@ "definition": { "a_galaxy_workflow": "true", "annotation": "This workflow takes as input a list of single-reads fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously as well as normalized coverage (per million mapped reads) on uniquely mapped reads. The counts are reprocessed to be similar to HTSeq-count output. FPKM are computed with cufflinks and/or with StringTie. The unstranded normalized coverage is computed with bedtools.", + "comments": [], "creator": [ { "class": "Person", @@ -1103,7 +1104,7 @@ "format-version": "0.1", "license": "MIT", "name": "RNAseq_SR", - "release": "0.6", + "release": "0.8", "steps": { "0": { "annotation": "Should be a list of single-read RNA-seq fastqs", @@ -1128,7 +1129,7 @@ "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", "tool_version": null, "type": "data_collection_input", - "uuid": "633ddb66-8a2b-4822-b894-2e947bf6607b", + "uuid": "2fee2555-0a2f-4758-9011-3667db23f962", "when": null, "workflow_outputs": [] }, @@ -1155,7 +1156,7 @@ "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "0179b655-f7e2-4b8b-b8b1-f875d0d8039f", + "uuid": "124c7578-bdaa-445b-a756-326077f2567d", "when": null, "workflow_outputs": [] }, @@ -1182,7 +1183,7 @@ "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "ff4a9932-6ed0-436f-a63c-d6fbe2a582a3", + "uuid": "39f1c435-1e7c-48d6-9149-37671b7b07da", "when": null, "workflow_outputs": [] }, @@ -1209,7 +1210,7 @@ "tool_state": "{\"optional\": false, \"tag\": \"\"}", "tool_version": null, "type": "data_input", - "uuid": "c91756d4-f7f1-4dcc-97f6-da4c96a53c94", + "uuid": "b32d0b73-c827-46f9-8279-697487cd3c4c", "when": null, "workflow_outputs": [] }, @@ -1236,7 +1237,7 @@ "tool_state": "{\"restrictions\": [\"stranded - forward\", \"stranded - reverse\", \"unstranded\"], \"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "fd2c51fd-58b3-43b5-b8ce-a919f5325cb7", + "uuid": "02b7890c-1d0d-493e-9943-3016f6594b46", "when": null, "workflow_outputs": [] }, @@ -1263,7 +1264,7 @@ "tool_state": "{\"parameter_type\": \"boolean\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "fbe4c961-6b62-46b7-a329-163b9cda4979", + "uuid": "a80fd45c-4164-4b94-847c-dcef5441b92a", "when": null, "workflow_outputs": [] }, @@ -1290,7 +1291,7 @@ "tool_state": "{\"optional\": true, \"tag\": \"\"}", "tool_version": null, "type": "data_input", - "uuid": "cc52d397-17a9-4c38-85f6-a7c0b8f21985", + "uuid": "54a833b6-bb4a-48c2-b8d7-4c8bb0172ce7", "when": null, "workflow_outputs": [] }, @@ -1317,13 +1318,13 @@ "tool_state": "{\"parameter_type\": \"boolean\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "9619cb07-6835-4f79-8f49-ce59e343736d", + "uuid": "05bdc4bb-4988-42e6-b281-cbb826b96c7b", "when": null, "workflow_outputs": [] }, "8": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1", + "content_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0", "errors": null, "id": 8, "input_connections": { @@ -1336,7 +1337,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Cutadapt", + "name": "library" + } + ], "label": "Cutadapt (remove adapter + bad quality bases)", "name": "Cutadapt", "outputs": [ @@ -1370,17 +1376,17 @@ "output_name": "report" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0", "tool_shed_repository": { - "changeset_revision": "64172f1c1202", + "changeset_revision": "aa784cb3810d", "name": "cutadapt", "owner": "lparsons", "tool_shed": "toolshed.g2.bx.psu.edu" }, - "tool_state": "{\"__job_resource\": {\"__current_case__\": 0, \"__job_resource__select\": \"no\"}, \"adapter_options\": {\"action\": \"trim\", \"error_rate\": \"0.1\", \"no_indels\": false, \"times\": \"1\", \"overlap\": \"3\", \"match_read_wildcards\": false, \"no_match_adapter_wildcards\": true, \"revcomp\": false}, \"filter_options\": {\"discard_trimmed\": false, \"discard_untrimmed\": false, \"minimum_length\": \"15\", \"maximum_length\": null, \"max_n\": null, \"pair_filter\": \"any\", \"max_expected_errors\": null, \"max_average_error_rate\": null, \"discard_cassava\": false}, \"library\": {\"type\": \"single\", \"__current_case__\": 0, \"input_1\": {\"__class__\": \"ConnectedValue\"}, \"r1\": {\"adapters\": [{\"__index__\": 0, \"adapter_source\": {\"adapter_source_list\": \"user\", \"__current_case__\": 0, \"adapter_name\": \"Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC\", \"adapter\": {\"__class__\": \"ConnectedValue\"}}, \"single_noindels\": false}], \"front_adapters\": [], \"anywhere_adapters\": []}}, \"output_selector\": [\"report\"], \"read_mod_options\": {\"cut\": \"0\", \"quality_cutoff\": \"30\", \"nextseq_trim\": \"0\", \"trim_n\": false, \"poly_a\": false, \"strip_suffix\": \"\", \"shorten_options\": {\"shorten_values\": \"False\", \"__current_case__\": 1}, \"length_tag\": \"\", \"rename\": \"\", \"zero_cap\": false}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "4.6+galaxy1", + "tool_state": "{\"__job_resource\": {\"__current_case__\": 0, \"__job_resource__select\": \"no\"}, \"adapter_options\": {\"action\": \"trim\", \"error_rate\": \"0.1\", \"no_indels\": false, \"times\": \"1\", \"overlap\": \"3\", \"match_read_wildcards\": false, \"no_match_adapter_wildcards\": true, \"revcomp\": false}, \"filter_options\": {\"discard_trimmed\": false, \"discard_untrimmed\": false, \"minimum_length\": \"15\", \"minimum_length2\": null, \"maximum_length\": null, \"maximum_length2\": null, \"max_n\": null, \"max_expected_errors\": null, \"max_average_error_rate\": null, \"discard_casava\": false, \"pair_filter\": \"any\"}, \"library\": {\"type\": \"single\", \"__current_case__\": 0, \"input_1\": {\"__class__\": \"ConnectedValue\"}, \"r1\": {\"adapters\": [{\"__index__\": 0, \"adapter_source\": {\"adapter_source_list\": \"user\", \"__current_case__\": 0, \"adapter_name\": \"Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC\", \"adapter\": {\"__class__\": \"ConnectedValue\"}}, \"single_noindels\": false}], \"front_adapters\": [], \"anywhere_adapters\": []}}, \"other_trimming_options\": {\"cut\": \"0\", \"cut2\": \"0\", \"quality_cutoff\": \"30\", \"quality_cutoff2\": \"\", \"nextseq_trim\": \"0\", \"trim_n\": false, \"poly_a\": false, \"shorten_options\": {\"shorten_values\": \"False\", \"__current_case__\": 1}, \"shorten_options_r2\": {\"shorten_values_r2\": \"False\", \"__current_case__\": 1}}, \"output_selector\": [\"report\"], \"read_mod_options\": {\"strip_suffix\": \"\", \"length_tag\": \"\", \"rename\": \"\", \"zero_cap\": false}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "4.9+galaxy0", "type": "tool", - "uuid": "7f7ca59a-09db-491f-b185-1caa51e9d2aa", + "uuid": "4d39b70d-c852-4c42-9e0d-f3641d632543", "when": null, "workflow_outputs": [] }, @@ -1425,7 +1431,7 @@ "tool_state": "{\"components\": [{\"__index__\": 0, \"param_type\": {\"select_param_type\": \"text\", \"__current_case__\": 0, \"component_value\": {\"__class__\": \"ConnectedValue\"}}}], \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.1.1", "type": "tool", - "uuid": "19dceb12-2f4e-46e6-bb2b-2f718dc4438c", + "uuid": "87e88a77-d412-4ed0-8bf1-9c23406d4a22", "when": null, "workflow_outputs": [] }, @@ -1440,7 +1446,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Map parameter value", + "name": "input_param_type" + } + ], "label": "awk command from strand", "name": "Map parameter value", "outputs": [ @@ -1470,7 +1481,7 @@ "tool_state": "{\"input_param_type\": {\"type\": \"text\", \"__current_case__\": 0, \"input_param\": {\"__class__\": \"ConnectedValue\"}, \"mappings\": [{\"__index__\": 0, \"from\": \"stranded - forward\", \"to\": \"NR>4{print $1\\\"\\\\t\\\"$3}\"}, {\"__index__\": 1, \"from\": \"stranded - reverse\", \"to\": \"NR>4{print $1\\\"\\\\t\\\"$4}\"}, {\"__index__\": 2, \"from\": \"unstranded\", \"to\": \"NR>4{print $1\\\"\\\\t\\\"$2}\"}]}, \"output_param_type\": \"text\", \"unmapped\": {\"on_unmapped\": \"fail\", \"__current_case__\": 1}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.2.0", "type": "tool", - "uuid": "98da5820-124e-4fe5-8e6c-efc602e700a8", + "uuid": "dc27749f-07ad-454d-8b8d-15612b31870c", "when": null, "workflow_outputs": [] }, @@ -1485,7 +1496,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Map parameter value", + "name": "input_param_type" + } + ], "label": "Get cufflinks strandess parameter", "name": "Map parameter value", "outputs": [ @@ -1515,7 +1531,7 @@ "tool_state": "{\"input_param_type\": {\"type\": \"text\", \"__current_case__\": 0, \"input_param\": {\"__class__\": \"ConnectedValue\"}, \"mappings\": [{\"__index__\": 0, \"from\": \"stranded - forward\", \"to\": \"fr-secondstrand\"}, {\"__index__\": 1, \"from\": \"stranded - reverse\", \"to\": \"fr-firststrand\"}, {\"__index__\": 2, \"from\": \"unstranded\", \"to\": \"fr-unstranded\"}]}, \"output_param_type\": \"text\", \"unmapped\": {\"on_unmapped\": \"fail\", \"__current_case__\": 1}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.2.0", "type": "tool", - "uuid": "e49965f9-2351-4c2b-a1ad-fdaf543dfe34", + "uuid": "d2d1af99-7b7b-4ec1-b2dc-5997fd3d702b", "when": null, "workflow_outputs": [] }, @@ -1530,7 +1546,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Map parameter value", + "name": "input_param_type" + } + ], "label": "Get Stringtie strandedness parameter", "name": "Map parameter value", "outputs": [ @@ -1560,7 +1581,7 @@ "tool_state": "{\"input_param_type\": {\"type\": \"text\", \"__current_case__\": 0, \"input_param\": {\"__class__\": \"ConnectedValue\"}, \"mappings\": [{\"__index__\": 0, \"from\": \"stranded - forward\", \"to\": \"--fr\"}, {\"__index__\": 1, \"from\": \"stranded - reverse\", \"to\": \"--rf\"}, {\"__index__\": 2, \"from\": \"unstranded\", \"to\": \"\"}]}, \"output_param_type\": \"text\", \"unmapped\": {\"on_unmapped\": \"fail\", \"__current_case__\": 1}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.2.0", "type": "tool", - 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"uuid": "b0cd7bb3-88dc-4e5c-b1c7-78929397c245", + "uuid": "8a26e154-29c0-426a-b0aa-215192f03596", "when": null, "workflow_outputs": [ { "label": "output_log", "output_name": "output_log", - "uuid": "9fdf6357-295b-41cd-98ed-eb8145c45354" + "uuid": "4cb18b88-63ab-4881-afec-d6569dbd3533" }, { "label": "reads_per_gene from STAR", "output_name": "reads_per_gene", - "uuid": "dd816276-a80e-4f6d-b5a1-5468b2348130" + "uuid": "056b9f4b-5208-4885-97e8-474f417537ee" }, { "label": "mapped-reads", "output_name": "mapped_reads", - "uuid": "57535a90-ff13-4ed3-9fc8-10875b4baae2" + "uuid": "94cb795a-4fa6-4323-af7d-99c346e83435" } ] }, @@ -1738,18 +1764,18 @@ "tool_state": "{\"comment\": \"\", \"export\": true, \"flat\": false, \"results\": [{\"__index__\": 0, \"software_cond\": {\"software\": \"cutadapt\", \"__current_case__\": 5, \"input\": {\"__class__\": \"ConnectedValue\"}}}, {\"__index__\": 1, \"software_cond\": {\"software\": \"star\", \"__current_case__\": 28, \"output\": [{\"__index__\": 0, \"type\": {\"type\": \"log\", \"__current_case__\": 0, \"input\": {\"__class__\": \"ConnectedValue\"}}}, {\"__index__\": 1, \"type\": {\"type\": \"genecounts\", \"__current_case__\": 1, \"input\": {\"__class__\": \"ConnectedValue\"}}}]}}], \"saveLog\": false, \"title\": \"\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.11+galaxy1", "type": "tool", - "uuid": "a4e1b954-a475-4a3c-b84a-5dc44947e1c8", + "uuid": "ba4d9ac2-f8b6-43bc-bc5f-e542c44441cd", "when": null, "workflow_outputs": [ - { - "label": "MultiQC on input dataset(s): Stats", - "output_name": "stats", - "uuid": "4a60ab44-4c20-40e2-8896-778ddf7c6b93" - }, { "label": "MultiQC webpage", "output_name": "html_report", - "uuid": "bbdeacff-6ca5-4259-940b-3b7bd033f41c" + "uuid": "24fe0860-563a-4938-b51d-6fdf10ec4175" + }, + { + "label": "MultiQC on input dataset(s): Stats", + "output_name": "stats", + "uuid": "4036a639-8e11-4de6-873f-a60183b789df" } ] }, @@ -1779,6 +1805,7 @@ "subworkflow": { "a_galaxy_workflow": "true", "annotation": "", + "comments": [], "creator": [ { "class": "Person", @@ -1791,14 +1818,14 @@ "name": "Get Uniquely mapped unstranded coverage", "steps": { "0": { - "annotation": "STAR mapping results (BAM)", + "annotation": "", "content_id": null, "errors": null, "id": 0, "input_connections": {}, "inputs": [ { - "description": "STAR mapping results (BAM)", + "description": "", "name": "STAR BAM" } ], @@ -1813,19 +1840,19 @@ "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", "tool_version": null, "type": "data_collection_input", - "uuid": "d6f1f09b-d56f-43f0-9c09-c7a5a92bb21c", + "uuid": "8688442b-cd63-46b3-8f36-a02e11091e4c", "when": null, "workflow_outputs": [] }, "1": { - "annotation": "STAR log", + "annotation": "", "content_id": null, "errors": null, "id": 1, "input_connections": {}, "inputs": [ { - "description": "STAR log", + "description": "", "name": "STAR log" } ], @@ -1840,13 +1867,13 @@ "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", "tool_version": null, "type": "data_collection_input", - "uuid": "4d4e4f39-3b7b-4c19-bd8a-08c1236b3052", + "uuid": "e97ce94f-3ccb-4abf-ab75-8b76c7cb1762", "when": null, "workflow_outputs": [] }, "2": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1", + "content_id": "toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy2", "errors": null, "id": 2, "input_connections": { @@ -1884,23 +1911,23 @@ "output_name": "out_file2" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy2", "tool_shed_repository": { - "changeset_revision": "108db6635177", + "changeset_revision": "993b19f20c76", "name": "bamtools_filter", "owner": "devteam", "tool_shed": "toolshed.g2.bx.psu.edu" }, - "tool_state": "{\"conditions\": [{\"__index__\": 0, \"filters\": [{\"__index__\": 0, \"bam_property\": {\"bam_property_selector\": \"tag\", \"__current_case__\": 21, \"bam_property_value\": \"NH=1\"}}]}], \"input_bam\": {\"__class__\": \"ConnectedValue\"}, \"rule_configuration\": {\"rules_selector\": false, \"__current_case__\": 0}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.5.2+galaxy1", + "tool_state": "{\"conditions\": [{\"__index__\": 0, \"filters\": [{\"__index__\": 0, \"bam_property\": {\"bam_property_selector\": \"tag\", \"__current_case__\": 21, \"bam_property_value\": \"NH=1\"}}]}], \"input_bam\": {\"__class__\": \"ConnectedValue\"}, \"rule_configuration\": {\"rules_selector\": \"false\", \"__current_case__\": 0}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2.5.2+galaxy2", "type": "tool", - "uuid": "7cc2377c-657b-4d9d-919b-1a68fd3eceec", + "uuid": "8b2522f8-237b-4bb0-8429-94c029a1c9d8", "when": null, "workflow_outputs": [] }, "3": { - "annotation": "This step get 1 / millions of uniquely mapped reads", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0", + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1", "errors": null, "id": 3, "input_connections": { @@ -1929,17 +1956,17 @@ "output_name": "outfile" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1", "tool_shed_repository": { - "changeset_revision": "12615d397df7", + "changeset_revision": "fbf99087e067", "name": "text_processing", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"code\": \"$0~\\\"Uniquely mapped reads number\\\"{print 1000000/$NF}\", \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "9.3+galaxy0", + "tool_version": "9.3+galaxy1", "type": "tool", - "uuid": "122cd0c2-4484-496c-b589-93b4553d1442", + "uuid": "12b386f6-5254-4389-9400-4fe5381b3336", "when": null, "workflow_outputs": [] }, @@ -1978,13 +2005,13 @@ "tool_state": "{\"input1\": {\"__class__\": \"ConnectedValue\"}, \"param_type\": \"float\", \"remove_newlines\": true, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.1.0", "type": "tool", - "uuid": "ae839aba-23c4-4633-9ffd-08c6becbb9e8", + "uuid": "2c5c3ff1-a96f-4002-937c-d0560c1b190f", "when": null, "workflow_outputs": [] }, "5": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.30.0", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.31.1", "errors": null, "id": 5, "input_connections": { @@ -1997,7 +2024,16 @@ "output_name": "float_param" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool bedtools Genome Coverage", + "name": "input_type" + }, + { + "description": "runtime parameter for tool bedtools Genome Coverage", + "name": "report" + } + ], "label": "Scaled Coverage both strands combined", "name": "bedtools Genome Coverage", "outputs": [ @@ -2017,17 +2053,17 @@ "output_name": "output" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.30.0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.31.1", "tool_shed_repository": { - "changeset_revision": "a1a923cd89e8", + "changeset_revision": "64e2edfe7a2c", "name": "bedtools", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"d\": false, \"dz\": false, \"five\": false, \"input_type\": {\"input_type_select\": \"bam\", \"__current_case__\": 1, \"input\": {\"__class__\": \"ConnectedValue\"}}, \"report\": {\"report_select\": \"bg\", \"__current_case__\": 0, \"zero_regions\": false, \"scale\": {\"__class__\": \"ConnectedValue\"}}, \"split\": true, \"strand\": \"\", \"three\": false, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.30.0", + "tool_version": "2.31.1", "type": "tool", - "uuid": "ef9e0577-c831-4cad-8fae-67ceaf0550fa", + "uuid": "6a733bff-0f07-454f-9e07-1abd649f8ab6", "when": null, "workflow_outputs": [] }, @@ -2068,29 +2104,29 @@ "tool_state": "{\"input1\": {\"__class__\": \"ConnectedValue\"}, \"settings\": {\"settingsType\": \"preset\", \"__current_case__\": 0}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.1.1", "type": "tool", - "uuid": "1260fbcb-0521-4957-842f-d9b4fd124a1a", + "uuid": "518f3e4f-cef7-4c50-936f-661873aee1d4", "when": null, "workflow_outputs": [ { "label": "both strands coverage", "output_name": "out_file1", - "uuid": "acac3057-9854-4236-a02d-e084b4bab1e4" + "uuid": "69f8c8e8-85d2-42c5-8b28-f7ba79dbcfa7" } ] } }, - "tags": "", - "uuid": "84f06c06-22e2-44a3-b1a9-74437ef5e4c7" + "tags": [], + "uuid": "0af80b84-9ced-41d5-8315-40dfe8c1b638" }, "tool_id": null, "type": "subworkflow", - "uuid": "9fbcf8ab-3e46-4ec6-9fc1-8b1ed61688d8", + "uuid": "093c0e8d-69f6-4bf9-9277-3e4183be1988", "when": null, "workflow_outputs": [ { "label": "both strands coverage", "output_name": "both strands coverage", - "uuid": "ed4b91ff-c2d2-4668-95c6-479e2ffc8d1e" + "uuid": "0ee924f9-48e4-406a-b7e2-dd14a8e1640f" } ] }, @@ -2125,6 +2161,7 @@ "subworkflow": { "a_galaxy_workflow": "true", "annotation": "", + "comments": [], "creator": [ { "class": "Person", @@ -2159,25 +2196,25 @@ "tool_state": "{\"restrictions\": [\"stranded - forward\", \"stranded - reverse\", \"unstranded\"], \"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "630bd9ab-da3a-4b98-a073-0c2e12af195a", + "uuid": "1865e89f-6f75-4bef-a34f-65c44f68eb83", "when": null, "workflow_outputs": [ { "label": null, "output_name": "output", - "uuid": "3e59583d-a7e6-4ba1-9be4-a9cc48ac8c94" + "uuid": "d9eef145-06bd-44e9-b2e5-ba276897fd0f" } ] }, "1": { - "annotation": "From STAR strand 1", + "annotation": "", "content_id": null, "errors": null, "id": 1, "input_connections": {}, "inputs": [ { - "description": "From STAR strand 1", + "description": "", "name": "Bedgraph strand 1" } ], @@ -2192,7 +2229,7 @@ "tool_state": "{\"optional\": false, \"format\": [\"bedgraph\"], \"tag\": null, \"collection_type\": \"list\"}", "tool_version": null, "type": "data_collection_input", - "uuid": "fa1b2712-805a-47f7-95d7-b1d2957a36a5", + "uuid": "480154cb-4343-4ed2-b106-9c20032aca7f", "when": null, "workflow_outputs": [] }, @@ -2219,7 +2256,7 @@ "tool_state": "{\"optional\": false, \"format\": [\"bedgraph\"], \"tag\": null, \"collection_type\": \"list\"}", "tool_version": null, "type": "data_collection_input", - "uuid": "79aee01a-2ba4-42c4-802d-975f955651ee", + "uuid": "99862f93-3061-4074-bb86-486b8bbf6009", "when": null, "workflow_outputs": [] }, @@ -2234,7 +2271,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Map parameter value", + "name": "input_param_type" + } + ], "label": "Get replacement for strand1", "name": "Map parameter value", "outputs": [ @@ -2269,7 +2311,7 @@ "tool_state": "{\"input_param_type\": {\"type\": \"text\", \"__current_case__\": 0, \"input_param\": {\"__class__\": \"ConnectedValue\"}, \"mappings\": [{\"__index__\": 0, \"from\": \"stranded - forward\", \"to\": \"$1_forward\"}, {\"__index__\": 1, \"from\": \"stranded - reverse\", \"to\": \"$1_reverse\"}, {\"__index__\": 2, \"from\": \"unstranded\", \"to\": \"$1_forward\"}]}, \"output_param_type\": \"text\", \"unmapped\": {\"on_unmapped\": \"fail\", \"__current_case__\": 1}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.2.0", "type": "tool", - "uuid": "e51b1ec5-6ac7-45c2-95e3-12ab8c027ff0", + "uuid": "22cf84f4-9cc7-49aa-a568-39b8716311a5", "when": null, "workflow_outputs": [] }, @@ -2284,7 +2326,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Map parameter value", + "name": "input_param_type" + } + ], "label": "Get replacement for strand2", "name": "Map parameter value", "outputs": [ @@ -2319,7 +2366,7 @@ "tool_state": "{\"input_param_type\": {\"type\": \"text\", \"__current_case__\": 0, \"input_param\": {\"__class__\": \"ConnectedValue\"}, \"mappings\": [{\"__index__\": 0, \"from\": \"stranded - forward\", \"to\": \"$1_reverse\"}, {\"__index__\": 1, \"from\": \"stranded - reverse\", \"to\": \"$1_forward\"}, {\"__index__\": 2, \"from\": \"unstranded\", \"to\": \"$1_reverse\"}]}, \"output_param_type\": \"text\", \"unmapped\": {\"on_unmapped\": \"fail\", \"__current_case__\": 1}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.2.0", "type": "tool", - "uuid": "b7588e70-d204-4630-99e4-f554a22ee2fe", + "uuid": "d6c2ce80-2927-4a4f-beab-2afd85b899f0", "when": null, "workflow_outputs": [] }, @@ -2358,13 +2405,13 @@ "tool_state": "{\"input_collection\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "0.0.2", "type": "tool", - "uuid": "274e53f9-17f8-45aa-960a-1ef619648c7c", + "uuid": "1fd86b13-3273-4a95-9b38-657ede0cb1a5", "when": null, "workflow_outputs": [] }, "6": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", "errors": null, "id": 6, "input_connections": { @@ -2397,23 +2444,23 @@ "output_name": "outfile" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", "tool_shed_repository": { - "changeset_revision": "12615d397df7", + "changeset_revision": "fbf99087e067", "name": "text_processing", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"find_and_replace\": [{\"__index__\": 0, \"find_pattern\": \"^(.+)$\", \"replace_pattern\": {\"__class__\": \"ConnectedValue\"}, \"is_regex\": true, \"global\": true, \"caseinsensitive\": false, \"wholewords\": false, \"skip_first_line\": false, \"searchwhere\": {\"searchwhere_select\": \"line\", \"__current_case__\": 0}}], \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "9.3+galaxy0", + "tool_version": "9.3+galaxy1", "type": "tool", - "uuid": "11b98d13-5c13-464e-b223-8fab20f69f62", + "uuid": "930e865a-bafd-4f20-81fd-c008d781b7d2", "when": null, "workflow_outputs": [] }, "7": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", "errors": null, "id": 7, "input_connections": { @@ -2446,17 +2493,17 @@ "output_name": "outfile" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", "tool_shed_repository": { - "changeset_revision": "12615d397df7", + "changeset_revision": "fbf99087e067", "name": "text_processing", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"find_and_replace\": [{\"__index__\": 0, \"find_pattern\": \"^(.+)$\", \"replace_pattern\": {\"__class__\": \"ConnectedValue\"}, \"is_regex\": true, \"global\": true, \"caseinsensitive\": false, \"wholewords\": false, \"skip_first_line\": false, \"searchwhere\": {\"searchwhere_select\": \"line\", \"__current_case__\": 0}}], \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "9.3+galaxy0", + "tool_version": "9.3+galaxy1", "type": "tool", - "uuid": "4e158197-8591-4fce-b969-9002f7482634", + "uuid": "7f9c10e6-8f19-4467-9549-641668c84812", "when": null, "workflow_outputs": [] }, @@ -2475,7 +2522,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Relabel identifiers", + "name": "how" + } + ], "label": "Relabelled strand 1", "name": "Relabel identifiers", "outputs": [ @@ -2499,7 +2551,7 @@ "tool_state": "{\"how\": {\"how_select\": \"txt\", \"__current_case__\": 0, \"labels\": {\"__class__\": \"ConnectedValue\"}, \"strict\": false}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "6a3f57c0-f6d6-468f-8ac9-b6882f754eed", + "uuid": "89b5768c-6f33-403a-98ca-efcdb302e65a", "when": null, "workflow_outputs": [] }, @@ -2518,7 +2570,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Relabel identifiers", + "name": "how" + } + ], "label": "Relabelled strand 2", "name": "Relabel identifiers", "outputs": [ @@ -2542,7 +2599,7 @@ "tool_state": "{\"how\": {\"how_select\": \"txt\", \"__current_case__\": 0, \"labels\": {\"__class__\": \"ConnectedValue\"}, \"strict\": false}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "d181b9ba-0cd3-4de6-8e82-c53a97c5ae67", + "uuid": "554d85f6-7c54-44f7-a9f4-9b0d2d9737f6", "when": null, "workflow_outputs": [] }, @@ -2585,7 +2642,7 @@ "tool_state": "{\"advanced\": {\"conflict\": {\"duplicate_options\": \"keep_first\", \"__current_case__\": 3}}, \"inputs\": [{\"__index__\": 0, \"input\": {\"__class__\": \"ConnectedValue\"}}, {\"__index__\": 1, \"input\": {\"__class__\": \"ConnectedValue\"}}], \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "4b4b9d77-13fe-4b8a-a5af-e0857547521e", + "uuid": "e3c1b832-2f79-4ce4-94d2-4e6396e569e3", "when": null, "workflow_outputs": [] }, @@ -2626,29 +2683,29 @@ "tool_state": "{\"input1\": {\"__class__\": \"ConnectedValue\"}, \"settings\": {\"settingsType\": \"preset\", \"__current_case__\": 0}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.1.1", "type": "tool", - "uuid": "b69eee65-c37e-4c75-8127-b78185b130db", + "uuid": "f9b2dbd6-c547-4c2e-be60-1423e06710a4", "when": null, "workflow_outputs": [ { "label": "stranded coverage", "output_name": "out_file1", - "uuid": "dd43e657-0116-46ad-9cc9-c12fb871988c" + "uuid": "b747244f-fc40-4f20-b713-882715921a5b" } ] } }, - "tags": "", - "uuid": "2641211f-6a1c-493c-8729-3471ff4065b5" + "tags": [], + "uuid": "7bf438af-cb14-4fd2-ba15-2e86b44ed0cb" }, "tool_id": null, "type": "subworkflow", - "uuid": "cc127732-933e-420a-a5ae-24fed48e7e6a", + "uuid": "3dbdc02e-6875-495d-841a-aae50c3b5f96", "when": null, "workflow_outputs": [ { "label": "stranded coverage", "output_name": "stranded coverage", - "uuid": "245c268e-87fc-43a7-9d49-d18d9363b475" + "uuid": "7302e44f-8cce-466e-9672-3b510b55072b" } ] }, @@ -2683,7 +2740,20 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Cufflinks", + "name": "advanced_settings" + }, + { + "description": "runtime parameter for tool Cufflinks", + "name": "advanced_settings" + }, + { + "description": "runtime parameter for tool Cufflinks", + "name": "reference_annotation" + } + ], "label": "Compute FPKM with cufflinks", "name": "Cufflinks", "outputs": [ @@ -2739,24 +2809,24 @@ "tool_state": "{\"__job_resource\": {\"__current_case__\": 0, \"__job_resource__select\": \"no\"}, \"advanced_settings\": {\"use_advanced_settings\": \"Yes\", \"__current_case__\": 1, \"library_type\": {\"__class__\": \"ConnectedValue\"}, \"mask_file\": {\"__class__\": \"ConnectedValue\"}, \"inner_mean_dist\": \"200\", \"inner_dist_std_dev\": \"80\", \"max_mle_iterations\": \"5000\", \"junc_alpha\": \"0.001\", \"small_anchor_fraction\": \"0.09\", \"overhang_tolerance\": \"8\", \"max_bundle_length\": \"10000000\", \"max_bundle_frags\": \"1000000\", \"min_intron_length\": \"50\", \"trim_three_avgcov_thresh\": \"10\", \"trim_three_dropoff_frac\": \"0.1\"}, \"bias_correction\": {\"do_bias_correction\": \"Yes\", \"__current_case__\": 0, \"seq_source\": {\"index_source\": \"cached\", \"__current_case__\": 0, \"index\": {\"__class__\": \"ConnectedValue\"}}}, \"global_model\": null, \"input\": {\"__class__\": \"ConnectedValue\"}, \"length_correction\": \"--no-effective-length-correction\", \"max_intron_len\": \"300000\", \"min_isoform_fraction\": \"0.1\", \"multiread_correct\": true, \"pre_mrna_fraction\": \"0.15\", \"reference_annotation\": {\"use_ref\": \"Use reference annotation\", \"__current_case__\": 1, \"reference_annotation_file\": {\"__class__\": \"ConnectedValue\"}, \"compatible_hits_norm\": \"\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "2.2.1.3", "type": "tool", - "uuid": "a3371ab0-86dd-4302-bdbc-4e79421186d9", + "uuid": "351d3b94-214e-496d-8eae-ef61174b6809", "when": "$(inputs.when)", "workflow_outputs": [ - { - "label": "transcripts_expression_cufflinks", - "output_name": "transcripts_expression", - "uuid": "1f278863-0d6b-4167-b5a4-27850704c72b" - }, { "label": "genes_expression_cufflinks", "output_name": "genes_expression", - "uuid": "fb312cfb-d5d4-4327-bcd8-16354713d720" + "uuid": "3ca1813f-0dcd-48b3-9075-15fa3b4a2ef3" + }, + { + "label": "transcripts_expression_cufflinks", + "output_name": "transcripts_expression", + "uuid": "37c571b6-cd9a-42a2-ae3e-d167daf8ef47" } ] }, "18": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1", "errors": null, "id": 18, "input_connections": { @@ -2791,29 +2861,29 @@ "output_name": "outfile" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1", "tool_shed_repository": { - "changeset_revision": "12615d397df7", + "changeset_revision": "fbf99087e067", "name": "text_processing", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"code\": {\"__class__\": \"ConnectedValue\"}, \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "9.3+galaxy0", + "tool_version": "9.3+galaxy1", "type": "tool", - "uuid": "3b5e2b1f-bb92-4b81-8b47-12dc83f81b02", + "uuid": "bae7a5b1-a9a1-4d45-9e8b-e375bfc27942", "when": null, "workflow_outputs": [ { "label": "HTS count like output", "output_name": "outfile", - "uuid": "799d84a4-0fe4-4ecc-882b-ee007a6f2358" + "uuid": "87baa6e9-1455-4537-bf0b-42d4beeba4c0" } ] }, "19": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.1+galaxy1", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0", "errors": null, "id": 19, "input_connections": { @@ -2838,6 +2908,10 @@ { "description": "runtime parameter for tool StringTie", "name": "adv" + }, + { + "description": "runtime parameter for tool StringTie", + "name": "input_options" } ], "label": "Compute FPKM with StringTie", @@ -2863,23 +2937,23 @@ "output_name": "output_gtf" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.1+galaxy1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0", "tool_shed_repository": { - "changeset_revision": "ae618321f34a", + "changeset_revision": "cbf488da3b2c", "name": "stringtie", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"adv\": {\"abundance_estimation\": true, \"omit_sequences\": \"\", \"name_prefix\": null, \"fraction\": \"0.01\", \"min_tlen\": \"200\", \"min_anchor_len\": \"10\", \"min_anchor_cov\": \"1\", \"min_bundle_cov\": \"1\", \"bdist\": \"50\", \"bundle_fraction\": \"1.0\", \"disable_trimming\": false, \"multi_mapping\": false, \"point_features\": {\"__class__\": \"RuntimeValue\"}}, \"guide\": {\"use_guide\": \"yes\", \"__current_case__\": 1, \"guide_source\": {\"guide_gff_select\": \"history\", \"__current_case__\": 1, \"ref_hist\": {\"__class__\": \"ConnectedValue\"}}, \"input_estimation\": true, \"special_outputs\": {\"special_outputs_select\": \"no\", \"__current_case__\": 2}, \"coverage_file\": false}, \"input_options\": {\"input_mode\": \"short_reads\", \"__current_case__\": 0, \"input_bam\": {\"__class__\": \"ConnectedValue\"}}, \"rna_strandness\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.2.1+galaxy1", + "tool_version": "2.2.3+galaxy0", "type": "tool", - "uuid": "4c7d6852-faac-4269-a7fa-92f93ebdab4c", + "uuid": "d87ca6aa-3738-49a3-8090-41aa896b52fa", "when": "$(inputs.when)", "workflow_outputs": [ { "label": "genes_expression_stringtie", "output_name": "gene_abundance_estimation", - "uuid": "bd391675-83ab-4eac-8083-be71c69b786f" + "uuid": "07d67129-87be-4281-b82b-64fcb300b0e1" } ] } @@ -2887,11 +2961,11 @@ "tags": [ "RNAseq" ], - "uuid": "847e4ce1-5522-499c-ab7d-9a3efe06a7be", - "version": 2 + "uuid": "6a424c0e-eb24-4f61-8750-adc09f4db1b1", + "version": 1 }, "readme": "# RNA-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a list of datasets of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- forward adapter sequence: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the read is complementary to the coding sequence, forward means that the read is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with Stringtie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. This can also be used to get the strandedness.\n- FPKM values for genes and transcripts are computed with cufflinks using correction for multi-mapped reads (this step is optionnal).\n- FPKM/TPM values for genes are computed with StringTie (this step is optional).\n- The BAM is filtered to keep only uniquely mapped reads (tag NH:i:1).\n- Unstranded coverage is computed with bedtools and normalized to the number of million uniquely mapped reads.\n- The three coverage files are converted to bigwig.\n\n### Warning\n\n- The coverage stranded output depends on the strandedness of the library:\n - If you have an unstranded library, stranded coverages are useless\n - If you have a forward stranded library, the label matches the orientation of reads.\n - If you have a reverse stranded library, `forward` should correspond to genes on the forward strand and uses the reads mapped on the reverse strand. `reverse` should correspond to genes on the reverse strand and uses the reads mapped on the forward strand.\n\n## Contribution\n\n@lldelisle wrote the workflow and the tests.\n\n@nagoue updated the tools, made it work in usegalaxy.org, fixed some best practices.\n", - "changelog": "# Changelog\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.5] 2023-09-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n\n### Manual update\n- Use STAR to compute normalized strand-specific coverage\n- Add an option to use StringTie to compute FPKM\n- Make cufflinks step optional\n\n## [0.4.1] 2023-09-14\n- add author in dockstore file\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-02\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1`\n\n## [0.1] 2022-10-12\n\nFirst release.\n" + "changelog": "# Changelog\n\n## [0.8] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n\n## [0.7] 2024-06-25\n\n### Automatic update (triggered manually)\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0`\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.5] 2023-09-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n\n### Manual update\n- Use STAR to compute normalized strand-specific coverage\n- Add an option to use StringTie to compute FPKM\n- Make cufflinks step optional\n\n## [0.4.1] 2023-09-14\n- add author in dockstore file\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-02\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1`\n\n## [0.1] 2022-10-12\n\nFirst release.\n" } ], "path": "./workflows/transcriptomics/rnaseq-sr" @@ -2903,9 +2977,9 @@ "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/rnaseq-pe.ga", + "primaryDescriptorPath": "/BREW3R.ga", "testParameterFiles": [ - "/rnaseq-pe-tests.yml" + "/BREW3R-tests.yml" ], "authors": [ { @@ -2915,749 +2989,1249 @@ ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow takes as input a list of paired-end fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously as well as normalized coverage (per million mapped reads) on uniquely mapped reads. The counts are reprocessed to be similar to HTSeq-count output. FPKM are computed with cufflinks and/or with StringTie. The unstranded normalized coverage is computed with bedtools.", + "annotation": "This workflow takes a collection of BAM (output of STAR) and a gtf. It extends the input gtf using de novo annotation.", + "comments": [], "creator": [ { "class": "Person", - "identifier": "0000-0002-1964-4960", + "identifier": "https://orcid.org/0000-0002-1964-4960", "name": "Lucille Delisle" } ], "format-version": "0.1", - "license": "MIT", - "release": "0.6", - "name": "RNAseq_PE", + "license": "GPL-3.0-or-later", + "name": "BREW3R", + "release": "0.1", + "report": { + "markdown": "\n# Workflow Execution Report\n\n## Workflow Inputs\n```galaxy\ninvocation_inputs()\n```\n\n## Workflow Outputs\n```galaxy\ninvocation_outputs()\n```\n\n## Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { - "annotation": "Should be a list of paired-end RNA-seq fastqs", + "annotation": "", "content_id": null, "errors": null, "id": 0, "input_connections": {}, "inputs": [ { - "description": "Should be a list of paired-end RNA-seq fastqs", - "name": "PE fastq input" + "description": "", + "name": "Input gtf" } ], - "label": "PE fastq input", - "name": "Input dataset collection", + "label": "Input gtf", + "name": "Input dataset", "outputs": [], "position": { "left": 0, - "top": 252.80832516863774 + "top": 0 }, "tool_id": null, - "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list:paired\"}", + "tool_state": "{\"optional\": false, \"format\": [\"gtf\"], \"tag\": null}", "tool_version": null, - "type": "data_collection_input", - "uuid": "688da967-e739-409a-b950-b4e4985a1a3b", + "type": "data_input", + "uuid": "c59ff317-5e58-4823-bd62-6474555f40a7", "when": null, "workflow_outputs": [] }, "1": { - "annotation": "Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC", + "annotation": "BAM collection for example output of STAR", "content_id": null, "errors": null, "id": 1, "input_connections": {}, "inputs": [ { - "description": "Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC", - "name": "forward_adapter" + "description": "BAM collection for example output of STAR", + "name": "BAM collection" } ], - "label": "forward_adapter", - "name": "Input parameter", + "label": "BAM collection", + "name": "Input dataset collection", "outputs": [], "position": { - "left": 26.45001220703125, - "top": 338.9083312721534 + "left": 52, + "top": 92.84911999999173 }, "tool_id": null, - "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", + "tool_state": "{\"optional\": false, \"format\": [\"bam\"], \"tag\": \"\", \"collection_type\": \"list\"}", "tool_version": null, - "type": "parameter_input", - "uuid": "0179b655-f7e2-4b8b-b8b1-f875d0d8039f", + "type": "data_collection_input", + "uuid": "14322b26-f7e5-415d-ab99-74b11036d9d8", "when": null, "workflow_outputs": [] }, "2": { - "annotation": "Please use: For R2: - For Nextera: CTGTCTCTTATACACATCTGACGCTGCCGACGA - For TruSeq: GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT or AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT", + "annotation": "", "content_id": null, "errors": null, "id": 2, "input_connections": {}, "inputs": [ { - "description": "Please use: For R2: - For Nextera: CTGTCTCTTATACACATCTGACGCTGCCGACGA - For TruSeq: GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT or AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT", - "name": "reverse_adapter" + "description": "", + "name": "strandedness" } ], - "label": "reverse_adapter", + "label": "strandedness", "name": "Input parameter", "outputs": [], "position": { - "left": 68, - "top": 427.04166257098154 + "left": 122, + "top": 186.84911999999173 }, "tool_id": null, - "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", + "tool_state": "{\"restrictions\": [\"stranded - forward\", \"stranded - reverse\", \"unstranded\"], \"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "a63a8ae0-aaf6-45ac-9b43-c6dc69dd7f6d", + "uuid": "ee38bb19-c158-4a54-82b1-a2eeb195e5f0", "when": null, "workflow_outputs": [] }, "3": { - "annotation": "reference_genome", + "annotation": "", "content_id": null, "errors": null, "id": 3, "input_connections": {}, "inputs": [ { - "description": "reference_genome", - "name": "reference_genome" + "description": "", + "name": "minimum coverage" } ], - "label": "reference_genome", + "label": "minimum coverage", "name": "Input parameter", "outputs": [], "position": { - "left": 132.63336181640625, - "top": 522.134886401586 + "left": 229, + "top": 269.84911999999173 }, "tool_id": null, - "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_state": "{\"default\": 10, \"parameter_type\": \"integer\", \"optional\": true}", "tool_version": null, "type": "parameter_input", - "uuid": "ff4a9932-6ed0-436f-a63c-d6fbe2a582a3", + "uuid": "912d8e34-2782-4375-a683-1f71ec0cabb7", "when": null, "workflow_outputs": [] }, "4": { - "annotation": "gtf compatible with the reference_genome. Mind the UCSC/Ensembl differences in chromosome naming", + "annotation": "", "content_id": null, "errors": null, "id": 4, "input_connections": {}, "inputs": [ { - "description": "gtf compatible with the reference_genome. Mind the UCSC/Ensembl differences in chromosome naming", - "name": "gtf" + "description": "", + "name": "minimum FPKM for merge" } ], - "label": "gtf", - "name": "Input dataset", + "label": "minimum FPKM for merge", + "name": "Input parameter", "outputs": [], "position": { - "left": 150.60003662109375, - "top": 606.751585620336 + "left": 278, + "top": 383.34911999999173 }, "tool_id": null, - "tool_state": "{\"optional\": false, \"tag\": \"\"}", + "tool_state": "{\"default\": 1.0, \"parameter_type\": \"float\", \"optional\": true}", "tool_version": null, - "type": "data_input", - "uuid": "c91756d4-f7f1-4dcc-97f6-da4c96a53c94", + "type": "parameter_input", + "uuid": "b71eaaf4-31b8-47e9-a5dd-27c48faaa0c6", "when": null, "workflow_outputs": [] }, "5": { - "annotation": "For stranded RNA, reverse means that the read is complementary to the coding sequence, forward means that the read is in the same orientation as the coding sequence", - "content_id": null, + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0", "errors": null, "id": 5, - 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"name": "cufflinks_FPKM" + "description": "runtime parameter for tool Map parameter value", + "name": "input_param_type" } ], - "label": "cufflinks_FPKM", - "name": "Input parameter", - "outputs": [], - "position": { - "left": 202.6500244140625, - "top": 735.4800895070166 - }, - "tool_id": null, - "tool_state": "{\"parameter_type\": \"boolean\", \"optional\": false}", - "tool_version": null, - "type": "parameter_input", - "uuid": "fbe4c961-6b62-46b7-a329-163b9cda4979", - "when": null, - "workflow_outputs": [] - }, - "7": { - "annotation": "Could be a gtf with for example one entry for the chrM forward and one entry for the chrM reverse", - "content_id": null, - "errors": null, - "id": 7, - "input_connections": {}, - "inputs": [ + "label": null, + "name": "Map parameter value", + "outputs": [ { - "description": "Could be a gtf with for example one entry for the chrM forward and one entry for the chrM reverse", - "name": "gtf with regions to exclude from FPKM normalization with Cufflinks" + "name": "output_param_text", + "type": "expression.json" } ], - 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forward`, `stranded - reverse` and `unstranded`. For stranded libraries, reverse means that the read is complementary to the coding sequence, forward means that the read is in the same orientation as the coding sequence.\n- minimum coverage: Minimum reads per bp coverage to consider for assembly in each de novo assembly (for each BAM file). Default: 10\n- minimum FPKM for merge: Minimum FPKM value for a transcript to be included into the merged de novo assembly.\n\n## Processing\n\n- StringTie is called once per input BAM file to compute de novo assembly.\n- StringTie is called to merge all outputs of previous steps.\n- BREW3R.r is run with the default parameters on the input gtf to extend and the output of StringTie. If the library was unstranded all merged transcripts without orientation that overlaps exons of both strands are not used for the extension.\n", + "changelog": "# Changelog\n\n## [0.1] 2024-06-17\n\nFirst release.\n" + } + ], + "path": "./workflows/transcriptomics/brew3r" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/rnaseq-pe.ga", + "testParameterFiles": [ + "/rnaseq-pe-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a list of paired-end fastqs. Adapters and bad quality bases are removed with cutadapt. Reads are mapped with STAR with ENCODE parameters and genes are counted simultaneously as well as normalized coverage (per million mapped reads) on uniquely mapped reads. The counts are reprocessed to be similar to HTSeq-count output. FPKM are computed with cufflinks and/or with StringTie. 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null, \"__rerun_remap_job_id__\": null}", - "tool_version": "9.3+galaxy0", + "tool_version": "9.3+galaxy1", "type": "tool", - "uuid": "4e158197-8591-4fce-b969-9002f7482634", + "uuid": "ec10a98b-adb9-4037-9137-1717068d7157", "when": null, "workflow_outputs": [] }, @@ -4328,7 +4928,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Relabel identifiers", + "name": "how" + } + ], "label": "Relabelled strand 1", "name": "Relabel identifiers", "outputs": [ @@ -4352,7 +4957,7 @@ "tool_state": "{\"how\": {\"how_select\": \"txt\", \"__current_case__\": 0, \"labels\": {\"__class__\": \"ConnectedValue\"}, \"strict\": false}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "6a3f57c0-f6d6-468f-8ac9-b6882f754eed", + "uuid": "e9dcd2df-2834-4e9a-bef2-7666de012b8a", "when": null, "workflow_outputs": [] }, @@ -4371,7 +4976,12 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Relabel identifiers", + "name": "how" + } + ], "label": "Relabelled strand 2", "name": "Relabel identifiers", "outputs": [ @@ -4395,7 +5005,7 @@ "tool_state": "{\"how\": {\"how_select\": \"txt\", \"__current_case__\": 0, \"labels\": {\"__class__\": \"ConnectedValue\"}, \"strict\": false}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "d181b9ba-0cd3-4de6-8e82-c53a97c5ae67", + "uuid": "147ccbb0-b951-4851-9bf5-2c6b439ac1b6", "when": null, "workflow_outputs": [] }, @@ -4438,7 +5048,7 @@ "tool_state": "{\"advanced\": {\"conflict\": {\"duplicate_options\": \"keep_first\", \"__current_case__\": 3}}, \"inputs\": [{\"__index__\": 0, \"input\": {\"__class__\": \"ConnectedValue\"}}, {\"__index__\": 1, \"input\": {\"__class__\": \"ConnectedValue\"}}], \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "4b4b9d77-13fe-4b8a-a5af-e0857547521e", + "uuid": "f47d7381-13b2-4615-b947-17a0ac2ad500", "when": null, "workflow_outputs": [] }, @@ -4479,29 +5089,29 @@ "tool_state": "{\"input1\": {\"__class__\": \"ConnectedValue\"}, \"settings\": {\"settingsType\": \"preset\", \"__current_case__\": 0}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.1.1", "type": "tool", - "uuid": "b69eee65-c37e-4c75-8127-b78185b130db", + "uuid": "852f2d23-b48e-44d0-aaf2-aed33532d98a", "when": null, "workflow_outputs": [ { "label": "stranded coverage", "output_name": "out_file1", - "uuid": "dd43e657-0116-46ad-9cc9-c12fb871988c" + "uuid": "56ad2ce4-a0d8-4895-b774-79705460c246" } ] } }, - "tags": "", - "uuid": "31aca78d-b855-4f28-b89c-6bf29f5f2015" + "tags": [], + "uuid": "3d850804-e1e9-4517-8f33-ecba0c527b73" }, "tool_id": null, "type": "subworkflow", - "uuid": "cc127732-933e-420a-a5ae-24fed48e7e6a", + "uuid": "d16e1013-cc55-4143-90a4-d58b24684f68", "when": null, "workflow_outputs": [ { "label": "stranded coverage", "output_name": "stranded coverage", - "uuid": "245c268e-87fc-43a7-9d49-d18d9363b475" + "uuid": "ee5ab22f-e952-4094-9895-11ce23b57f79" } ] }, @@ -4536,7 +5146,20 @@ "output_name": "output" } }, - "inputs": [], + "inputs": [ + { + "description": "runtime parameter for tool Cufflinks", + "name": "advanced_settings" + }, + { + "description": "runtime parameter for tool Cufflinks", + "name": "advanced_settings" + }, + { + "description": "runtime parameter for tool Cufflinks", + "name": "reference_annotation" + } + ], "label": "Compute FPKM with cufflinks", "name": "Cufflinks", "outputs": [ @@ -4592,24 +5215,24 @@ "tool_state": "{\"__job_resource\": {\"__current_case__\": 0, \"__job_resource__select\": \"no\"}, \"advanced_settings\": {\"use_advanced_settings\": \"Yes\", \"__current_case__\": 1, \"library_type\": {\"__class__\": \"ConnectedValue\"}, \"mask_file\": {\"__class__\": \"ConnectedValue\"}, \"inner_mean_dist\": \"200\", \"inner_dist_std_dev\": \"80\", \"max_mle_iterations\": \"5000\", \"junc_alpha\": \"0.001\", \"small_anchor_fraction\": \"0.09\", \"overhang_tolerance\": \"8\", \"max_bundle_length\": \"10000000\", \"max_bundle_frags\": \"1000000\", \"min_intron_length\": \"50\", \"trim_three_avgcov_thresh\": \"10\", \"trim_three_dropoff_frac\": \"0.1\"}, \"bias_correction\": {\"do_bias_correction\": \"Yes\", \"__current_case__\": 0, \"seq_source\": {\"index_source\": \"cached\", \"__current_case__\": 0, \"index\": {\"__class__\": \"ConnectedValue\"}}}, \"global_model\": null, \"input\": {\"__class__\": \"ConnectedValue\"}, \"length_correction\": \"--no-effective-length-correction\", \"max_intron_len\": \"300000\", \"min_isoform_fraction\": \"0.1\", \"multiread_correct\": true, \"pre_mrna_fraction\": \"0.15\", \"reference_annotation\": {\"use_ref\": \"Use reference annotation\", \"__current_case__\": 1, \"reference_annotation_file\": {\"__class__\": \"ConnectedValue\"}, \"compatible_hits_norm\": \"\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "2.2.1.3", "type": "tool", - "uuid": "a3371ab0-86dd-4302-bdbc-4e79421186d9", + "uuid": "c38c3093-61e6-49f9-b756-8e25c37c8c68", "when": "$(inputs.when)", "workflow_outputs": [ { "label": "genes_expression_cufflinks", "output_name": "genes_expression", - "uuid": "fb312cfb-d5d4-4327-bcd8-16354713d720" + "uuid": "807a3d5e-8f42-43c2-a627-a4500c721939" }, { "label": "transcripts_expression_cufflinks", "output_name": "transcripts_expression", - "uuid": "1f278863-0d6b-4167-b5a4-27850704c72b" + "uuid": "bb2b3707-a64b-4fd6-801e-9d2ff1e3dbda" } ] }, "19": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1", "errors": null, "id": 19, "input_connections": { @@ -4644,29 +5267,29 @@ "output_name": "outfile" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1", "tool_shed_repository": { - "changeset_revision": "12615d397df7", + "changeset_revision": "fbf99087e067", "name": "text_processing", "owner": "bgruening", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"code\": {\"__class__\": \"ConnectedValue\"}, \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "9.3+galaxy0", + "tool_version": "9.3+galaxy1", "type": "tool", - "uuid": "3b5e2b1f-bb92-4b81-8b47-12dc83f81b02", + "uuid": "34922bd3-4676-4f7d-8e05-af0ef0c1efa4", "when": null, "workflow_outputs": [ { "label": "HTS count like output", "output_name": "outfile", - "uuid": "799d84a4-0fe4-4ecc-882b-ee007a6f2358" + "uuid": "45b51c7f-57ca-45d4-8460-30ead2bda023" } ] }, "20": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.1+galaxy1", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0", "errors": null, "id": 20, "input_connections": { @@ -4691,6 +5314,10 @@ { "description": "runtime parameter for tool StringTie", "name": "adv" + }, + { + "description": "runtime parameter for tool StringTie", + "name": "input_options" } ], "label": "Compute FPKM with StringTie", @@ -4716,23 +5343,23 @@ "output_name": "output_gtf" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.1+galaxy1", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0", "tool_shed_repository": { - "changeset_revision": "ae618321f34a", + "changeset_revision": "cbf488da3b2c", "name": "stringtie", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"adv\": {\"abundance_estimation\": true, \"omit_sequences\": \"\", \"name_prefix\": null, \"fraction\": \"0.01\", \"min_tlen\": \"200\", \"min_anchor_len\": \"10\", \"min_anchor_cov\": \"1\", \"min_bundle_cov\": \"1\", \"bdist\": \"50\", \"bundle_fraction\": \"1.0\", \"disable_trimming\": false, \"multi_mapping\": false, \"point_features\": {\"__class__\": \"RuntimeValue\"}}, \"guide\": {\"use_guide\": \"yes\", \"__current_case__\": 1, \"guide_source\": {\"guide_gff_select\": \"history\", \"__current_case__\": 1, \"ref_hist\": {\"__class__\": \"ConnectedValue\"}}, \"input_estimation\": true, \"special_outputs\": {\"special_outputs_select\": \"no\", \"__current_case__\": 2}, \"coverage_file\": false}, \"input_options\": {\"input_mode\": \"short_reads\", \"__current_case__\": 0, \"input_bam\": {\"__class__\": \"ConnectedValue\"}}, \"rna_strandness\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.2.1+galaxy1", + "tool_version": "2.2.3+galaxy0", "type": "tool", - "uuid": "4c7d6852-faac-4269-a7fa-92f93ebdab4c", + "uuid": "0403b248-c73c-4a1b-85fd-64f36278c952", "when": "$(inputs.when)", "workflow_outputs": [ { "label": "genes_expression_stringtie", "output_name": "gene_abundance_estimation", - "uuid": "bd391675-83ab-4eac-8083-be71c69b786f" + "uuid": "fc2a77c2-1868-46c0-ad76-648484d764a2" } ] } @@ -4740,11 +5367,11 @@ "tags": [ "RNAseq" ], - "uuid": "065bd049-36f9-4ff9-95ea-effca41a691e", - "version": 2 + "uuid": "242ed0e9-f1fc-4eb0-af99-8328211f5998", + "version": 1 }, "readme": "# RNA-seq paired-end Workflow\n\n## Inputs dataset\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n- As well as a gtf file with genes\n- Optional, but recommended: a gtf file with regions to exclude from normalization in Cufflinks.\n\n - For instance a gtf that masks chrM for the mm10 genome:\n\n```\nchrM\tchrM_gene\texon\t0\t16299\t.\t+\t.\tgene_id \"chrM_gene_plus\"; transcript_id \"chrM_tx_plus\"; exon_id \"chrM_ex_plus\";\nchrM\tchrM_gene\texon\t0\t16299\t.\t-\t.\tgene_id \"chrM_gene_minus\"; transcript_id \"chrM_tx_minus\"; exon_id \"chrM_ex_minus\";\n```\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually classical Illumina RNA libraries are Truseq and ISML (relatively new Illumina library) is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera. If the read length is relatively short (50bp), there is probably no adapter so it will not impact your results.\n- reference_genome: this field will be adapted to the genomes available for STAR\n- strandedness: For stranded RNA, reverse means that the first read in a pair is complementary to the coding sequence, forward means that the first read in a pair is in the same orientation as the coding sequence. This will only count alignments that are compatible with your library preparation strategy. This is also used for the stranded coverage and for FPKM computation with cufflinks/StringTie.\n- cufflinks_FPKM: Whether you want to get FPKM with Cufflinks (pretty long)\n- stringtie_FPKM: Whether you want to get FPKM/TPM etc... with StringTie.\n\n## Processing\n\n- The workflow will remove adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with STAR with ENCODE parameters (for long RNA-seq but I use it for short also). STAR is also used to count reads per gene and generate strand-specific normalized coverage (on uniquely mapped reads).\n- A multiQC is run to have an overview of the QC. This can also be used to get the strandedness.\n- FPKM values for genes and transcripts are computed with cufflinks using correction for multi-mapped reads (this step is optionnal).\n- FPKM/TPM values for genes are computed with StringTie.\n- The BAM is filtered to keep only uniquely mapped reads (tag NH:i:1).\n- Unstranded coverage is computed with bedtools and normalized to the number of million uniquely mapped reads.\n- The three coverage files are converted to bigwig.\n\n### Warning\n\n- The coverage stranded output depends on the strandedness of the library:\n - If you have an unstranded library, stranded coverages are useless\n - If you have a forward stranded library, the label matches the orientation of the first read in pairs.\n - If you have a reverse stranded library, the label matches the orientation of the second read in pairs.\n", - "changelog": "# Changelog\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.5] 2023-09-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n\n### Manual update\n- Use STAR to compute normalized strand-specific coverage\n- Add an option to use StringTie to compute FPKM\n- Make cufflinks step optional\n\n## [0.4.1] 2023-09-14\n- add author in dockstore file\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-02\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1`\n\n## [0.1] 2022-10-21\n\nFirst release.\n" + "changelog": "# Changelog\n\n## [0.8] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n\n## [0.7] 2024-06-25\n\n### Automatic update (triggered manually)\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_genomecoveragebed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0`\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/map_param_value/map_param_value/0.2.0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy0`\n\n## [0.5] 2023-09-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n\n### Manual update\n- Use STAR to compute normalized strand-specific coverage\n- Add an option to use StringTie to compute FPKM\n- Make cufflinks step optional\n\n## [0.4.1] 2023-09-14\n- add author in dockstore file\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-02\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.8a+galaxy1`\n\n## [0.1] 2022-10-21\n\nFirst release.\n" } ], "path": "./workflows/transcriptomics/rnaseq-pe" @@ -5312,166 +5939,367 @@ "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/Genome-assembly-with-Flye.ga", + "primaryDescriptorPath": "/bacterial_genome_assembly.ga", "testParameterFiles": [ - "/Genome-assembly-with-Flye-tests.yml" + "/bacterial_genome_assembly-tests.yml" ], "authors": [ { - "name": "Anna Syme", - "orcid": "0000-0002-9906-0673" + "name": "abromics-consortium", + "url": "https://www.abromics.fr/" + }, + { + "name": "ABRomics", + "email": "abromics-support@groupes.france-bioinformatique.fr" + }, + { + "name": "Pierre Marin", + "alternateName": "pimarin", + "orcid": "0000-0002-8304-138X" + }, + { + "name": "Clea Siguret", + "alternateName": "clsiguret", + "orcid": "0009-0005-6140-0379" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "Assemble long reads with Flye, then view assembly statistics and assembly graph", + "annotation": "Assembly of bacterial paired-end short read data with generation of quality metrics and reports", "creator": [ + { + "class": "Organization", + "name": "abromics-consortium", + "url": "https://www.abromics.fr/" + }, { "class": "Person", - "identifier": "https://orcid.org/0000-0002-9906-0673", - "name": "Anna Syme" + "email": "mailto:abromics-support@groupes.france-bioinformatique.fr", + "name": "ABRomics" + }, + { + "alternateName": "pimarin", + "class": "Person", + "identifier": "https://orcid.org/0000-0002-8304-138X", + "name": "Pierre Marin" + }, + { + "alternateName": "clsiguret", + "class": "Person", + "identifier": 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{ + "changeset_revision": "def7a82d23e1", + "name": "tooldistillator_summarize", + "owner": "iuc", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"summarize_data\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "0.9+galaxy0", + "type": "tool", + "uuid": "3bbe0eba-b6bb-4d43-ab57-2b899b8112ae", + "when": null, + "workflow_outputs": [ + { + "label": "tooldistillator_summarize", + "output_name": "summary_json", + "uuid": "9097e16d-ace5-47f5-9af5-7eb3b13b91d2" } ] } }, - "tags": [], - "uuid": "83ef6fdc-b8a9-41af-a824-0225f0199e63", - "version": 21 + "tags": [ + "fastq", + "Genomics", + "bacterial-genomics", + "paired-end", + "assembly", + "quality", + "ABRomics" + ], + "uuid": "bfe7f341-07ef-4bfe-9b50-2bc7628d6c55", + "version": 1 }, - "readme": "# Genome assembly with Flye workflow\n\n\n## Why use this workflow?\n\n- This is a fairly simple workflow that assembles a genome from long sequencing reads.\n- It takes in sequencing reads from PacBio (Hifi or non-Hifi), or Oxford Nanopore.\n- If you have PacBio Hifi reads, you may prefer to use a workflow with the assembly tool Hifiasm, such as the those in the suite of VGP workflows. \n\n## Inputs\n\nRaw sequencing reads from PacBio or Oxford Nanopore in format:\nfasta, fasta.gz, fastq, fastq.gz, fastqsanger.gz or fastqsanger\n\n## What does the workflow do\n\n- Assembles the reads with the tool Flye\n- Summarizes the statistics with the tool Fasta statistics\n- Report with the tool Quast\n- Renders the assembly graph with the tool Bandage\n\n## Settings\n\nRun as-is or change parameters at runtime\n\nFor example:\n- change the Flye option of \"mode\" to the correct sequencing type\n- change the Quast option for \"Type of organism\" to correct taxon\n \n## Outputs\n\n- Flye assembly output - four files: fasta, gfa for bandage, graph_dot file, assembly info\n- Fasta statistics\n- Bandage image\n- Quast report\n", - "changelog": "# Changelog\n\n## [0.2] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/flye/flye/2.9.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/flye/flye/2.9.3+galaxy0`\n\nAll notable changes to this project will be documented in this file.\n\nThe format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),\nand this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).\n\n## [0.1] 2023-07-14\nFirst release.\n" + "readme": "# Bacterial genome assembly workflow for paired end data (v1.0)\n\nThis workflow uses paired-end illumina trimmed reads fastq(.gz) files and executes the following steps:\n1. Assembly raw reads to a final contig fasta file \n - **Shovill**\n2. Quality control of the assembly\n - **Quast**\n - **Bandage** to plot assembly graph\n - **Refseqmasher** to identify the closed reference genome\n3. Aggregating outputs into a single JSON file\n - **ToolDistillator** to extract and aggregate information from different tool outputs to JSON parsable files\n\n## Inputs\n\n1. Paired-end illumina trimmed reads in fastq(.gz) format.\n\n## Outputs\n\n1. Assembly:\n - Assembly with contig in fasta\n - Mapped read on assembly in bam format\n - Graph assembly in gfa format\n2. Quality of Assembly:\n - Assembly report\n - Assembly Graph\n - Tabular result of closed reference genome\n3. Aggregating outputs\n - JSON file with information about the outputs of **Shovill**, **Quast**, **Bandage**, **Refseqmasher**", + "changelog": "# Changelog\n\n## [1.1.1] 2024-07-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.9+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.9+galaxy0`\n\n## [1.1] 2024-06-24\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/shovill/shovill/1.1.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/shovill/shovill/1.1.0+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_info/0.8.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_info/2022.09+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_image/0.8.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_image/2022.09+galaxy4`\n\n## [1.0] - 05-06-2024\n\n- First release" } ], - "path": "./workflows/genome-assembly/assembly-with-flye" + "path": "./workflows/genome-assembly/bacterial-genome-assembly" }, { "version": 1.2, "workflows": [ { "name": "main", - "primaryDescriptorPath": "/metaprosip.ga", "subclass": "Galaxy", "publish": true, + "primaryDescriptorPath": "/Genome-assembly-with-Flye.ga", "testParameterFiles": [ - "/metaprosip-tests.yml" + "/Genome-assembly-with-Flye-tests.yml" ], "authors": [ { - "name": "Matthias Bernt", - "orcid": "0000-0003-3763-0797" + "name": "Anna Syme", + "orcid": "0000-0002-9906-0673" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "Automated inference of stable isotope incorporation rates in proteins for functional metaproteomics ", + "annotation": "Assemble long reads with Flye, then view assembly statistics and assembly graph", "creator": [ { "class": "Person", - "identifier": "0000-0003-3763-0797", - "name": "Matthias Bernt" + "identifier": "https://orcid.org/0000-0002-9906-0673", + "name": "Anna Syme" } ], "format-version": "0.1", "license": "MIT", - 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four files: fasta, gfa for bandage, graph_dot file, assembly info\n- Fasta statistics\n- Bandage image\n- Quast report\n", + "changelog": "# Changelog\n\n## [0.2] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/flye/flye/2.9.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/flye/flye/2.9.3+galaxy0`\n\nAll notable changes to this project will be documented in this file.\n\nThe format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),\nand this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).\n\n## [0.1] 2023-07-14\nFirst release.\n" + } + ], + "path": "./workflows/genome-assembly/assembly-with-flye" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/quality_and_contamination_control.ga", + "testParameterFiles": [ + "/quality_and_contamination_control-tests.yml" + ], + "authors": [ + { + "name": "ABRomics", + "email": "abromics-support@groupes.france-bioinformatique.fr" + }, + { + "name": "abromics-consortium", + "url": "https://www.abromics.fr/" + }, + { + "name": "Pierre Marin", + "alternateName": "pimarin", + "orcid": "0000-0002-8304-138X" + }, + { + "name": "Clea Siguret", + "alternateName": "clsiguret", + "orcid": "0009-0005-6140-0379" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Short paired-end read analysis to provide quality analysis, read cleaning and taxonomy assignation", + "creator": [ + { + "class": "Person", + "email": "mailto:abromics-support@groupes.france-bioinformatique.fr", + "name": "ABRomics" }, - 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"tags": [], - "uuid": "f25be8fa-7823-456f-9707-a497703f48d7", - "version": 0 + "tags": [ + "Genomics", + "fastq", + "bacterial-genomics", + "taxonomy-assignment", + "paired-end", + "quality", + "ABRomics", + "trimming" + ], + "uuid": "eb1c667d-639d-4403-a2b4-1cb6683e0fa5", + "version": 1 }, - "readme": "# RepeatMasking Workflow\n\nThis workflow uses RepeatModeler and RepeatMasker for genome analysis.\n\n- RepeatModeler is a software package for identifying and modeling de novo families of transposable elements (TEs). At the heart of RepeatModeler are three de novo repeat search programs (RECON, RepeatScout and LtrHarvest/Ltr_retriever) which use complementary computational methods to identify repeat element boundaries and family relationships from sequence data.\n\n- RepeatMasker is a program that analyzes DNA sequences for *interleaved repeats* and *low-complexity* DNA sequences. The result of the program is a detailed annotation of the repeats present in the query sequence, as well as a modified version of the query sequence in which all annotated repeats are present.\n\n## Input dataset for RepeatModeler\n- RepeatModeler requires a single input file, a genome in fasta format.\n\n\n## Outputs dataset for RepeatModeler\n- Two output files are generated:\n - summary file (.tbl)\n - fasta file containing alignments in order of appearance in the query sequence\n\n\n## Input dataset for RepeatMasker\n- ReapatMasker requires the fasta file generated by RepeatModeler\n\n## Outputs datasets for RepeatMasker\n- Five output files are generated:\n - a fasta file\n - .gff3 file\n - a table summarizing the repeated content of the sequence analyzed\n - a file with statistics related to the repeated content of the sequence analyzed\n - a summary of the mutation sites found and the order of grouping\n \n", - "changelog": "# Changelog\n\n## [0.1]\n\nInitial version of the RepeatMasking workflow for genomic sequencing data." + "readme": "# Quality and Contamination control workflow for paired end data (v1.0)\n\nThis workflow uses paired-end illumina fastq(.gz) files and executes the following steps:\n1. Quality control and trimming\n - **fastp** QC control and trimming\n2. Taxonomic assignation on trimmed data\n - **Kraken2** assignation\n - **Bracken** to re-estimate abundance to the species level\n - **Recentrifuge** to make a krona chart\n3. Aggregating outputs into a single JSON file\n - **ToolDistillator** to extract and aggregate information from different tool outputs to JSON parsable files\n\n## Inputs\n\n1. Paired-end illumina raw reads in fastq(.gz) format.\n\n## Outputs\n\n1. Quality control:\n - quality report\n - trimmed raw reads\n2. Taxonomic assignation:\n - Tabular report of identified species\n - Tabular file with assigned read to a taxonomic level\n - Krona chart to illustrate species diversity of the sample\n3. Aggregating outputs:\n - JSON file with information about the outputs of **fastp**, **Kraken2**, **Bracken**, **Recentrifuge** \n", + "changelog": "# Changelog\n\n## [1.1.1] 2024-07-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.9+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.9+galaxy0`\n\n## [1.1] 2024-06-24\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/kraken2/kraken2/2.1.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/kraken2/kraken2/2.1.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bracken/est_abundance/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bracken/est_abundance/2.9+galaxy0`\n\n## [1.0] - 04-06-2024\n\n- First release\n" } ], - "path": "./workflows/repeatmasking" + "path": "./workflows/genome-assembly/quality-and-contamination-control" }, { "version": 1.2, "workflows": [ { "name": "main", + "primaryDescriptorPath": "/metaprosip.ga", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/cutandrun.ga", "testParameterFiles": [ - "/cutandrun-tests.yml" + "/metaprosip-tests.yml" ], "authors": [ { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" + "name": "Matthias Bernt", + "orcid": "0000-0003-3763-0797" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow take as input a collection of paired fastq. 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MetaProSIP parameter `Tolerance in ppm` (-mz_tolerance_ppm)\n- Fixed modifications\n- Variable modifications\n- Labeled element\n\n## Processing\n\n- DecoyDatabase: Add decoy sequences to the Fasta database (for FDR calculation)\n- FeatureFinderCentroided: identify eluting peptides that correspond to isotopologues with natural isotopic distributions \n- MSGFPlusAdapter: identify peptides through peptide fragment fingerprinting (database search)\n- FeatureFinderMultiplex: detect elution profiles of unlabeled peptides\n- PeptideIndexer: annotate protein association to identified peptides\n- FalseDiscoveryRate: Calculate FDR\n- IDMapper: map identified spectra to elution profiles\n- MetaProSIP: calculate the protein-SIP features, to perform functional grouping, and for protein inference\n", + "changelog": "# Changelog\n\n## [0.2] 2024-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_decoydatabase/DecoyDatabase/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_decoydatabase/DecoyDatabase/3.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_featurefindermultiplex/FeatureFinderMultiplex/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_featurefindermultiplex/FeatureFinderMultiplex/3.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_msgfplusadapter/MSGFPlusAdapter/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_msgfplusadapter/MSGFPlusAdapter/3.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_peptideindexer/PeptideIndexer/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_peptideindexer/PeptideIndexer/3.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_falsediscoveryrate/FalseDiscoveryRate/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_falsediscoveryrate/FalseDiscoveryRate/3.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idmapper/IDMapper/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_idmapper/IDMapper/3.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_metaprosip/MetaProSIP/2.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/galaxyp/openms_metaprosip/MetaProSIP/3.1+galaxy0`\n\n## [0.1] 2023-04-13\nFirst release.\n" + } + ], + "path": "./workflows/proteomics/openms-metaprosip" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/RepeatMasking-Workflow.ga", + "testParameterFiles": [ + "/RepeatMasking-Workflow-tests.yml" + ], + "authors": [ + { + "name": "Romane Libouban", + "email": "romane.libouban@irisa.fr" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "", + "format-version": "0.1", + "license": "MIT", + "release": "0.1", + "name": "Repeat masking with RepeatModeler and RepeatMasker", + "creator": [ + { + "class": "Person", + "email": "mailto:romane.libouban@irisa.fr", + "name": "Romane Libouban" + } + ], + "steps": { + "0": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "Apply repeat masking to this fasta file", + "name": "input" + } + ], + "label": "input", + "name": "Input dataset", + "outputs": [], + "position": { + "left": 10, + "top": 10 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null}", + "tool_version": null, + "type": "data_input", + "uuid": "ab5e19b0-ce35-4e54-a55e-f75243c86e3d", + "when": null, + "workflow_outputs": [] }, - 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"tool_version": "1.11+galaxy1", + "tool_state": "{\"__input_ext\": \"input\", \"advanced\": {\"is_only\": false, \"is_clip\": false, \"no_is\": false, \"rodspec\": false, \"primspec\": false, \"nolow\": false, \"noint\": false, \"norna\": false, \"alu\": false, \"div\": false, \"search_speed\": \"\", \"frag\": \"40000\", \"gc\": null, \"gccalc\": false, \"nocut\": false, \"xout\": false, \"keep_alignments\": false, \"invert_alignments\": false, \"poly\": false}, \"chromInfo\": \"/shared/ifbstor1/galaxy/mutable-config/tool-data/shared/ucsc/chrom/?.len\", \"excln\": true, \"gff\": true, \"input_fasta\": null, \"repeat_source\": {\"source_type\": \"dfam\", \"__current_case__\": 0, \"species_source\": {\"species_from_list\": \"no\", \"__current_case__\": 1, \"species_name\": \"\"}}, \"xsmall\": true, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "4.1.5+galaxy0", "type": "tool", - "uuid": "0edf5e04-cc38-414c-9b57-117e919c435b", + "uuid": "e6c8e6a1-efe8-4291-b12b-5fdb3795b6ca", "when": null, "workflow_outputs": [ { - "label": "MultiQC on input dataset(s): Stats", - "output_name": "stats", - "uuid": "59dfba75-8658-4213-8fd9-b3ce5a916f14" + "output_name": "output_masked_genome", + "label": "RepeatMasker masked genome" }, { - "label": "MultiQC webpage", - "output_name": "html_report", - "uuid": "6d87436a-550e-4d76-a5da-d4463dfd4473" + "output_name": "output_log", + "label": "RepeatMasker output log" + }, + { + "output_name": "output_table", + "label": "RepeatMasker repeat statistics" + }, + { + "output_name": "output_repeat_catalog", + "label": "RepeatMasker repeat catalog" + }, + { + "output_name": "output_gff", + "label": "RepeatMasker repeat annotation" } ] } }, - "tags": [ - "CUTnRUN" - ], - "uuid": "98e9e34b-b203-43db-9a23-5fa72963fa6d", - "version": 1 + "tags": [], + "uuid": "f25be8fa-7823-456f-9707-a497703f48d7", + "version": 0 }, - "readme": "# CUT&RUN (and CUT&TAG) Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually CUT&RUN is Truseq and CUT&TAG is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera\n- reference_genome: this field will be adapted to the genomes available for bowtie2\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb\n- The BAM is filtered to keep only MAPQ30 and concordant pairs\n- The PCR duplicates are removed with Picard (only from version 0.6)\n- The BAM is converted to BED to enable macs2 to take both pairs into account\n- The peaks are called with macs2 which at the same time generates a coverage file (normalized or not).\n- The coverage file is converted to bigwig\n- A multiQC is run to have an overview of the QC\n", - "changelog": "# Changelog\n\n## [0.10] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.9] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.8] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.7] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/3.1.1.0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.6.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.6] 2023-10-19\n\nFix the remove duplicate step!\nIn all previous versions, due to an error, PCR duplicates were not removed.\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-03-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.3` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-06\nFirst release.\n" + "readme": "# RepeatMasking Workflow\n\nThis workflow uses RepeatModeler and RepeatMasker for genome analysis.\n\n- RepeatModeler is a software package for identifying and modeling de novo families of transposable elements (TEs). At the heart of RepeatModeler are three de novo repeat search programs (RECON, RepeatScout and LtrHarvest/Ltr_retriever) which use complementary computational methods to identify repeat element boundaries and family relationships from sequence data.\n\n- RepeatMasker is a program that analyzes DNA sequences for *interleaved repeats* and *low-complexity* DNA sequences. The result of the program is a detailed annotation of the repeats present in the query sequence, as well as a modified version of the query sequence in which all annotated repeats are present.\n\n## Input dataset for RepeatModeler\n- RepeatModeler requires a single input file, a genome in fasta format.\n\n\n## Outputs dataset for RepeatModeler\n- Two output files are generated:\n - summary file (.tbl)\n - fasta file containing alignments in order of appearance in the query sequence\n\n\n## Input dataset for RepeatMasker\n- ReapatMasker requires the fasta file generated by RepeatModeler\n\n## Outputs datasets for RepeatMasker\n- Five output files are generated:\n - a fasta file\n - .gff3 file\n - a table summarizing the repeated content of the sequence analyzed\n - a file with statistics related to the repeated content of the sequence analyzed\n - a summary of the mutation sites found and the order of grouping\n \n", + "changelog": "# Changelog\n\n## [0.1]\n\nInitial version of the RepeatMasking workflow for genomic sequencing data." } ], - "path": "./workflows/epigenetics/cutandrun" + "path": "./workflows/repeatmasking" }, { "version": 1.2, @@ -7251,9 +8611,9 @@ "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/chipseq-sr.ga", + "primaryDescriptorPath": "/cutandrun.ga", "testParameterFiles": [ - "/chipseq-sr-tests.yml" + "/cutandrun-tests.yml" ], "authors": [ { @@ -7263,7 +8623,7 @@ ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow takes as input a collection of fastqs (single reads). Remove adapters with cutadapt, map with bowtie2. Keep MAPQ30. MACS2 for bam with fixed extension or model.", + "annotation": "This workflow take as input a collection of paired fastq. Remove adapters with cutadapt, map pairs with bowtie2 allowing dovetail. Keep MAPQ30 and concordant pairs. BAM to BED. MACS2 with \"ATAC\" parameters.", "creator": [ { "class": "Person", @@ -7273,45 +8633,45 @@ ], "format-version": "0.1", "license": "MIT", - "release": "0.9", - "name": "ChIPseq_SR", + "release": "0.12", + "name": "CUTandRUN", "steps": { "0": { - "annotation": "Should be a collection with ChIPseq fastqs", + "annotation": "Should be a paired collection with CUT and RUN fastqs", "content_id": null, "errors": null, "id": 0, "input_connections": {}, "inputs": [ { - "description": "Should be a collection with ChIPseq fastqs", - "name": "SR fastq input" + "description": "Should be a paired collection with CUT and RUN fastqs", + "name": "PE fastq input" } ], - "label": "SR fastq input", + "label": "PE fastq input", "name": "Input dataset collection", "outputs": [], "position": { "left": 0, - "top": 0 + "top": 268 }, "tool_id": null, - "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list:paired\"}", "tool_version": null, "type": "data_collection_input", - 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"uuid": "fb066848-43df-412a-9767-9613bac7d961", + "uuid": "0edf5e04-cc38-414c-9b57-117e919c435b", "when": null, "workflow_outputs": [ - { - "label": "MultiQC webpage", - "output_name": "html_report", - "uuid": "2167289f-6c78-479a-8d3b-95caf11d0c4e" - }, { "label": "MultiQC on input dataset(s): Stats", "output_name": "stats", - "uuid": "d4c3e0a7-d5b7-4307-8669-0254a3723ce0" + "uuid": "59dfba75-8658-4213-8fd9-b3ce5a916f14" + }, + { + "label": "MultiQC webpage", + "output_name": "html_report", + "uuid": "6d87436a-550e-4d76-a5da-d4463dfd4473" } ] } }, "tags": [ - "ChIP" + "CUTnRUN" ], - "uuid": "fe6bda9f-1fc2-4a86-bf8d-e779c79466fc", + "uuid": "98e9e34b-b203-43db-9a23-5fa72963fa6d", "version": 1 }, - "readme": "# ChIP-seq single-read Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of fastqsanger files.\n\n## Inputs values\n\n- adapters sequence_forward: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30.\n- The peaks are called with MACS2 with a fixed extension of 200bp which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n", - "changelog": "# Changelog\n\n## [0.9] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.8] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.7] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-18\nFirst release.\n" + "readme": "# CUT&RUN (and CUT&TAG) Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapter sequences: this depends on the library preparation. Usually CUT&RUN is Truseq and CUT&TAG is Nextera. If you don't know, use FastQC to determine if it is Truseq or Nextera\n- reference_genome: this field will be adapted to the genomes available for bowtie2\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb\n- The BAM is filtered to keep only MAPQ30 and concordant pairs\n- The PCR duplicates are removed with Picard (only from version 0.6)\n- The BAM is converted to BED to enable macs2 to take both pairs into account\n- The peaks are called with macs2 which at the same time generates a coverage file (normalized or not).\n- The coverage file is converted to bigwig\n- A multiQC is run to have an overview of the QC\n", + "changelog": "# Changelog\n\n## [0.12] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n\n## [0.11] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.30.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.31.1+galaxy0`\n\n## [0.10] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.9] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.8] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.7] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/3.1.1.0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.6.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.6] 2023-10-19\n\nFix the remove duplicate step!\nIn all previous versions, due to an error, PCR duplicates were not removed.\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-03-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.3` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-06\nFirst release.\n" } ], - "path": "./workflows/epigenetics/chipseq-sr" + "path": "./workflows/epigenetics/cutandrun" }, { "version": 1.2, "workflows": [ { - "name": "hic-fastq-to-cool-hicup-cooler", + "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/hic-fastq-to-cool-hicup-cooler.ga", + "primaryDescriptorPath": "/chipseq-sr.ga", "testParameterFiles": [ - "/hic-fastq-to-cool-hicup-cooler-tests.yml" + "/chipseq-sr-tests.yml" ], "authors": [ { @@ -7979,7 +9494,7 @@ ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow takes as input a collection of paired fastq. It uses HiCUP to go from fastq to validPair file using the middle of the fragment as coordinates. The pairs are filtered for MAPQ and sorted by cooler to generate a tabix dataset. Cooler is used to generate a balanced cool file to the desired resolution.", + "annotation": "This workflow takes as input a collection of fastqs (single reads). Remove adapters with cutadapt, map with bowtie2. Keep MAPQ30. MACS2 for bam with fixed extension or model.", "creator": [ { "class": "Person", @@ -7989,1259 +9504,746 @@ ], "format-version": "0.1", "license": "MIT", - "release": "0.3", - "name": "Hi-C_fastqToCool_hicup_cooler", + "release": "0.11", + "name": "ChIPseq_SR", "steps": { "0": { - "annotation": "Should be a paired collection with Hi-C fastqs", + "annotation": "Should be a collection with ChIPseq fastqs", "content_id": null, "errors": null, "id": 0, "input_connections": {}, "inputs": [ { - "description": "Should be a paired collection with Hi-C fastqs", - "name": "PE fastq input" + "description": "Should be a collection with ChIPseq fastqs", + "name": "SR fastq input" } ], - "label": "PE fastq input", + "label": "SR fastq input", "name": "Input dataset collection", "outputs": [], "position": { "left": 0, - "top": 101.53334045410156 + "top": 0 }, "tool_id": null, - "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list:paired\"}", + "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", "tool_version": null, "type": "data_collection_input", - "uuid": "30fe3d0f-541a-478a-b57d-a43c0c16ccad", + "uuid": "e09c0852-1db3-4a68-b88c-1b94c205cb6c", "when": null, "workflow_outputs": [] }, "1": { - "annotation": "only use genome ids which have bowtie2 indexes", + "annotation": "Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC ", "content_id": null, "errors": null, "id": 1, "input_connections": {}, "inputs": [ { - "description": "only use genome ids which have bowtie2 indexes", - "name": "genome name" + "description": "Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC ", + "name": "adapter_forward" } ], - "label": "genome name", + "label": "adapter_forward", "name": "Input parameter", "outputs": [], "position": { - "left": 39.01666259765625, - "top": 171.5 + "left": 39.0333251953125, + "top": 77.44999694824219 }, "tool_id": null, - "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "45194ed6-a1e9-4248-8d3a-f51febc36d61", + "uuid": "30c1d867-5e73-4348-8969-848f58d94015", "when": null, "workflow_outputs": [] }, "2": { - "annotation": "Restriction enzyme used e.g. A^GATCT,BglII. Some Hi-C protocols may use several enzymes. To specify several enzymes, use the ':' to separate them e.g. A^GATCT,BglII:A^AGCTT,HindIII:^GATC,DpnII. HiCUP accomodates N in restriction enzyme: e.g. :A^ANCTT", + "annotation": "reference_genome", "content_id": null, "errors": null, "id": 2, "input_connections": {}, "inputs": [ { - "description": "Restriction enzyme used e.g. A^GATCT,BglII. Some Hi-C protocols may use several enzymes. To specify several enzymes, use the ':' to separate them e.g. A^GATCT,BglII:A^AGCTT,HindIII:^GATC,DpnII. HiCUP accomodates N in restriction enzyme: e.g. :A^ANCTT", - "name": "Restriction enzyme" + "description": "reference_genome", + "name": "reference_genome" } ], - "label": "Restriction enzyme", + "label": "reference_genome", "name": "Input parameter", "outputs": [], "position": { - "left": 71.98333740234375, - "top": 246.5 + "left": 62.7833251953125, + "top": 169.9666748046875 }, "tool_id": null, - "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "ec011ceb-c601-464f-8661-ca9c0b335bb5", + "uuid": "0119d669-7ce9-46fd-ba6f-3efd92dfb7f2", "when": null, "workflow_outputs": [] }, "3": { - "annotation": "Hi-C protocol did NOT include a fill-in of sticky ends prior to re-ligation and therefore reads shall be truncated at the restriction site sequence", + "annotation": "Used by MACS2: H. sapiens: 2700000000, M. musculus: 1870000000, D. melanogaster: 120000000, C. elegans: 90000000", "content_id": null, "errors": null, "id": 3, "input_connections": {}, "inputs": [ { - "description": "Hi-C protocol did NOT include a fill-in of sticky ends prior to re-ligation and therefore reads shall be truncated at the restriction site sequence", - "name": "No fill-in" + "description": "Used by MACS2: H. sapiens: 2700000000, M. musculus: 1870000000, D. melanogaster: 120000000, C. elegans: 90000000", + "name": "effective_genome_size" } ], - "label": "No fill-in", + "label": "effective_genome_size", "name": "Input parameter", "outputs": [], "position": { - "left": 98.433349609375, - "top": 332 + "left": 106.23333740234375, + "top": 262.3999938964844 }, "tool_id": null, - "tool_state": "{\"parameter_type\": \"boolean\", \"optional\": false}", + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "11e64d82-c022-48b2-b616-076bfcdb14ad", + "uuid": "5bb3b3df-60ab-4ec7-88e4-476be547ffbf", "when": null, "workflow_outputs": [] }, "4": { - "annotation": "can be set to 0 for no filtering", + "annotation": "Whether you want to have a profile normalized as Signal to Million Reads", "content_id": null, "errors": null, "id": 4, "input_connections": {}, "inputs": [ { - "description": "can be set to 0 for no filtering", - "name": "minimum MAPQ" + "description": "Whether you want to have a profile normalized as Signal to Million Reads", + "name": "normalize_profile" } ], - "label": "minimum MAPQ", + "label": "normalize_profile", "name": "Input parameter", "outputs": [], "position": { - "left": 143.9666748046875, - "top": 401.5333251953125 + "left": 163.95545543674132, + "top": 359.9555974960296 }, "tool_id": null, - "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_state": "{\"parameter_type\": \"boolean\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "748c8800-5bef-41b7-b2cf-6d6a57c0eb70", + "uuid": "b89b796d-df4f-416f-8bc4-4f1951efa449", "when": null, "workflow_outputs": [] }, "5": { - "annotation": "For example 10000 for 10kb", - "content_id": null, + "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0", "errors": null, "id": 5, - "input_connections": {}, + "input_connections": { + "library|input_1": { + "id": 0, + "output_name": "output" + }, + "library|r1|adapters_0|adapter_source|adapter": { + "id": 1, + "output_name": "output" + } + }, "inputs": [ { - "description": "For example 10000 for 10kb", - "name": "Bin size in bp" + "description": "runtime parameter for tool Cutadapt", + "name": "library" + } + ], + "label": "Cutadapt (remove adapter + bad quality bases)", + "name": "Cutadapt", + "outputs": [ + { + "name": "out1", + "type": "fastqsanger" + }, + { + "name": "report", + "type": "txt" } ], - "label": "Bin size in bp", - "name": "Input parameter", - "outputs": [], "position": { - "left": 186, - "top": 491.0333251953125 + "left": 423.31666564941406, + "top": 80.16667175292969 }, - "tool_id": null, - "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", - "tool_version": null, - "type": "parameter_input", - "uuid": "1e019ddf-171c-4247-ab11-0d2cdbe10f6a", + "post_job_actions": { + "HideDatasetActionout1": { + "action_arguments": {}, + "action_type": "HideDatasetAction", + "output_name": "out1" + }, + "HideDatasetActionreport": { + "action_arguments": {}, + "action_type": "HideDatasetAction", + "output_name": "report" + }, + "RenameDatasetActionreport": { + "action_arguments": { + "newname": "cutadapt report" + }, + "action_type": "RenameDatasetAction", + "output_name": "report" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0", + "tool_shed_repository": { + "changeset_revision": "aa784cb3810d", + "name": "cutadapt", + "owner": "lparsons", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__job_resource\": {\"__current_case__\": 0, \"__job_resource__select\": \"no\"}, \"adapter_options\": {\"action\": \"trim\", \"error_rate\": \"0.1\", \"no_indels\": false, \"times\": \"1\", \"overlap\": \"3\", \"match_read_wildcards\": false, \"no_match_adapter_wildcards\": true, \"revcomp\": false}, \"filter_options\": {\"discard_trimmed\": false, \"discard_untrimmed\": false, \"minimum_length\": \"15\", \"minimum_length2\": null, \"maximum_length\": null, \"maximum_length2\": null, \"max_n\": null, \"max_expected_errors\": null, \"max_average_error_rate\": null, \"discard_casava\": false, \"pair_filter\": \"any\"}, \"library\": {\"type\": \"single\", \"__current_case__\": 0, \"input_1\": {\"__class__\": \"ConnectedValue\"}, \"r1\": {\"adapters\": [{\"__index__\": 0, \"adapter_source\": {\"adapter_source_list\": \"user\", \"__current_case__\": 0, \"adapter_name\": \"Please use: For R1: - For Nextera: CTGTCTCTTATACACATCTCCGAGCCCACGAGAC - For TrueSeq: GATCGGAAGAGCACACGTCTGAACTCCAGTCAC or AGATCGGAAGAGCACACGTCTGAACTCCAGTCAC\", \"adapter\": {\"__class__\": \"ConnectedValue\"}}, \"single_noindels\": false}], \"front_adapters\": [], \"anywhere_adapters\": []}}, \"other_trimming_options\": {\"cut\": \"0\", \"cut2\": \"0\", \"quality_cutoff\": \"30\", \"quality_cutoff2\": \"\", \"nextseq_trim\": \"0\", \"trim_n\": false, \"poly_a\": false, \"shorten_options\": {\"shorten_values\": \"False\", \"__current_case__\": 1}, \"shorten_options_r2\": {\"shorten_values_r2\": \"False\", \"__current_case__\": 1}}, \"output_selector\": [\"report\"], \"read_mod_options\": {\"strip_suffix\": \"\", \"length_tag\": \"\", \"rename\": \"\", \"zero_cap\": false}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "4.9+galaxy0", + "type": "tool", + "uuid": "c7846b4c-54fb-458e-982e-c0d8358a9f5d", "when": null, "workflow_outputs": [] }, "6": { - "annotation": "Nothing means genome-wide, '--cis-only' means only Cis interactions, '--trans-only' means only Trans interactions", - 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If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Reads.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30.\n- The peaks are called with MACS2 with a fixed extension of 200bp which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n", + "changelog": "# Changelog\n\n## [0.11] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n\n## [0.10] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy1`\n\n## [0.9] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.8] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.7] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-18\nFirst release.\n" + } + ], + "path": "./workflows/epigenetics/chipseq-sr" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "hic-fastq-to-cool-hicup-cooler", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/hic-fastq-to-cool-hicup-cooler.ga", + "testParameterFiles": [ + "/hic-fastq-to-cool-hicup-cooler-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a collection of paired fastq. 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"tool_version": "3.8+galaxy2", - "type": "tool", - "uuid": "d8b80397-70dc-4522-8a12-948b1107ac8d", - "when": null, - "workflow_outputs": [ - { - "label": "plot with pyGenomeTracks", - "output_name": "outFileName", - "uuid": "27b9c4ea-2a6a-4477-bd5e-7f69a89d69fa" - } - ] - } - }, - "tags": [ - "Hi-C" - ], - "uuid": "2196fbff-317e-437d-a022-696a1f95a850", - "version": 4 - }, - "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", - "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" - }, - { - "name": "chic-fastq-to-cool-hicup-cooler", - "subclass": "Galaxy", - "publish": true, - "primaryDescriptorPath": "/chic-fastq-to-cool-hicup-cooler.ga", - "testParameterFiles": [ - "/chic-fastq-to-cool-hicup-cooler-tests.yml" - ], - "authors": [ - { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" - } - ], - "definition": { - "a_galaxy_workflow": "true", - "annotation": "This workflow take as input a collection of paired fastq. 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"description": "For example: chr2", - "name": "capture region (chromosome)" + "description": "You can use your region of interest or a region known for high level of insulation for example HoxD locus:\nhg19: chr2:175,689,620-178,604,461\nhg38: chr2:174,692,032-177,585,317\nmm10: chr2:73,779,626-75,669,724\nmm39: ", + "name": "region for matrix plotting" } ], - "label": "capture region (chromosome)", + "label": "region for matrix plotting", "name": "Input parameter", "outputs": [], "position": { - "left": 279.5, - "top": 622.6216799999941 + "left": 282, + "top": 710 }, "tool_id": null, "tool_state": "{\"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "386a8e30-aab6-4168-877e-581b883928e5", + "uuid": "ea792308-f30e-49c4-9fec-8de03f45f64c", "when": null, "workflow_outputs": [] }, "8": { - "annotation": "For example: 72402000", - "content_id": null, - "errors": null, - "id": 8, - "input_connections": {}, - "inputs": [ - { - "description": "For example: 72402000", - 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"label": "final_plot", + "label": "final plot", "name": "pyGenomeTracks", "outputs": [ { @@ -10594,8 +11381,8 @@ } ], "position": { - "left": 1673, - "top": 806.6216799999941 + "left": 1295, + "top": 693 }, "post_job_actions": { "RenameDatasetActionoutFileName": { @@ -10616,13 +11403,13 @@ "tool_state": "{\"global_args\": {\"title\": \"\", \"fontsize\": \"12\", \"dpi\": \"72\", \"width\": \"40.0\", \"plotWidth\": null, \"height\": null, \"trackLabelFraction\": \"0.05\", \"trackLabelHAlign\": \"left\", \"decreasingXAxis\": false}, \"image_file_format\": \"png\", \"region\": {\"__class__\": \"ConnectedValue\"}, \"tracks\": [{\"__index__\": 0, \"track_file_style_conditional\": {\"track_file_style_selector\": \"hic_matrix_option\", \"__current_case__\": 0, \"title\": \"\", \"matrix_h5_cooler_multiple\": {\"__class__\": \"ConnectedValue\"}, \"colormap\": \"RdYlBu_r\", \"min_value\": null, \"max_value\": null, \"depth\": \"8000000\", \"transform\": \"no\", \"height_matrix\": null, \"show_masked_bins\": false, \"boundaries_file\": {\"__class__\": \"RuntimeValue\"}, \"scale_factor\": \"1.0\", \"rasterize\": true, \"invert_orientation\": false, \"spacer_height\": null}}, {\"__index__\": 1, \"track_file_style_conditional\": {\"track_file_style_selector\": \"xaxis_option\", \"__current_case__\": 13, \"title\": \"\", \"fontsize\": null, \"xaxis_where\": \"bottom\", \"spacer_height\": null}}], \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "3.8+galaxy2", "type": "tool", - "uuid": "dfbe45de-b2a7-479e-b717-29ec5b31379e", + "uuid": "d8b80397-70dc-4522-8a12-948b1107ac8d", "when": null, "workflow_outputs": [ { "label": "plot with pyGenomeTracks", "output_name": "outFileName", - "uuid": "32a70740-19aa-463d-a280-6394156bd412" + "uuid": "27b9c4ea-2a6a-4477-bd5e-7f69a89d69fa" } ] } @@ -10630,19 +11417,19 @@ "tags": [ "Hi-C" ], - "uuid": "2a89cbe4-a69f-4bff-9465-2e04b0217e35", + "uuid": "2196fbff-317e-437d-a022-696a1f95a850", "version": 4 }, "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" }, { - "name": "hic-juicermediumtabix-to-cool-cooler", + "name": "chic-fastq-to-cool-hicup-cooler", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/hic-juicermediumtabix-to-cool-cooler.ga", + "primaryDescriptorPath": "/chic-fastq-to-cool-hicup-cooler.ga", "testParameterFiles": [ - "/hic-juicermediumtabix-to-cool-cooler-tests.yml" + "/chic-fastq-to-cool-hicup-cooler-tests.yml" ], "authors": [ { @@ -10652,7 +11439,7 @@ ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow uses as input a collection of juicer medium tabix files and a genome name. It builds balanced cool file to the desired resolution.", + "annotation": "This workflow take as input a collection of paired fastq. It uses HiCUP to go from fastq to validPair file. The pairs are filtered for MAPQ and for the region captured. Then, they are sorted by cooler to generate a tabix dataset. 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The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", - "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" - }, - { - "name": "hic-fastq-to-pairs-hicup", - "subclass": "Galaxy", - "publish": true, - "primaryDescriptorPath": "/hic-fastq-to-pairs-hicup.ga", - "testParameterFiles": [ - "/hic-fastq-to-pairs-hicup-tests.yml" - ], - "authors": [ - { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" - } - ], - "definition": { - "a_galaxy_workflow": "true", - "annotation": "This workflow takes as input a collection of paired fastq. 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juicebox format", + "uuid": "bc19676e-9619-43b9-9c21-bc3c31fad3b2" + }, { "label": "valid pairs in juicebox format MAPQ filtered", - "output_name": "out_file1", - "uuid": "b08373c7-59b2-4ae3-90b7-7c9a05ca81b7" - } - ] - } - }, - "tags": [ - "Hi-C" - ], - "uuid": "48f579ea-eaac-49ee-b38f-93c82f8b7d76", - "version": 2 - }, - "readme": "# Hi-C (hic_fastq_to_cool_hicup_cooler) and region capture Hi-C (chic_fastq_to_cool_hicup_cooler) Workflows\n\nThis can also be used for Hi-ChIP experiments, in that case the output with `matrix with iced values` is ignored and the matrix to use is `matrix with raw values`.\n\n## Input datasets\n\n- The workflow needs a list of dataset pairs of fastqsanger.\n\n## Input values\n\n- genome name: suggested from the bowtie2 indices, it is used to map and build the list of bins.\n- restriction enzyme: Restriction enzyme used e.g. A^GATCT,BglII. The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", - "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" - 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The identifiers of your bigwigs must be like:\n - whatever_sample1_identificationOfReplicate1\n - whatever_sample1_identificationOfReplicate2\n - ...\n - whatever_sample2_identificationOfReplicate1\n - whatever_sample2_identificationOfReplicate2\n - ...\n\n## Inputs values\n\n- bin_size: this is used when average of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs. I suggest 5bp for RNA-seq and 50bp for other applications.\n\n## Processing\n\n- The workflow will split identifiers between everything which is before the last underscore which will be the *sample* and everything which is after the last underscore which will be the *replicate identifier*. 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The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", + "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" + }, + { + "name": "hic-juicermediumtabix-to-cool-cooler", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/hic-juicermediumtabix-to-cool-cooler.ga", + "testParameterFiles": [ + "/hic-juicermediumtabix-to-cool-cooler-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow uses as input a collection of juicer medium tabix files and a genome name. 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The '^' is used to express where the enzyme cuts.\n- No fill-in: If you used a biotin fill-in protocol, put this to false, else, put it to true.\n- minimum MAPQ: Filtering to apply to pairs you want to keep in your matrix, set it to 0 to not apply filtering (HiCUP already filter for uniquely mapped or MAPQ30).\n- Bin size in bp: Used to generate your first matrix but you will be able to rerun the subworkflow `hic_tabix_to_cool_cooler` to get other resolutions.\n- Interactions to consider to calculate weights in normalization step: this is a parameter for the last correction step (ICE).\n\nFor the region capture workflow:\n\n- chromosome, start and end positions of the capture region\n\nFor the Hi-C workflow:\n\n- region to use in pyGenomeTracks to check the matrices.\n\n## Processing\n\n- Reads are processed with HiCUP which comprises these steps:\n - Truncation of reads for the religation motif\n - Mapping of mates independently with bowtie2\n - Pairing the mates when both mates are uniquely mapped or MAPQ30\n - Filtering the pairs for undigested, self-ligated...\n - Removing duplicates\n- The output BAM file is converted to medium juicer format: ` ` where str = strand (0 for forward, anything else for reverse) and pos is the middle of the fragment.\n- The pairs are filtered for MAPQ if specified.\n- For the region capture Hi-C workflow the pairs are filtered for both mates in the captured region.\n- The filtered pairs are sorted and indexed with cooler_csort.\n- The pairs are loaded into a matrix of the given resolution and balanced with cooler.\n- A final plot is made with pyGenomeTracks using the balanced matrices on the region provided or the capture region.\n\n## Subworkflows\n\nThere are 2 subworkflows: `hic_tabix_to_cool_cooler` and `hic_fastq_to_pairs_hicup.ga`.\n\n### hic_tabix_to_cool_cooler\n\nThis first subworkflow can be used to generate matrices to different resolutions using one of the output of the full workflow (`valid pairs filtered and sorted`).\n\nIf the dataset are still in galaxy (format: juicer_medium_tabix.gz), the workflow can be run directly.\n\nIf the dataset is not anymore in galaxy, you need to upload and specify the datatype as: juicer_medium_tabix.gz\n\n### hic_fastq_to_pairs_hicup\n\nThe second subworkflow has no real reason to be launched by itself except for QC tests.\n\nIf you want to run the first subworkflow from these results:\n\n- You first need to filter the pairs (`valid pairs in juicebox format MAPQ filtered`) for the capture region if relevent using the tool Filter1 (**Filter** data on any column using simple expressions) with the condition `(c3=='chr2' and c4<180000000 and c4>170000000) and (c7==\"chr2\" and c8<180000000 and c8>170000000)` if your capture region is chr2:170000000-180000000.\n- Then you need to run cooler_csort (**cooler csort with tabix** Sort and index a contact list.) with as input the `valid pairs in juicebox format MAPQ filtered` or the output of the previous step and for \"Format of your input file\" use \"Juicer Medium Format\".\n\nThe output of `cooler_csort` can be used as input of the first subworkflow.\n", + "changelog": "# Changelog\n\n## [0.3] 2023-09-08\n\n### Update tools\n- all cooler tools were updated from 0.8.11 to 0.9.3\n- pyGenomeTracks was updated from 3.7 to 3.8\n\n## [0.2.1] 2023-09-01 Bug fix\n\nFix dockstore (workflows are the same)\n\n## [0.2] 2023-02-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pygenometracks/pygenomeTracks/3.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup_hicup/hicup_hicup/0.9.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.8.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hicup2juicer/hicup2juicer/0.9.2+galaxy0`\n\n### Manual update\n- Get fragment id in valid pairs file.\n- Use the middle of the fragment instead of 5' of the read in the valid pairs file.\n\n## [0.1] 2023-01-16\n\nFirst release.\n" + }, + { + "name": "hic-fastq-to-pairs-hicup", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/hic-fastq-to-pairs-hicup.ga", + "testParameterFiles": [ + "/hic-fastq-to-pairs-hicup-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input a collection of paired fastq. 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"toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0", + "errors": null, + "id": 3, + "input_connections": { + "advancedOpt|binSize": { + "id": 1, + "output_name": "output" + }, + "bigwigs": { + "id": 2, + "output_name": "output" + } + }, + "inputs": [ + { + "description": "runtime parameter for tool bigwigAverage", + "name": "advancedOpt" + } + ], + "label": "average bigwigs from different replicates", + "name": "bigwigAverage", + "outputs": [ + { + "name": "outFileName", + "type": "bigwig" + } + ], + "position": { + "left": 474, + "top": 11.5 + }, + "post_job_actions": {}, + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0", + "tool_shed_repository": { + "changeset_revision": "4a53856a5b85", + "name": "deeptools_bigwig_average", + "owner": "bgruening", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"advancedOpt\": {\"showAdvancedOpt\": \"yes\", \"__current_case__\": 1, \"binSize\": {\"__class__\": \"ConnectedValue\"}, \"skipNAs\": false, \"scaleFactors\": \"1\", \"blackListFileName\": {\"__class__\": \"RuntimeValue\"}}, \"bigwigs\": {\"__class__\": \"ConnectedValue\"}, \"outFileFormat\": \"bigwig\", \"region\": \"\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "3.5.4+galaxy0", + "type": "tool", + "uuid": "f63daf4e-ce9f-4301-be74-e4c263b6e88b", + "when": null, + "workflow_outputs": [ + { + "label": "average_bigwigs", + "output_name": "outFileName", + "uuid": "19023604-eee1-4099-b1c2-abe3de93b3f3" + } + ] + } + }, + "tags": [], + "uuid": "c6ed4b0e-d719-4997-9860-ba99488ec332", + "version": 6 + }, + "readme": "# Average Bigwig between replicates\n\nThis workflow is very useful when you processed multiple samples in collections and you want to generate an average coverage per condition.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of bigwigs (normalized). The identifiers of your bigwigs must be like:\n - whatever_sample1_identificationOfReplicate1\n - whatever_sample1_identificationOfReplicate2\n - ...\n - whatever_sample2_identificationOfReplicate1\n - whatever_sample2_identificationOfReplicate2\n - ...\n\n## Inputs values\n\n- bin_size: this is used when average of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs. I suggest 5bp for RNA-seq and 50bp for other applications.\n\n## Processing\n\n- The workflow will split identifiers between everything which is before the last underscore which will be the *sample* and everything which is after the last underscore which will be the *replicate identifier*. And restructure the collection as list:list:\n - whatever_sample1:\n - identificationOfReplicate1\n - identificationOfReplicate2\n - ...\n - whatever_sample2:\n - identificationOfReplicate1\n - identificationOfReplicate2\n - ---\n - ...\n- Then it will average bigwigs into each inner list\n\n## Outputs\n\n- The output is a collection of bigwig datasets like:\n - whatever_sample1\n - whatever_sample2\n - ...\n", + "changelog": "# Changelog\n\n## [0.2] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.1] 2023-09-22\nFirst release.\n" + } + ], + "path": "./workflows/epigenetics/average-bigwig-between-replicates" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "consensus-peaks-chip-sr", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/consensus-peaks-chip-sr.ga", + "testParameterFiles": [ + "/consensus-peaks-chip-sr-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow takes as input SR BAM from ChIP-seq. It calls peaks on each replicate and intersect them. In parallel, each BAM is subsetted to smallest number of reads. Peaks are called using all subsets combined. Only peaks called using a combination of all subsets which have summits intersecting the intersection of at least x replicates will be kept.", + "comments": [ + { + "child_steps": [ + 5, + 8, + 12 + ], + "color": "blue", + "data": { + "title": "Get a BED with intersection of at least x rep" + }, + "id": 0, "position": [ - 687.5, - 395.8 + 767.4, + 0.0 ], "size": [ - 498.9, - 345.5 + 525.4, + 382.7 ], "type": "frame" }, @@ -13015,35 +13890,34 @@ "data": { "title": "Downsample input BAM to get the same number of reads" }, - "id": 1, + "id": 2, "position": [ - 180.2, - 744.1 + 310.4, + 898.0 ], "size": [ - 1889, - 379 + 2000, + 403 ], "type": "frame" }, { "child_steps": [ - 5, - 8, - 12 + 9, + 13 ], - "color": "blue", + "color": "green", "data": { - "title": "Get a BED with intersection of at least x rep" + "title": "Get the average coverage" }, - "id": 0, + "id": 1, "position": [ - 764.8, - 0.0 + 721.4, + 539.8 ], "size": [ - 531.7, - 370.1 + 548.7, + 332 ], "type": "frame" } @@ -13057,8 +13931,8 @@ ], "format-version": "0.1", "license": "MIT", - "release": "1.0", - "name": "Get Confident Peaks From ChIP_PE replicates", + "release": "1.1", + "name": "Get Confident Peaks From ChIP_SR replicates", "steps": { "0": { "annotation": "A collection with n replicates. 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"tool_version": "2.30.0+galaxy1", + "tool_version": "2.31.1+galaxy0", "type": "tool", "uuid": "d6183a41-f78c-49fc-b826-f8aa95ff84cb", "when": null, @@ -14139,8 +15013,8 @@ } ], "position": { - "left": 2091.738158489414, - "top": 26.470097442576304 + "left": 2315.5733416696335, + "top": 16.13231218303406 }, "post_job_actions": { "HideDatasetActionstats": { @@ -14191,7 +15065,7 @@ ], "position": { "left": 1874.401877544738, - "top": 306.13125220702955 + "top": 319.9312522070295 }, "post_job_actions": { "HideDatasetActionout_file1": { @@ -14230,7 +15104,7 @@ ], "position": { "left": 2104.095825078475, - "top": 400.23050506519184 + "top": 414.0305050651918 }, "post_job_actions": { "HideDatasetActionout_file1": { @@ -14269,7 +15143,7 @@ ], "position": { "left": 2336.462697917632, - "top": 421.3788245160598 + "top": 435.17882451605976 }, "post_job_actions": { "ChangeDatatypeActionoutfile": { @@ -14311,19 +15185,19 @@ "tags": [ "ATAC-seq" ], - "uuid": "a2f66906-e9e3-42f9-8629-390017ed2db0", - "version": 6 + "uuid": "f71eee25-8402-41da-8284-5298656ab379", + "version": 2 }, "readme": "# Consensus peaks Workflow\n\nThe goal of this workflow is to get a list of confident peaks with summits from n replicates.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of datasets with n BAM where PCR duplicates have been removed (the workflow also works for nested list if you have multiple conditions each with multiple replicates).\n\n## Inputs values\n\n- Minimum number of overlap: Minimum number of replicates into which the final summit should be present.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- bin_size: this is the bin sized used to compute the average of normalized profiles. Large values will allow to have a smaller output file but with less resolution while small values will increase computation time and size of the output file to produce a more resolutive bigwig.\n\n## Strategy summary\n\nHere is a generated example to highlight the strategy:\n![strategy](./strategy.png)\n\n## Processing\n\n- The workflow will:\n - first part:\n - call peaks and compute normalized coverage on each BAM individually\n - average normalized profiles\n - compute the intersection between all peaks and filter when at least x replicate overlaps\n - second part:\n - subset all BAM to get the same number of reads\n - call peaks on all subsetted BAM combined\n - finally, keep only peaks from the second part that have summits overlapping the filtered intersection of the first part.\n", - "changelog": "# Changelog\n\n## [1.0] 2024-05-01\n\n### Changed\nThe workflow changed as it accepts now more than 2 replicates and has a new parameter to define what is the minimum number of replicates where the summit should be found.\nThe workflow for ATAC and CUT&RUN changed the input datatype as now a BAM is required instead of a BED.\n\n## [0.7] 2024-04-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.6] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.5] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0`\n\n## [0.4] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.3] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.1] 2023-08-31\nFirst release.\n" + "changelog": "# Changelog\n\n## [1.1] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.30.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.31.1+galaxy0`\n\n## [1.0] 2024-05-01\n\n### Changed\nThe workflow changed as it accepts now more than 2 replicates and has a new parameter to define what is the minimum number of replicates where the summit should be found.\nThe workflow for ATAC and CUT&RUN changed the input datatype as now a BAM is required instead of a BED.\n\n## [0.7] 2024-04-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.6] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.5] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0`\n\n## [0.4] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.3] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.1] 2023-08-31\nFirst release.\n" }, { - "name": "consensus-peaks-atac-cutandrun", + "name": "consensus-peaks-chip-pe", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/consensus-peaks-atac-cutandrun.ga", + "primaryDescriptorPath": "/consensus-peaks-chip-pe.ga", "testParameterFiles": [ - "/consensus-peaks-atac-cutandrun-tests.yml" + "/consensus-peaks-chip-pe-tests.yml" ], "authors": [ { @@ -14333,74 +15207,74 @@ ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow takes as input BAM from ATAC-seq or CUT&RUN. It calls peaks on each replicate and intersect them. In parallel, each BAM is subsetted to smallest number of reads. Peaks are called using all subsets combined. Only peaks called using a combination of all subsets which have summits intersecting the intersection of at least x replicates will be kept.", + "annotation": "This workflow takes as input PE BAM from ChIP-seq. It calls peaks on each replicate and intersect them. In parallel, each BAM is subsetted to smallest number of reads. Peaks are called using all subsets combined. Only peaks called using a combination of all subsets which have summits intersecting the intersection of at least x replicates will be kept.", "comments": [ { "child_steps": [ - 5, - 8, - 11, - 12, - 15, - 16, - 17, - 18, - 19, - 20 + 9, + 13 ], - "color": "blue", + "color": "green", "data": { - "title": "Downsample input BAM to get the same number of reads" + "title": "Get the average coverage" }, "id": 2, "position": [ - 228, - 878.7 + 687.5, + 395.8 ], "size": [ - 1917.8, - 397.4 + 498.9, + 345.5 ], "type": "frame" }, { "child_steps": [ - 6, - 9, - 13 + 4, + 7, + 11, + 10, + 15, + 14, + 16, + 17, + 18, + 19 ], - "color": "blue", + "color": "none", "data": { - "title": "Get a BED with intersection of at least x rep" + "title": "Downsample input BAM to get the same number of reads" }, - "id": 0, + "id": 1, "position": [ - 776.6, - 0 + 180.2, + 744.1 ], "size": [ - 508.7, - 363 + 1889, + 379 ], "type": "frame" }, { "child_steps": [ - 10, - 14 + 5, + 8, + 12 ], - "color": "green", + "color": "blue", "data": { - "title": "Get the average coverage" + "title": "Get a BED with intersection of at least x rep" }, - "id": 1, + "id": 0, "position": [ - 647.1, - 523.9 + 764.8, + 0.0 ], "size": [ - 504.5, - 324 + 531.7, + 370.1 ], "type": "frame" } @@ -14414,27 +15288,27 @@ ], "format-version": "0.1", "license": "MIT", - "release": "1.0", - "name": "Get Confident Peaks From ATAC or CUTandRUN replicates", + "release": "1.1", + "name": "Get Confident Peaks From ChIP_PE replicates", "steps": { "0": { - "annotation": "A collection with n replicates. BAM should not have duplicates.", + "annotation": "A collection with n replicates. BAM should not have duplicates", "content_id": null, "errors": null, "id": 0, "input_connections": {}, "inputs": [ { - "description": "A collection with n replicates. BAM should not have duplicates.", - "name": "n rmDup BAM" + "description": "A collection with n replicates. BAM should not have duplicates", + "name": "n rmDup BAMPE" } ], - "label": "n rmDup BAM", + "label": "n rmDup BAMPE", "name": "Input dataset collection", "outputs": [], "position": { "left": 0, - "top": 194.74998779296874 + "top": 155.14998779296874 }, "tool_id": null, "tool_state": "{\"optional\": false, \"format\": [\"bam\"], \"tag\": \"\", \"collection_type\": \"list\"}", @@ -14461,7 +15335,7 @@ "outputs": [], "position": { "left": 25, - "top": 273.2 + "top": 233.6 }, "tool_id": null, "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", @@ -14488,7 +15362,7 @@ "outputs": [], "position": { "left": 39, - "top": 367.74791480468576 + "top": 328.1479148046858 }, "tool_id": null, "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", @@ -14515,7 +15389,7 @@ "outputs": [], "position": { "left": 57, - "top": 464.78123999999826 + "top": 425.1812399999983 }, "tool_id": null, "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", @@ -14526,55 +15400,10 @@ "workflow_outputs": [] }, "4": { - 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"top": 345.7312522070295 + "top": 306.13125220702955 }, "post_job_actions": { "HideDatasetActionout_file1": { @@ -15655,14 +16439,14 @@ "when": null, "workflow_outputs": [] }, - "26": { + "24": { "annotation": "", "content_id": "Cut1", "errors": null, - "id": 26, + "id": 24, "input_connections": { "input": { - "id": 25, + "id": 23, "output_name": "out_file1" } }, @@ -15677,7 +16461,7 @@ ], "position": { "left": 2104.095825078475, - "top": 439.8305050651918 + "top": 400.23050506519184 }, "post_job_actions": { "HideDatasetActionout_file1": { @@ -15694,14 +16478,14 @@ "when": null, "workflow_outputs": [] }, - "27": { + "25": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1", "errors": null, - "id": 27, + "id": 25, "input_connections": { "infile": { - "id": 26, + "id": 24, "output_name": "out_file1" } }, @@ -15716,7 +16500,7 @@ ], "position": { "left": 2336.462697917632, - "top": 460.9788245160598 + "top": 421.3788245160598 }, "post_job_actions": { "ChangeDatatypeActionoutfile": { @@ -15758,25 +16542,19 @@ "tags": [ "ATAC-seq" ], - "uuid": "f58371cd-2e2d-41da-b1ca-ef10f7330047", - "version": 13 + "uuid": "a2f66906-e9e3-42f9-8629-390017ed2db0", + "version": 6 }, "readme": "# Consensus peaks Workflow\n\nThe goal of this workflow is to get a list of confident peaks with summits from n replicates.\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of datasets with n BAM where PCR duplicates have been removed (the workflow also works for nested list if you have multiple conditions each with multiple replicates).\n\n## Inputs values\n\n- Minimum number of overlap: Minimum number of replicates into which the final summit should be present.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- bin_size: this is the bin sized used to compute the average of normalized profiles. Large values will allow to have a smaller output file but with less resolution while small values will increase computation time and size of the output file to produce a more resolutive bigwig.\n\n## Strategy summary\n\nHere is a generated example to highlight the strategy:\n![strategy](./strategy.png)\n\n## Processing\n\n- The workflow will:\n - first part:\n - call peaks and compute normalized coverage on each BAM individually\n - average normalized profiles\n - compute the intersection between all peaks and filter when at least x replicate overlaps\n - second part:\n - subset all BAM to get the same number of reads\n - call peaks on all subsetted BAM combined\n - finally, keep only peaks from the second part that have summits overlapping the filtered intersection of the first part.\n", - "changelog": "# Changelog\n\n## [1.0] 2024-05-01\n\n### Changed\nThe workflow changed as it accepts now more than 2 replicates and has a new parameter to define what is the minimum number of replicates where the summit should be found.\nThe workflow for ATAC and CUT&RUN changed the input datatype as now a BAM is required instead of a BED.\n\n## [0.7] 2024-04-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.6] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.5] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0`\n\n## [0.4] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.3] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.1] 2023-08-31\nFirst release.\n" - } - ], - "path": "./workflows/epigenetics/consensus-peaks" - }, - { - "version": 1.2, - "workflows": [ + "changelog": "# Changelog\n\n## [1.1] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.30.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_multiintersectbed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_intersectbed/2.31.1+galaxy0`\n\n## [1.0] 2024-05-01\n\n### Changed\nThe workflow changed as it accepts now more than 2 replicates and has a new parameter to define what is the minimum number of replicates where the summit should be found.\nThe workflow for ATAC and CUT&RUN changed the input datatype as now a BAM is required instead of a BED.\n\n## [0.7] 2024-04-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.6] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy1`\n\n## [0.5] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sorted_uniq/9.3+galaxy0`\n\n## [0.4] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.3] 2023-11-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n\n## [0.2] 2023-11-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.1] 2023-08-31\nFirst release.\n" + }, { - "name": "main", + "name": "consensus-peaks-atac-cutandrun", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/atacseq.ga", + "primaryDescriptorPath": "/consensus-peaks-atac-cutandrun.ga", "testParameterFiles": [ - "/atacseq-tests.yml" + "/consensus-peaks-atac-cutandrun-tests.yml" ], "authors": [ { @@ -15786,7 +16564,78 @@ ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow takes as input a collection of paired fastq. It will remove bad quality and adapters with cutadapt. Map with Bowtie2 end-to-end. Will remove reads on MT and unconcordant pairs and pairs with mapping quality below 30 and PCR duplicates. Will compute the pile-up on 5' +- 100bp. Will call peaks and count the number of reads falling in the 1kb region centered on the summit. Will compute 2 normalization for coverage: normalized by million reads and normalized by million reads in peaks. Will plot the number of reads for each fragment length.", + "annotation": "This workflow takes as input BAM from ATAC-seq or CUT&RUN. It calls peaks on each replicate and intersect them. In parallel, each BAM is subsetted to smallest number of reads. Peaks are called using all subsets combined. Only peaks called using a combination of all subsets which have summits intersecting the intersection of at least x replicates will be kept.", + "comments": [ + { + "child_steps": [ + 5, + 8, + 11, + 12, + 15, + 16, + 17, + 18, + 19, + 20 + ], + "color": "blue", + "data": { + "title": "Downsample input BAM to get the same number of reads" + }, + "id": 2, + "position": [ + 228, + 878.7 + ], + "size": [ + 1917.8, + 397.4 + ], + "type": "frame" + }, + { + "child_steps": [ + 6, + 9, + 13 + ], + "color": "blue", + "data": { + "title": "Get a BED with intersection of at least x rep" + }, + "id": 0, + "position": [ + 776.6, + 0 + ], + "size": [ + 508.7, + 363 + ], + "type": "frame" + }, + { + "child_steps": [ + 10, + 14 + ], + "color": "green", + "data": { + "title": "Get the average coverage" + }, + "id": 1, + "position": [ + 647.1, + 523.9 + ], + "size": [ + 504.5, + 324 + ], + "type": "frame" + } + ], "creator": [ { "class": "Person", @@ -15796,72 +16645,72 @@ ], "format-version": "0.1", "license": "MIT", - "release": "0.14", - "name": "ATACseq", + "release": "1.1", + "name": "Get Confident Peaks From ATAC or CUTandRUN replicates", "steps": { "0": { - "annotation": "Should be a paired collection with ATAC-seq fastqs", + "annotation": "A collection with n replicates. 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"changelog": "# Changelog\n\n## [0.9] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.8] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.7] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.6.1] 2024-03-14\n\nFix bug introduced in 0.6: the second adapter sequence was not used.\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## 2022-10-20\nChIPseq_PE has been renamed chipseq-pe (still version 0.1)\n\n## [0.1] 2022-10-06\nFirst release.\n" - 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This is important because the dada2 step outputs\na collection in sorted order. If the input collection would not be sorted then the mergePairs step\nsamples would be mixed up.\n\n- `FilterAndTrim` Quality control by filtering and trimming reads\n- `QualityProfile` is called before and after the FilterAndTrim step\n- `Unzip Collection` separates forward and reverse reads (the next steps are evaluated separately on forward and reverse reads)\n- `learnErrors` learn error rates\n- `dada` filter noisy reads\n- `mergePairs` merge forward and reverse reads\n- `makeSequenceTable` create the sequence table\n- `removeBimeraDenovo` remove chimeric sequencs\n- `assignTaxonomy` assign taxonomic information from a reference data base\n\n## TODO\n\nSome possibilities to extend/improve the workflow\n\n- output BIOM\n- use ASV1, ... in sequence table and taxonomy output, and output additional fasta\n- allow to use custom taxonomy / make it optional\n", - "changelog": "# Changelog\n\n## [0.1] 2024-01-09\nFirst release.\n" + "readme": "# ATACseq Workflow\n\nThis workflow is highly concordant with the corresponding training material.\nYou can have more information about ATAC-seq analysis in the [slides](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/slides.html) and the [tutorial](https://training.galaxyproject.org/training-material/topics/epigenetics/tutorials/atac-seq/tutorial.html).\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- reference_genome: this field will be adapted to the genomes available for bowtie2 and the genomes available for bedtools slopbed (dbkeys table)\n- effective_genome_size: this is used by macs2 and may be entered manually (indications are provided for heavily used genomes)\n- bin_size: this is used when normalization of coverage is performed. Large values will allow to have smaller output files but with less resolution while small values will increase computation time and size of output files to produce more resolutive bigwigs.\n\n## Processing\n\n- The workflow will remove nextera adapters and low quality bases and filter out any read smaller than 15bp.\n- The filtered reads are mapped with bowtie2 allowing dovetail and fragment length up to 1kb.\n- The BAM is filtered to keep only MAPQ30, concordant pairs and pairs outside of the mitochondria.\n- The PCR duplicates are removed with Picard (only from version 0.8).\n- The BAM is converted to BED to enable macs2 to take both pairs into account.\n- The peaks are called with macs2 which at the same time generates a coverage file.\n- The coverage file is converted to bigwig\n- The amount of reads 500bp from summits and the total number of reads are computed.\n- Two normalizations are computed:\n - By million reads\n - By million reads in peaks (500bp from summits)\n- Other QC are performed:\n - A histogram with fragment length is computed.\n - The evaluation of percentage of reads to chrM or MT is computed.\n- A multiQC is run to have an overview of the QC.\n\n### Warning\n\n- The `reference_genome` parameter value is used to select references in bowtie2 and bedtools slopbed. Only references that are present in bowtie2 **and** bedtools slopbed are selectable. If your favorite reference genome is not available ask your administrator to make sure that each bowtie2 reference has a corresponding len file for use in bedtools slopbed.\n", + "changelog": "# Changelog\n\n## [0.16] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n\n## [0.15] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.30.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_slopbed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_slopbed/2.31.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_mergebed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_mergebed/2.31.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_coveragebed/2.30.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_coveragebed/2.31.1+galaxy0`\n\n## [0.14] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.13] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.12] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.11] 2024-03-18\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy2`\n\n## [0.10] 2024-03-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/samtools_idxstats/samtools_idxstats/2.0.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/samtools_idxstats/samtools_idxstats/2.0.5`\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/3.1.1.0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/samtools_view/samtools_view/1.15.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.9] 2023-10-23\n\nFix the normalization factor. It was coverage per reads and per reads in peaks instead of per million reads and per million reads in peaks.\n\n## [0.8] 2023-10-19\n\nFix the remove duplicate step!\nIn all previous versions, due to an error, PCR duplicates were not removed.\n\n## [0.7] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.6] 2023-09-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/deeptools_bigwig_average/deeptools_bigwig_average/3.5.4+galaxy0`\n\n## [0.5.1] 2023-09-22\n\nFix bug in normalize profiles when used with multiple samples (in 0.5.0 it is averaging samples instead of normalizing each sample).\n\n## [0.5] 2023-03-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.3` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/picard/picard_MarkDuplicates/2.18.2.4`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_coveragebed/2.30.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_coveragebed/2.30.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- add normalization steps for coverage\n\n## [0.4] 2023-01-16\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bamtools_filter/bamFilter/2.5.2+galaxy1`\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## [0.1] 2022-10-12\nFirst release.\n" } ], - "path": "./workflows/amplicon/dada2" + "path": "./workflows/epigenetics/atacseq" }, { "version": 1.2, "workflows": [ { - "name": "QIIME2-Ia import multiplexed data single end", + "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/QIIME2-Ia-multiplexed-data-single-end.ga", + "primaryDescriptorPath": "/chipseq-pe.ga", "testParameterFiles": [ - "/QIIME2-Ia-multiplexed-data-single-end-tests.yml" + "/chipseq-pe-tests.yml" ], "authors": [ { - "name": "Debjyoti Ghosh", - "orcid": "0009-0008-1496-1677" - }, - { - "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", - "address": "Permoserstra\u00dfe 15, 04318 Leipzig" + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "Importing single-end multiplexed data (not demultiplexed yet)", + "annotation": "This workflow takes as input a collection of paired fastqs. 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"readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. 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Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." - }, + "readme": "# ChIP-seq paired-end Workflow\n\n## Inputs dataset\n\n- The workflow needs a single input which is a list of dataset pairs of fastqsanger.\n\n## Inputs values\n\n- adapters sequences: this depends on the library preparation. If you don't know, use FastQC to determine if it is Truseq or Nextera.\n- reference_genome: this field will be adapted to the genomes available for bowtie2.\n- effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).\n- normalize_profile: Whether you want to have a profile normalized as Signal to Million Fragments.\n\n## Processing\n\n- The workflow will remove illumina adapters and low quality bases and filter out any pair with mate smaller than 15bp.\n- The filtered reads are mapped with bowtie2 with default parameters.\n- The BAM is filtered to keep only MAPQ30 and concordant pairs.\n- The peaks are called with MACS2 which at the same time generates a coverage file (normalized or not).\n- The coverage is converted to bigwig.\n- A MultiQC is run to have an overview of the QC.\n\n### Warning\n\n- The filtered bam still has PCR duplicates which are removed by MACS2.\n\n## Contribution\n\n@lldelisle wrote the workflow.\n\n@nagoue updated the tools, made it work in usegalaxy.org, fixed the best practices and wrote the tests.\n", + "changelog": "# Changelog\n\n## [0.11] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n\n## [0.10] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy1`\n\n## [0.9] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n## [0.8] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n\n## [0.7] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n\n## [0.6.1] 2024-03-14\n\nFix bug introduced in 0.6: the second adapter sequence was not used.\n\n## [0.6] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.6+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n\n## [0.5] 2023-10-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.7.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/macs2/macs2_callpeak/2.2.9.1+galaxy0`\n\n## [0.4] 2023-06-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n\n### Manual update\n- New parameter to get normalized profile\n\n## [0.3] 2022-12-17\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1`\n\n## [0.2] 2022-11-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.4.5+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/bowtie2/bowtie2/2.5.0+galaxy0`\n\n## 2022-10-20\nChIPseq_PE has been renamed chipseq-pe (still version 0.1)\n\n## [0.1] 2022-10-06\nFirst release.\n" + } + ], + "path": "./workflows/epigenetics/chipseq-pe" + }, + { + "version": 1.2, + "workflows": [ { - 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"label": "Summarising the demultiplexed output", - "name": "qiime2 demux summarize", + "label": "ToolDistillator summarize", + "name": "ToolDistillator Summarize", "outputs": [ { - "name": "visualization", - "type": "qzv" + "name": "summary_json", + "type": "json" } ], "position": { - "left": 1339.6939711359755, - "top": 5.9268220678864205 + "left": 1510.406873337906, + "top": 835.1044439315301 }, "post_job_actions": { - "RenameDatasetActionvisualization": { + "RenameDatasetActionsummary_json": { "action_arguments": { - "newname": "demux-visualization" + "newname": "tooldistillator_summarize" }, "action_type": "RenameDatasetAction", - "output_name": "visualization" + "output_name": "summary_json" + }, + "TagDatasetActionsummary_json": { + "action_arguments": { + "tags": "tooldistillator_summarize" + }, + "action_type": "TagDatasetAction", + "output_name": "summary_json" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/q2d2/qiime2__demux__summarize/qiime2__demux__summarize/2023.5.0+q2galaxy.2023.5.0.2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.9+galaxy0", "tool_shed_repository": { - 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"tags": [], - "uuid": "5a57f873-52f8-4c51-9e8d-e747d32d183a", + "tags": [ + "fasta", + "Genomics", + "ABRomics", + "antibiotic-resistance", + "antimicrobial-resistance-genes", + "antimicrobial resistance", + "bacterial-genomics", + "AMR", + "AMR-detection" + ], + "uuid": "dfcedd6a-9dc1-4dcd-8b15-dbd21482f463", "version": 1 }, - "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed." - }, + "readme": "# AMR gene detection workflow in an assembled bacterial genome (v1.0)\n\nThis workflow uses assembled bacterial genome fasta files (but can be any fasta file) and executes the following steps:\n1. Genomic detection\n - Antimicrobial resistance gene identification:\n - **staramr** to blast against ResFinder and PlasmidFinder database\n - **AMRFinderPlus** to find antimicrobial resistance genes and point mutations \n - Virulence gene identification:\n - **ABRicate** with VFDB_A database\n2. Aggregating outputs into a single JSON file\n - **ToolDistillator** to extract and aggregate information from different tool outputs to JSON parsable files\n\n## Inputs\n\n1. Assembled bacterial genome in fasta format.\n\n## Outputs\n\n1. Genomic detection\n - Antimicrobial resistance gene identification:\n - AMR gene list\n - MLST typing\n - Plasmid gene identification\n - Blast hits\n - AMR gene fasta (assembled nucleotide sequences)\n - Point mutation list\n - Virulence gene identification:\n - Gene identification in tabular format\n2. Aggregating outputs:\n - JSON file with information about the outputs of **staramr**, **AMRFinderPlus**, **ABRicate**", + "changelog": "# Changelog\n\n## [1.1.1] 2024-07-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.9+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.9+galaxy0`\n\n## [1.1] 2024-06-24\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/nml/staramr/staramr_search/0.10.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/nml/staramr/staramr_search/0.10.0+galaxy1`\n\n## [1.0] - 05-06-2024\n\n- First release" + } + ], + "path": "./workflows/bacterial_genomics/amr_gene_detection" + }, + { + "version": 1.2, + "workflows": [ { - "name": "QIIME2-Id import demultiplexed data paired end", + "name": "main", "subclass": "Galaxy", "publish": true, - 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"uuid": "f6376403-1be3-4bc0-af85-d5e2e04984b2", + "uuid": "3427b1f1-79ce-4ade-a350-baf15ac250c2", "when": null, "workflow_outputs": [ { - "label": "DADA2 output table", - "output_name": "visualization", - "uuid": "13960a03-ee65-4385-8936-b7ff5e5a98f3" + "label": "tooldistillator_summarize", + "output_name": "summary_json", + "uuid": "96d63721-4cb5-4879-8984-4eeba8dec36b" } ] } }, - "tags": [], - "uuid": "718df5b9-9cbb-4792-be50-604e18ef0548", - "version": 2 + "tags": [ + "Genomics", + "fasta", + "ABRomics", + "bacterial-genomics", + "Annotation", + "genome-annotation" + ], + "uuid": "d55a9e46-a205-4143-b92f-3783499063ed", + "version": 1 }, - "readme": "# QIIME2 workflows\n\n## Available workflows\n\nDenoising (using `qiime2`'s `dada2` integration for paired / single end data.\n\n## Inputs\n\n- Demultiplexed sequences as a qiime2 aertifact file (`qza`) containing the sequence information.\n- Metadata table (`tabular`)\n- Truncation length\n- Trimming length (optional)\n\nFor the paired end workflow the truncation and trimming length for the reverse reads can / has to be given.\n\n\n## Processing\n\n- Denoising with `qiime2 dada2 denoise-single`/`paired`\n- For each of the three outputs (see below) another tool is started to prepare a corresponding qzv file\n - representative sequences `qiime2 feature-table tabulate-seqs `\n - denoising statistics `qiime2 metadata tabulate`\n - summary of the feature table\n\n## Outputs\n\n - representative sequences \n - denoising statistics \n - summary of the feature table (how many sequences are lost in the corresponding steps)\n" - }, + "readme": "# Bacterial genome annotation workflow (v1.0)\n\nThis workflow uses assembled bacterial genome fasta files (but can be any fasta file) and executes the following steps:\n1. Genomic annotation\n - **Bakta** to predict CDS and small proteins (sORF)\n2. Integron identification\n - **IntegronFinder2** to identify CALIN elements, In0 elements, and complete integrons\n3. Plasmid gene identification\n - **Plasmidfinder** to identify and typing plasmid sequences\n4. Inserted sequence (IS) detection\n - **ISEScan** to detect IS elements\n5. Aggregating outputs into a single JSON file\n - **ToolDistillator** to extract and aggregate information from different tool outputs to JSON parsable files\n\n## Inputs\n\n1. Assembled bacterial genome in fasta format.\n\n## Outputs\n\n1. Genomic annotation:\n - genome annotation in tabular, gff and several other formats\n - annotation plot\n - nucleotide and protein sequences identified\n - summary of genomic identified elements\n2. Integron identification:\n - integron identification in tabular format and a summary\n3. Plasmid gene identification:\n - plasmid gene identified and associated blast hits\n4. Inserted Element (IS) detection:\n - IS element list in tabular format\n - is hits in fasta format\n - ORF hits in protein and nucleotide fasta format\n - IS annotation gff format\n5. Aggregating outputs:\n - JSON file with information about the outputs of **Bakta**, **IntegronFinder2**, **Plasmidfinder**, **ISEScan**", + "changelog": "# Changelog\n\n## [1.1.2] - 2024-07-19\n\n- PlasmidFinder database correction in .ga\n\n## [1.1.1] 2024-07-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator/tooldistillator/0.9+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.8.5.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/tooldistillator_summarize/tooldistillator_summarize/0.9+galaxy0`\n\n## [1.1] 2024-06-24\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/integron_finder/integron_finder/2.0.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/integron_finder/integron_finder/2.0.5+galaxy0`\n\n## [1.0] - 14-06-2024\n\n- First release\n" + } + ], + "path": "./workflows/bacterial_genomics/bacterial_genome_annotation" + }, + { + "version": 1.2, + "workflows": [ { - "name": "QIIME2-IIb denoising and feature table creation for paired ended data", + "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/QIIME2-IIb-denoising-and-feature-table-creation-paired-end.ga", + "primaryDescriptorPath": "/dada2_paired.ga", "testParameterFiles": [ - "/QIIME2-IIb-denoising-and-feature-table-creation-paired-end-tests.yml" + "/dada2_paired-tests.yml" ], "authors": [ { - "name": "Debjyoti Ghosh", - "orcid": "0009-0008-1496-1677" + "name": "Matthias Bernt", + "orcid": "0000-0003-3763-0797" }, { - "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", - "address": "Permoserstra\u00dfe 15, 04318 Leipzig" + "name": "UFZ Leipzig" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "Use DADA2 for sequence quality control. DADA2 is a pipeline for detecting and correcting (where possible) Illumina amplicon sequence data. 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Empty means no truncation.", "content_id": null, "errors": null, "id": 1, "input_connections": {}, "inputs": [ { - "description": "Demultiplexed sequences in qza format", - "name": "Demultiplexed sequences" + "description": "Forward reads will be truncated to this length. Empty means no truncation.", + "name": "Read length forward read" } ], - "label": "Demultiplexed sequences", - "name": "Input dataset", + "label": "Read length forward read", + "name": "Input parameter", "outputs": [], "position": { - "left": 2.4506271621231845, - "top": 238.07957958589887 + "left": 12, + "top": 242.3237599999942 }, "tool_id": null, - "tool_state": "{\"optional\": false, \"format\": [\"qza\"], \"tag\": null}", + "tool_state": "{\"parameter_type\": \"integer\", \"optional\": true}", "tool_version": null, - "type": "data_input", - "uuid": "e250ddc1-f567-40ca-9f2b-e07bbf84cdec", + "type": "parameter_input", + "uuid": "42e4d027-9232-4280-8972-86df76743ffd", "when": null, "workflow_outputs": [] }, "2": { - "annotation": "Length to which the forward read sequence should be truncated. Will remove bases from the 3' end.", + "annotation": "Reverse reads will be truncated to this length. 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Will remove bases from the 3' end.", - "name": "Truncation length (reverse)" + "description": "Pooling may increase sensitivity", + "name": "Pool samples" } ], - "label": "Truncation length (reverse)", + "label": "Pool samples", "name": "Input parameter", "outputs": [], "position": { - "left": 0.12398288926847933, - "top": 478.1294436628793 + "left": 10.577839999617993, + "top": 522.3237599999942 }, "tool_id": null, - "tool_state": "{\"parameter_type\": \"integer\", \"optional\": false}", + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", "tool_version": null, "type": "parameter_input", - "uuid": "2af02538-19c9-4ffc-924e-5108987064a1", + "uuid": "69ae9a01-0659-4a34-9c68-727038d75bb6", "when": null, "workflow_outputs": [] }, "4": { - "annotation": "Number of bases at the 5' end of the forward read that should be removed. 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"tags": [], - "uuid": "1ea0b92d-d863-435a-96ac-1e547fdbc994", - "version": 7 + "tags": [ + "name:amplicon" + ], + "uuid": "11d717f8-92ef-4dd7-bda7-c193175fece2", + "version": 1 }, - "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n", - "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0`\n\n## [0.3] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0`\n\n## [0.2] 2023-12-01\n\n### Add 'compute p-value' parameter in 2d\n\n### Semi-automatic update\n- all baredsc tools were updated from `1.1.2+galaxy0` to `1.1.2+galaxy1`\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1] 2023-10-03\n\nFirst release.\n" - }, + "readme": "# Dada2: amplicon analysis for paired end data\n\n## Inputs dataset\n\n- `Paired input data` paired input collection in FASTQ format\n\n## Inputs values\n\n- `Read length forward/reverse reads` length of the forward/reverse reads to which they should be truncated in the filter and trim step\n- `Pool samples` pooling may increase sensitivity\n- `Reference database` that should be used for taxonomic assignment\n\n## Processing\n\nThe workflow follows the steps described in the [dada2 tutorial](https://benjjneb.github.io/dada2/tutorial.html).\n\nAs a first step the input collection is sorted. This is important because the dada2 step outputs\na collection in sorted order. If the input collection would not be sorted then the mergePairs step\nsamples would be mixed up.\n\n- `FilterAndTrim` Quality control by filtering and trimming reads\n- `QualityProfile` is called before and after the FilterAndTrim step\n- `Unzip Collection` separates forward and reverse reads (the next steps are evaluated separately on forward and reverse reads)\n- `learnErrors` learn error rates\n- `dada` filter noisy reads\n- `mergePairs` merge forward and reverse reads\n- `makeSequenceTable` create the sequence table\n- `removeBimeraDenovo` remove chimeric sequencs\n- `assignTaxonomy` assign taxonomic information from a reference data base\n\n## TODO\n\nSome possibilities to extend/improve the workflow\n\n- output BIOM\n- use ASV1, ... in sequence table and taxonomy output, and output additional fasta\n- allow to use custom taxonomy / make it optional\n", + "changelog": "# Changelog\n\n## [0.2] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_plotqualityprofile/dada2_plotQualityProfile/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_plotqualityprofile/dada2_plotQualityProfile/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_filterandtrim/dada2_filterAndTrim/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_filterandtrim/dada2_filterAndTrim/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_learnerrors/dada2_learnErrors/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_learnerrors/dada2_learnErrors/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_dada/dada2_dada/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_dada/dada2_dada/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_mergepairs/dada2_mergePairs/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_mergepairs/dada2_mergePairs/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_makesequencetable/dada2_makeSequenceTable/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_makesequencetable/dada2_makeSequenceTable/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_removebimeradenovo/dada2_removeBimeraDenovo/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_removebimeradenovo/dada2_removeBimeraDenovo/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_seqcounts/dada2_seqCounts/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_seqcounts/dada2_seqCounts/1.30.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/dada2_assigntaxonomyaddspecies/dada2_assignTaxonomyAddspecies/1.28+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/dada2_assigntaxonomyaddspecies/dada2_assignTaxonomyAddspecies/1.30.0+galaxy0`\n\n## [0.1] 2024-01-09\nFirst release.\n" + } + ], + "path": "./workflows/amplicon/dada2" + }, + { + "version": 1.2, + "workflows": [ { - "name": "baredSC-2d-logNorm", + "name": "QIIME2-III-V-Phylogeny-Rarefaction-Taxonomic-Analysis", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/baredSC-2d-logNorm.ga", + "primaryDescriptorPath": "/QIIME2-III-V-Phylogeny-Rarefaction-Taxonomic-Analysis.ga", "testParameterFiles": [ - "/baredSC-2d-logNorm-tests.yml" + "/QIIME2-III-V-Phylogeny-Rarefaction-Taxonomic-Analysis-tests.yml" ], "authors": [ { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" + "name": "Debjyoti Ghosh", + "orcid": "0009-0008-1496-1677" + }, + { + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", + "address": "Permoserstra\u00dfe 15, 04318 Leipzig" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "Run baredSC in 2 dimensions in logNorm for 1 to N gaussians and combine models.", + "annotation": "This workflow \n- Reconstruct phylogeny (insert fragments in a reference)\n- Alpha rarefaction analysis\n- Taxonomic analysis", + "comments": [], "creator": [ { "class": "Person", - "identifier": "https://orcid.org/0000-0002-1964-4960", - "name": "Lucille Delisle" + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ" } ], "format-version": "0.1", "license": "MIT", - "release": "0.4", - "name": "baredSC_2d_logNorm", + "name": "QIIME2-III-V-Phylogeny-Rarefaction-Taxonomic-Analysis", + "release": "0.1", "steps": { "0": { - "annotation": "The dataset must have a first row with row names. 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"label": "combined_other_outputs", - "output_name": "other_outputs", - "uuid": "eca7f33c-3a1d-41d7-a56a-925167baf364" + "label": "Rarefaction curve", + "output_name": "Rarefaction curve", + "uuid": "12394a5b-15fc-44f2-80cd-2b38de92517a" } ] } }, "tags": [], - "uuid": "1936816b-958a-4140-b839-58be4cdae1a5", - "version": 1 + "uuid": "3163175d-7673-42d9-8aae-505afbd74946", + "version": 30 }, - "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n", - "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0`\n\n## [0.3] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0`\n\n## [0.2] 2023-12-01\n\n### Add 'compute p-value' parameter in 2d\n\n### Semi-automatic update\n- all baredsc tools were updated from `1.1.2+galaxy0` to `1.1.2+galaxy1`\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1] 2023-10-03\n\nFirst release.\n" - } - ], - "path": "./workflows/scRNAseq/baredsc" - }, - { - "version": 1.2, - "workflows": [ + "readme": "# QIIME2 workflows\n\n## Available workflows\n\n- III-V Downstream analyses: III) reconstruct a taxonomy for diversity analysis, IV) rarefaction analysis, V) taxonomic analysis.\n- VI: Computation of diversity metrics and estimations\n\nAnalogous to the procedures described in the Parkinson\u2019s Mouse Tutorial: https://docs.qiime2.org/2024.5/tutorials/pd-mice/\n\n## Inputs\n\nThe two workflows have two inputs in common \n\n- Feature table: Count data\n- Metadata: Metadata table\n\nand the following extra inputs\n\nIII-V\n\n- Representative sequences: Representative (ASV) sequences\n- Minimum depth: Lower limit of the sampling depth for the alpha rarefaction analysis\n- Maximum depth: Upper limit of the sampling depth for the alpha rarefaction analysis\n- SEPP fragment insertion reference: used for the reconstruction of the phylogenetic tree\n- Taxonomic classifier: The classifier to assign taxonomic information to the ASVs\n\nVI:\n\nSampling depth: For the metric calculation (should be based on the rarefaction analysis done in IV)\nTarget metadata parameter: that should be used for beta diversity calculations\nRooted Tree: for instance the tree computed in III\n\n## Processing\n\nIII-V\n\n- Phylogenetic tree generation using `qiime2 fragment-insertion sepp`\n- Alpha rarefaction analysis using `qiime2 diversity alpha-rarefaction`\n- Taxonomic classification using `qiime2 feature-classifier classify-sklearn` and compute barplot and tabular output\n\nVI: \n\n- compute alpha and beta diversity metrics using `qiime2 diversity core-metrics-phylogenetic`\n- organize these metrics in 4 collections:\n 1. Distance matrix collection (weighted and unweighted unifrac, jaccard and bray curtis)\n 2. PCoA collection (same as the distance matrices)\n 3. Emperor plot collection (same as the distance matrices)\n 4. Richness and evenness collection (rarefied table, faith pd vector observed features vector, shannon vector, evenness vector)\n- get visualization for alpha diversity:\n - Pielou's eveness\n - Observed features\n - Shannons diversity index\n- get visualization for beta diversity\n - Jaccard distance matrix\n - Bray curtis distance matrix\n - Unifrac distance metrix \n\n## Outputs\n\nIII-V:\n\n- Phylogenetic tree\n- Rarefaction curve\n- Taxonomic classification (as qza, barplot and table)\n\nVI:\n\n- Four collections containing: distance matrix, PCoA, Emperor plots, Richness and evenness\n- Visualization for alpha diversity: Pielou's eveness, Observed features, Shannons diversity index\n- Visualization for beta diversity: Jaccard, Bray curtis, Unifrac", + "changelog": "# Changelog\n\n## [0.1] 2024-06-22\nFirst release." + }, { - "name": "scrna-seq-fastq-to-matrix-10x-cellplex", + "name": "QIIME2-VI-diversity-metrics-and-estimations", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/scrna-seq-fastq-to-matrix-10x-cellplex.ga", + "primaryDescriptorPath": "/QIIME2-VI-diversity-metrics-and-estimations.ga", "testParameterFiles": [ - "/scrna-seq-fastq-to-matrix-10x-cellplex-tests.yml" + "/QIIME2-VI-diversity-metrics-and-estimations-tests.yml" ], "authors": [ { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" - }, - { - "name": "Mehmet Tekman", - "orcid": "0000-0002-4181-2676" - }, - { - "name": "Hans-Rudolf Hotz", - "orcid": "0000-0002-2799-424X" - }, - { - "name": "Daniel Blankenberg", - "orcid": "0000-0002-6833-9049" + "name": "Debjyoti Ghosh", + "orcid": "0009-0008-1496-1677" }, { - "name": "Wendi Bacon", - "orcid": "0000-0002-8170-8806" + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", + "address": "Permoserstra\u00dfe 15, 04318 Leipzig" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "This workflow processes the CMO fastqs with CITE-seq-Count and include the translation step required for cellPlex processing. 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files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. 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files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed.", + "changelog": "# Changelog\n\n## [0.1] 2024-04-08\nFirst release.\n## [0.2] 2024-05-23\nFix dockstore.yml and test." + }, + { + "name": "Ic-import-demultiplexed-se", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/QIIME2-Ic-demultiplexed-data-single-end.ga", + "testParameterFiles": [ + "/QIIME2-Ic-demultiplexed-data-single-end-tests.yml" + ], + "authors": [ + { + "name": "Debjyoti Ghosh", + "orcid": "0009-0008-1496-1677" + }, + { + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", + "address": "Permoserstra\u00dfe 15, 04318 Leipzig" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Importing demultiplexed data (single-end)", + "creator": [ + { + "class": "Person", + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum 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"inputs": [], + "label": "Import data into the pipeline", + "name": "qiime2 tools import", + "outputs": [ + { + "name": "imported_data", + "type": "qza" + } + ], + "position": { + "left": 1079.0168624775688, + "top": 1.637809220122261 + }, + "post_job_actions": { + "RenameDatasetActionimported_data": { + "action_arguments": { + "newname": "input-data-demultiplexed" + }, + "action_type": "RenameDatasetAction", + "output_name": "imported_data" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/q2d2/qiime2_core__tools__import/qiime2_core__tools__import/2023.5.0+dist.h193f7cc9.3", + "tool_shed_repository": { + "changeset_revision": "10447a4b0cc3", + "name": "qiime2_core__tools__import", + "owner": "q2d2", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"import_root\": {\"type\": \"SampleData__ob__SequencesWithQuality__cb__\", \"__current_case__\": 49, \"__q2galaxy__GUI__cond__format__\": {\"format\": \"CasavaOneEightLanelessPerSampleDirFmt\", \"__current_case__\": 0, 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"output_name": "imported_data" + } + }, + "inputs": [], + "label": "Summarising the demultiplexed output", + "name": "qiime2 demux summarize", + "outputs": [ + { + "name": "visualization", + "type": "qzv" + } + ], + "position": { + "left": 1339.6939711359755, + "top": 5.9268220678864205 + }, + "post_job_actions": { + "RenameDatasetActionvisualization": { + "action_arguments": { + "newname": "demux-visualization" + }, + "action_type": "RenameDatasetAction", + "output_name": "visualization" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/q2d2/qiime2__demux__summarize/qiime2__demux__summarize/2023.5.0+q2galaxy.2023.5.0.2", + "tool_shed_repository": { + "changeset_revision": "d8a9f74f1a6d", + "name": "qiime2__demux__summarize", + "owner": "q2d2", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"__q2galaxy__GUI__section__extra_opts__\": {\"n\": \"10000\"}, \"data\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "2023.5.0+q2galaxy.2023.5.0.2", + "type": "tool", + "uuid": "cf48f270-6c6c-4fad-8c1d-2b02bb73ae49", + "when": null, + "workflow_outputs": [ + { + "label": "Visualization", + "output_name": "visualization", + "uuid": "5c67b911-b178-4f6f-8ef8-0071d72d3a25" + } + ] + } + }, + "tags": [], + "uuid": "5a57f873-52f8-4c51-9e8d-e747d32d183a", + "version": 1 + }, + "readme": "# QIIME2 import workflows\n\n\n## Available workflows\n\nImport of fastqsanger.gz data into QIIME artifact files.\n\nAvailable for:\n\n- paired / single end data\n- demultiplexed / multiplexed data (the former according to the EMP protocol)\n\nFor data that is multiplexed with another protocol the Galaxy cutadapt tool can be use.\n\n## Inputs\n\n- Single end or paired end reads in fastq format.\n- For demultiplexed data all datasets must be in a single (flat) collection\n (also paired data).\n\n### Demultiplexed data\n\n- Demultiplexed data must follow the naming scheme `.+_.+_R[12]_001\\.fastq\\.gz`.\n Any lane information (in the form of `L[0-9][0-9][0-9]_`) in the dataset names\n is automatically removed.\n\n### Mulmultiplexed data\n\n- Multiplexed data in a single or two fastq.gz dataset(s)\n- Barcodes as fastq.gz file\n- Metadata (a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed.", + "changelog": "# Changelog\n\n## [0.1] 2024-04-08\nFirst release.\n## [0.2] 2024-05-23\nFix dockstore.yml and test." + }, + { + "name": "Id-import-demultiplexed-pe", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/QIIME2-Id-demultiplexed-data-paired-end.ga", + "testParameterFiles": [ + "/QIIME2-Id-demultiplexed-data-paired-end-tests.yml" + ], + "authors": [ + { + "name": "Debjyoti Ghosh", + "orcid": "0009-0008-1496-1677" + }, + { + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", + "address": "Permoserstra\u00dfe 15, 04318 Leipzig" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Importing demultiplexed data (paired-end)", + "creator": [ + { + "class": "Person", + "identifier": "0009-0008-1496-1677", + "name": "Debjyoti Ghosh" + }, + { + "address": "Permoserstra\u00dfe 15, 04318 Leipzig", + "class": "Organization", + "name": "Helmholtz-Zentrum 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(a table describing the samples) and a metadata parameter (the name of the column that contains the barcode sequences)\n- A boolean determining if there reverse complement of the barcode sequences shoul dbe used\n\n## Processing\n\nFor demultiplexed data\n\n1. Lane information is removed from the collection identifiers (using `Extract element identifiers`, `Regex Find And Replace` and `Relabel identifiers`)\n2. Import of sequence data using `qiime2 tools import` with `Casava One Eight Laneless Per Sample Directory Format`\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\nFor multiplexed data\n\n1. Import sequences and metadata with `qiime2 tools import` as `EMP Paired End Directory Format` and `Immutable Metadata Format`, resp.\n2. Demultiplex the sequences with `qiime2 demux emp-paired`/`paired` (using sequences and metadata information)\n3. Prepare visualisation dataset with `qiime2 demux summarize`\n\n\n## Outputs\n\n- Sequence data in `qza` format\n- A corresponding qiime visualization file in `qzv` format\n\n## TODOs\n\n- The import workflows for multiplexed data currently first convert the metadata into qza and require the user to enter a column as free text. If Galaxy allows for data-column workflow parameters this step can be removed.", + "changelog": "# Changelog\n\n## [0.1] 2024-04-08\nFirst release.\n## [0.2] 2024-05-23\nFix dockstore.yml and test." + } + ], + "path": "./workflows/amplicon/qiime2/qiime2-I-import" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "IIa-denoising-se", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/QIIME2-IIa-denoising-and-feature-table-creation-single-end.ga", + "testParameterFiles": [ + "/QIIME2-IIa-denoising-and-feature-table-creation-single-end-tests.yml" + ], + "authors": [ + { + "name": "Debjyoti Ghosh", + "orcid": "0009-0008-1496-1677" + }, + { + "name": "Helmholtz-Zentrum f\u00fcr Umweltforschung - UFZ", + "address": "Permoserstra\u00dfe 15, 04318 Leipzig" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Use DADA2 for sequence quality control. 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sequences are lost in the corresponding steps)\n", + "changelog": "# Changelog\n\n## [0.1] 2024-04-08\nFirst release.\n## [0.2] 2024-05-23\nFix dockstore.yml." + } + ], + "path": "./workflows/amplicon/qiime2/qiime2-II-denoising" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "baredSC-1d-logNorm", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/baredSC-1d-logNorm.ga", + "testParameterFiles": [ + "/baredSC-1d-logNorm-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run baredSC in 1 dimension in logNorm for 1 to N gaussians and combine models.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.5", + "name": "baredSC_1d_logNorm", + "steps": { + "0": { + "annotation": "The dataset must have 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+ "uuid": "1ea0b92d-d863-435a-96ac-1e547fdbc994", + "version": 7 + }, + "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n", + "changelog": "# Changelog\n\n## [0.5] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0`\n\n## [0.3] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0`\n\n## [0.2] 2023-12-01\n\n### Add 'compute p-value' parameter in 2d\n\n### Semi-automatic update\n- all baredsc tools were updated from `1.1.2+galaxy0` to `1.1.2+galaxy1`\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1] 2023-10-03\n\nFirst release.\n" + }, + { + "name": "baredSC-2d-logNorm", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/baredSC-2d-logNorm.ga", + "testParameterFiles": [ + "/baredSC-2d-logNorm-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run baredSC in 2 dimensions in logNorm for 1 to N gaussians and combine models.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.5", + "name": "baredSC_2d_logNorm", + "steps": { + "0": { + "annotation": "The dataset must have a first row with row names. 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"MCMC" + }, + { + "description": "runtime parameter for tool Combine multiple 2D Models", + "name": "MCMC" + }, + { + "description": "runtime parameter for tool Combine multiple 2D Models", + "name": "advanced" + }, + { + "description": "runtime parameter for tool Combine multiple 2D Models", + "name": "input_counts" + } + ], + "label": null, + "name": "Combine multiple 2D Models", + "outputs": [ + { + "name": "other_outputs", + "type": "input" + }, + { + "name": "pdf2d", + "type": "tabular" + }, + { + "name": "pdf2d_flat", + "type": "tabular" + }, + { + "name": "plot", + "type": "png" + } + ], + "position": { + "left": 1240, + "top": 199.5 + }, + "post_job_actions": {}, + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0", + "tool_shed_repository": { + "changeset_revision": "02fc39c8610d", + "name": "baredsc_combine_2d", + "owner": "iuc", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"MCMC\": {\"outputs\": {\"__class__\": \"ConnectedValue\"}, \"xmin\": \"0.0\", \"xmax\": {\"__class__\": \"ConnectedValue\"}, \"nx\": \"25\", \"minScalex\": \"0.1\", \"ymin\": \"0.0\", \"ymax\": {\"__class__\": \"ConnectedValue\"}, \"ny\": \"25\", \"minScaley\": \"0.1\", \"scale\": {\"type\": \"Seurat\", \"__current_case__\": 0, \"targetSum\": \"10000.0\"}, \"seed\": \"1\"}, \"advanced\": {\"getPVal\": {\"__class__\": \"ConnectedValue\"}, \"osampx\": \"10\", \"osampxpdf\": \"4\", \"osampy\": \"10\", \"osampypdf\": \"4\", \"coviscale\": \"1.0\", \"nis\": \"1000\", \"scalePrior\": \"0.3\"}, \"filter\": {\"nb\": \"0\", \"__current_case__\": 0}, \"geneXColName\": {\"__class__\": \"ConnectedValue\"}, \"geneYColName\": {\"__class__\": \"ConnectedValue\"}, \"input_counts\": {\"filetype\": \"tabular\", \"__current_case__\": 0, \"input\": {\"__class__\": \"ConnectedValue\"}}, \"plots\": {\"image_file_format\": \"png\", \"title\": \"\", \"removeFirstSamples\": \"-1\", \"nsampInPlot\": \"100000\", \"prettyBinsx\": \"-1\", \"prettyBinsy\": \"-1\", \"log1pColorScale\": false, \"splity\": \"\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "1.1.3+galaxy0", + "type": "tool", + "uuid": "e4eebae4-0952-4d21-8bb6-d16d1b5397b3", + "when": null, + "workflow_outputs": [ + { + "label": "combined_pdf2d", + "output_name": "pdf2d", + "uuid": "0fff7566-a7d9-4dac-b77b-416e6a2f56ef" + }, + { + "label": "combined_pdf2d_flat", + "output_name": "pdf2d_flat", + "uuid": "79eb786a-7465-4f24-aafa-d2520028527d" + }, + { + "label": "combined_plot", + "output_name": "plot", + "uuid": "db367996-7c6c-4cd3-8692-c0483fbc671c" + }, + { + "label": "combined_other_outputs", + "output_name": "other_outputs", + "uuid": "eca7f33c-3a1d-41d7-a56a-925167baf364" + } + ] + } + }, + "tags": [], + "uuid": "1936816b-958a-4140-b839-58be4cdae1a5", + "version": 1 + }, + "readme": "# BaredSC Workflows\n\nThese workflows allow to run a baredSC analysis from a table with counts in a single click. It uses models from 1 to N Gaussians and combine them. It uses the logNorm scale, 100 bins for 1 dimension and 25 bins on each axis in 2 dimensions.\n\n## Inputs dataset\n\n- Both workflows need a tabular dataset where each row is a cell. The tabular needs to have a header line with column names. There must be at least two columns: 'nCount_RNA' and another one with the counts for the gene(s) of interest. A way to get such table in R from a Seurat object (`seurat.obj`) is:\n\n```r\nmy.genes <- c(\"Hoxa13\", \"Hoxd13\")\ndf <- cbind(seurat.obj[[]], # This will give you all metadata including nCount_RNA\n FetchData(seurat.obj, slot = \"counts\", vars = my.genes))\n\nwrite.table(df, \"input_for_baredSC.txt\", quote = F, sep = \"\\t\", row.names = F)\n```\n\n## Inputs values\n\nFor the 1D:\n\n- Gene name: The name of the column with the counts of your gene of interest.\n- Maximum value in logNorm: The maximum value to explore in PDF. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 Gaussians to models with this number of Gaussians will be combined.\n\nFor the 2D:\n\n- Gene name for x axis: The name of the column with the counts of your gene in x axis.\n- Gene name for y axis: The name of the column with the counts of your gene in y axis.\n- maximum value in logNorm for x-axis: The maximum value to explore in PDF in the x axis. This value should be large enough so the PDF is at 0 at this value.\n- maximum value in logNorm for y-axis: The maximum value to explore in PDF in the y axis. This value should be large enough so the PDF is at 0 at this value.\n- Maximum number of Gaussians to study: All models between models with 1 2D-Gaussians to models with this number of 2D-Gaussians will be combined.\n- compute p-value: Whether you want to get a p-value. As a consequence, less samples than available will be used for plots as p-value computation requires to have independent samples.\n\n## Processing\n\n- The workflow will generate paramater values from 1 to the maximum number of Gaussians to study.\n- baredSC_1d or baredSC_2d is run for each of these number of Gaussians\n- All models are combined into a single result.\n", + "changelog": "# Changelog\n\n## [0.5] 2024-05-27\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.2`\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_1d/baredsc_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_1d/baredsc_combine_1d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_2d/baredsc_2d/1.1.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/baredsc_combine_2d/baredsc_combine_2d/1.1.3+galaxy0`\n\n## [0.3] 2024-03-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/1.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_text_file_with_recurring_lines/9.3+galaxy0`\n\n## [0.2] 2023-12-01\n\n### Add 'compute p-value' parameter in 2d\n\n### Semi-automatic update\n- all baredsc tools were updated from `1.1.2+galaxy0` to `1.1.2+galaxy1`\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/split_file_to_collection/split_file_to_collection/0.5.1`\n\n## [0.1] 2023-10-03\n\nFirst release.\n" + } + ], + "path": "./workflows/scRNAseq/baredsc" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "scrna-seq-fastq-to-matrix-10x-cellplex", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/scrna-seq-fastq-to-matrix-10x-cellplex.ga", + "testParameterFiles": [ + "/scrna-seq-fastq-to-matrix-10x-cellplex-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + }, + { + "name": "Mehmet Tekman", + "orcid": "0000-0002-4181-2676" + }, + { + "name": "Hans-Rudolf Hotz", + "orcid": "0000-0002-2799-424X" + }, + { + "name": "Daniel Blankenberg", + "orcid": "0000-0002-6833-9049" + }, + { + "name": "Wendi Bacon", + "orcid": "0000-0002-8170-8806" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "This workflow processes the CMO fastqs with CITE-seq-Count and include the translation step required for cellPlex processing. In parallel it processes the Gene Expresion fastqs with STARsolo, filter cells with DropletUtils and reformat all outputs to be easily used by the function 'Read10X' from Seurat.", + "creator": [ + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-1964-4960", + "name": "Lucille Delisle" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-4181-2676", + "name": "Mehmet Tekman" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-2799-424X", + "name": "Hans-Rudolf Hotz" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-6833-9049", + "name": "Daniel Blankenberg" + }, + { + "class": "Person", + "identifier": "https://orcid.org/0000-0002-8170-8806", + "name": "Wendi Bacon" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.4", + "name": "scRNA-seq_preprocessing_10X_cellPlex", + "steps": { + "0": { + "annotation": "reads containing genes", + "content_id": null, + "errors": null, + 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You can use 24000.", + "content_id": null, + "errors": null, + "id": 7, + "input_connections": {}, + "inputs": [ + { + "description": "Used by CITE-seq-Count, does not really seem to impact result. 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Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n", + "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n\n## [0.3] 2024-02-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.2] 2024-02-05\n\n### Tool updates\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy3` was updated to 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One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n", + "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n\n## [0.3] 2024-02-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.2] 2024-02-05\n\n### Tool updates\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n- `pick_value` was replaced by `toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.2.0`\n\n\n\n## [0.1] 2023-12-21\n\nFirst release.\n" + } + ], + "path": "./workflows/scRNAseq/fastq-to-matrix-10x" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "Velocyto-on10X-from-bundled", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Velocyto-on10X-from-bundled.ga", + "testParameterFiles": [ + "/Velocyto-on10X-from-bundled-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Run velocyto to get loom with counts of spliced and unspliced. 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There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n", + "changelog": "# Changelog\n\n## [0.2] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy2`\n## [0.1] 2024-01-26\n\nFirst release.\n" + }, + { + "name": "Velocyto-on10X-filtered-barcodes", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Velocyto-on10X-filtered-barcodes.ga", + "testParameterFiles": [ + "/Velocyto-on10X-filtered-barcodes-tests.yml" + ], + "authors": [ + { + "name": "Lucille Delisle", + "orcid": "0000-0002-1964-4960" + } + ], + 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parameter for tool velocyto CLI", + "name": "main" + }, + { + "description": "runtime parameter for tool velocyto CLI", + "name": "main" + }, + { + "description": "runtime parameter for tool velocyto CLI", + "name": "main" + }, + { + "description": "runtime parameter for tool velocyto CLI", + "name": "main" + } + ], + "label": "velocyto", + "name": "velocyto CLI", + "outputs": [ + { + "name": "samples", + "type": "loom" + } + ], + "position": { + "left": 470.66666666666663, + "top": 116.32222493489576 + }, + "post_job_actions": {}, + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy2", + "tool_shed_repository": { + "changeset_revision": "90e95e9ee190", + "name": "velocyto_cli", + "owner": "iuc", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"main\": {\"do\": \"run10x\", \"__current_case__\": 0, \"sample_definition\": {\"sample_definition_select\": \"identifier\", \"__current_case__\": 1}, \"BAM\": {\"__class__\": 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There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). 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have been sequenced in two halves in two separate sequencing runs, and utilizes this property to resolve the inverted terminal repeat (ITR) sequences of pox virus genomes.\n\nThe workflow uses BWA-MEM for mapping the reads from each half-genome sequencing run to a correspondingly masked version of the reference genome, merges the resulting two read mappings, and uses iVar for primer trimming and consensus sequence generation.\n\nConceptually, this workflow builds on https://github.com/iwc-workflows/sars-cov-2-pe-illumina-artic-ivar-analysis and adds the logic for the split genome mapping and merging of the results.", + "changelog": "# Changelog\n\n## [0.2] 2024-06-19\n\n### Tool version updates\n\n- `toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated tp 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`toolshed.g2.bx.psu.edu/repos/iuc/ivar_trim/ivar_trim/1.3.1+galaxy6` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ivar_trim/ivar_trim/1.4.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ivar_consensus/ivar_consensus/1.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ivar_consensus/ivar_consensus/1.4.2+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n\n## [0.1]\n\nInitial version of Pox Virus Illumina Amplicon workflow (iVar based) for half-genomes sequencing data\n" + } + ], + "path": "./workflows/virology/pox-virus-amplicon" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": 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"release": "0.1", + "name": "Pathogen Detection PathoGFAIR Samples Aggregation and Visualisation", + "report": { + "markdown": "# Pathogen Detection - PathoGFAIR Samples Aggregation and Visualisation Workflow Report\nBelow are the results for the PathoGFAIR Samples Aggregation and Visualisation Workflow\n\nThis workflow was run on:\n\n```galaxy\ngenerate_time()\n```\n\nWith Galaxy version:\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Workflow Inputs\nTabular files and a FASTA file from the Gene-based Pathogen Identification workflow, four other tabular files from Nanopore Preprocessing and Nanopore - Allele-based Pathogen Identification workflow, and an optional Metadata tabular file with more sample information:\n\nFrom Gene-based Pathogenic Identification workflow: \n- contigs, FASTA file\n- VFs, Tabular file\n- vfs_of_genes_identified_by_vfdb, Tabular file\n- AMRs, Tabular file\n- amr_identified_by_ncbi, Tabular file\n\nFrom Nanopore - Allele bases Pathogen Identification workflow: \n- number_of_variants_per_sample, Tabular file\n- mapping_mean_depth_per_sample, Tabular file\n- mapping_coverage_percentage_per_sample, Tabular file\n\nFrom Nanopore Preprocessing: \n- removed_hosts_percentage_tabular, Tabular file\n\n## Some of the Workflow Outputs\n\n1- All Samples VFs Heatmap\n\n```galaxy\nhistory_dataset_as_image(output=\"heatmap_png\")\n```\n\n2- All samples phylogenetic tree VFs based\n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_vfs\")\n```\n\n3- All samples Phylogenetic tree AMR based \n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_amrs\")\n```\n\n4- Bar-plot for the Number of reads before host sequences removal and Number of found host reads per sample, performed in the Nanopore - Preprocessing workflow\n\n\n5- Barplot for the total number of removed host sequences per sample\n\n \n6- Barplot for the Mapping mean depth of coverage per sample\n\n\n6- Barplot for the Mapping 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"b8bd25f7-caa3-44da-8329-26dce6d46636", - "version": 4 + "uuid": "cb26018e-9d2f-4513-a372-122474df703e", + "version": 58 }, - "readme": "# Single-cell RNA-seq fastq to matrix for 10X data\n\nThese workflows are inspired by the [training material](https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-preprocessing-tenx/tutorial.html). Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n", - "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n\n## [0.3] 2024-02-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.2] 2024-02-05\n\n### Tool updates\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n- `pick_value` was replaced by `toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.2.0`\n\n\n\n## [0.1] 2023-12-21\n\nFirst release.\n" - }, + "readme": "# Pathogen Detection: PathoGFAIR Samples Aggregation and Visualisation\n\nIn this workflow, we will aggregate results and use the results from 3 workflows (**Nanopore Preprocessing**, **Gene-based Pathogen Identification** and **Nanopore Allele-based Pathogen Identification**) to help track pathogens among samples and visualise all performed analysis by:\n\n1. Drawing a presence-absence heatmap of the identified VF genes within all samples to visualise in which samples these genes can be found.\n2. Drawing a phylogenetic tree for each pathogenic genes detected, where we will relate the contigs of the samples together where this gene is found.\n3. Plotting QC reads, host reads, mapping coverage and depth, and SNP analysis.\n\nWith these types of visualisations, we can have an overview of all samples and the genes, but also how samples are related to each other, which common pathogenic genes they share. Given the time of the sampling and the location one can easily identify using these graphs, where and when the contamination has occurred among the different samples.\n\nIf you're unsure how to use this workflows, or if you want to see it in action with test datasets, it is included in our detailed training material for foodborne pathogen detection and tracking. You can find step-by-step instructions and practical examples in the following [GTN tutorial](https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.html)\n", + "changelog": "# Changelog\n\n## [0.1] 2024-04-24\n\nFirst release.\n" + } + ], + "path": "./workflows/microbiome/pathogen-detection-pathogfair-samples-aggregation-and-visualisation" + }, + { + "version": 1.2, + "workflows": [ { - "name": "scrna-seq-fastq-to-matrix-10x-v3", + "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/scrna-seq-fastq-to-matrix-10x-v3.ga", + "primaryDescriptorPath": "/Allele-based-Pathogen-Identification.ga", "testParameterFiles": [ - "/scrna-seq-fastq-to-matrix-10x-v3-tests.yml" + "/Allele-based-Pathogen-Identification-tests.yml" ], "authors": [ { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" - }, - { - "name": "Mehmet Tekman", - "orcid": "0000-0002-4181-2676" - }, - { - 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"tags": [ - "#single-cell" - ], - "uuid": "19feac09-8db7-4e3f-9774-8b815918cfa7", - "version": 2 - }, - "readme": "# Single-cell RNA-seq fastq to matrix for 10X data\n\nThese workflows are inspired by the [training material](https://training.galaxyproject.org/training-material/topics/single-cell/tutorials/scrna-preprocessing-tenx/tutorial.html). Except that the output is in a 'bundle' format: three files (one matrix, one with genes, one with barcodes) which is similar to the cellranger output format.\n\nBoth are designed for fastqs from 10X libraries v3. One is for regular 10X library (one library per sample), while the other one is for CellPlex 10X library which allows to multiplex samples using CMOs (see [this blog article](https://www.10xgenomics.com/blog/answering-your-questions-about-sample-multiplexing-for-single-cell-gene-expression)).\n\n## Input datasets\n\n- Specific for each experiment:\n - For both workflows: you need a list of pairs of fastqs with gene expression.\n - For CellPlex: you need in addition a list of pairs of fastqs with CMO.\n - For CellPlex: you need a list of csv which describes samples and CMO used:\n - first column is the sequence and second column is the name\n /!\\ The order of samples need to be exactly the same between the collection of fastqs of CMO and the collection of csv.\n\n- Common for all experiments:\n - Gene annotations: A gtf file with gene locations\n - List of barcodes used by 10X. You can download it at https://zenodo.org/record/3457880/files/3M-february-2018.txt.gz\n\n## Input values\n\n- reference genome: this genome needs to be available for STAR\n- Barcode Size is same size of the Read: if the length of your R1 of GEX matches the size of cell barcode + UMI set to true. If your R1 contains trailling A, put false.\n- number of cells: If you make it too large no cell barcode correction will be performed to demultiplex CMOs.\n\n## Processing\n- Gene expression processing:\n - Reads are aligned to the genome, asigned to genes, cell barcode and UMI with STAR Solo\n - MultiQC report the mapping rate and the number of reads attributed to genes\n - The output of STAR Solo is filtered with Droplet Utils to remove cellular barcodes which are probably empty.\n - The output of Droplet Utils is reorganized to be:\n```\nMain Collection:\n - Sample 1:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n - Sample 2:\n - matrix.mtx\n - barcodes.tsv\n - genes.tsv\n...\n```\nFor the CellPlex workflow:\n- CMO processing:\n - CITE-Seq Count is used to asign reads and generate a matrix where 'genes' are the CMO and 'unmapped'.\n - Cellular barcodes are translated to match the cellular barcodes of Gene expression see [this article](https://kb.10xgenomics.com/hc/en-us/articles/360031133451-Why-is-there-a-discrepancy-in-the-3M-february-2018-txt-barcode-whitelist-).\n - Reorganize the output with UMI matrices to match the same structure as gene expression matrices.\n\n## Test data\n\nThe test dataset has been produced to make it as small as possible in order to make the workflow pass on CI.\n\n- The CMO reads come from [zenodo](https://zenodo.org/records/10229382) and have been sampled to 0.1 with seqtk.\n- The GEX reads come from SRR13948489 but have been subsetted to the cells selected in the above zenodo.\n", - "changelog": "# Changelog\n\n## [0.4] 2024-04-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n\n## [0.3] 2024-02-12\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.10b+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rna_starsolo/rna_starsolo/2.7.11a+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.2] 2024-02-05\n\n### Tool updates\n- `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/rgrnastar/rna_star/2.7.10b+galaxy4`\n- `pick_value` was replaced by `toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.2.0`\n\n\n\n## [0.1] 2023-12-21\n\nFirst release.\n" - } - ], - "path": "./workflows/scRNAseq/fastq-to-matrix-10x" - }, - { - "version": 1.2, - "workflows": [ - { - "name": "Velocyto-on10X-from-bundled", - "subclass": "Galaxy", - "publish": true, - "primaryDescriptorPath": "/Velocyto-on10X-from-bundled.ga", - "testParameterFiles": [ - "/Velocyto-on10X-from-bundled-tests.yml" - ], - "authors": [ - { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" - } - ], - "definition": { - "a_galaxy_workflow": "true", - "annotation": "Run velocyto to get loom with counts of spliced and unspliced. 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There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n", - "changelog": "# Changelog\n\n## [0.2] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy2`\n## [0.1] 2024-01-26\n\nFirst release.\n" - }, + "readme": "# Allele-based Pathogen Identification\n\nThis workflow identifies pathogens using an allelic approach, detecting Single Nucleotide Polymorphisms (SNPs) to track emerging variants, i.e. markers showing evolutionary histories of homogeneous strains. This process includes SNP calling, aimed at identifying novel pathogen strains and elucidating discrepancies compared to reference sequences, thereby facilitating the tracking of emerging variants. Within this workflow, both variants and SNPs are discerned, serving as crucial elements for subsequent pathogen identification and variant tracking purposes.\n\n## Input Datasets\n- Collection of Pre-Processed Sequenced reads of all samples, ready for further analysis with the other workflows, in a `fastqsanger or fastqsanger.gz` format, the output of **Nanopore Preprocessing** workflow.\n- A reference genome to the tested pathogen.\n\n## Output Datasets\n- VCF files indicating identified variants and SNPs, BAM files with mapping results, and Tabular files with mapping depth and coverage calculations.\n\nIf you're unsure how to use this workflows, or if you want to see it in action with test datasets, it is included in our detailed training material for foodborne pathogen detection and tracking. You can find step-by-step instructions and practical examples in the following [GTN tutorial](https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.html)\n", + "changelog": "# Changelog\n\n## [0.1.1] 2024-06-28\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_norm/bcftools_norm/1.9+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_norm/bcftools_norm/1.15.1+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_consensus/bcftools_consensus/1.9+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bcftools_consensus/bcftools_consensus/1.15.1+galaxy3`\n\n## [0.1] 2024-06-19\n\nFirst release.\n" + } + ], + "path": "./workflows/microbiome/allele-based-pathogen-identification" + }, + { + "version": 1.2, + "workflows": [ { - "name": "Velocyto-on10X-filtered-barcodes", + "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/Velocyto-on10X-filtered-barcodes.ga", + "primaryDescriptorPath": "/Taxonomy-Profiling-and-Visualization-with-Krona.ga", "testParameterFiles": [ - "/Velocyto-on10X-filtered-barcodes-tests.yml" + "/Taxonomy-Profiling-and-Visualization-with-Krona-tests.yml" ], "authors": [ { - "name": "Lucille Delisle", - "orcid": "0000-0002-1964-4960" + "name": "Engy Nasr", + "orcid": "0000-0001-9047-4215", + "url": "https://orcid.org/0000-0001-9047-4215" + }, + { + "name": "B\u00e9r\u00e9nice Batut", + "orcid": "0000-0001-9852-1987", + "url": "https://orcid.org/0000-0001-9852-1987" + }, + { + "name": "Paul Zierep", + "orcid": "0000-0003-2982-388X", + "url": "https://orcid.org/0000-0003-2982-388X" } ], "definition": { "a_galaxy_workflow": "true", - "annotation": "Run velocyto to get loom with counts of spliced and unspliced", - "comments": [], + "annotation": "Microbiome - Taxonomy Profiling", + "comments": [ + { + "child_steps": [ + 4 + ], + "color": "red", + "data": { + "title": "Taxonomy Visualisation" + }, + "id": 1, + "position": [ + 685, + 167.31666564941406 + ], + "size": [ + 236, + 191 + ], + "type": "frame" + }, + { + "child_steps": [ + 2, + 3, + 1 + ], + "color": "red", + "data": { + "title": "Taxonomy Profiling" + }, + "id": 0, + "position": [ + 4.800000000000011, + 165.01666564941405 + ], + "size": [ + 663.2, + 295.6 + ], + "type": "frame" + } + ], "creator": [ { "class": "Person", - "identifier": "https://orcid.org/0000-0002-1964-4960", - "name": "Lucille Delisle" + "identifier": "0000-0001-9047-4215", + "name": "Engy Nasr", + "url": "https://orcid.org/0000-0001-9047-4215" + }, + { + "class": "Person", + "identifier": "0000-0001-9852-1987", + "name": "B\u00e9r\u00e9nice Batut", + "url": "https://orcid.org/0000-0001-9852-1987" + }, + { + "class": "Person", + "identifier": "0000-0003-2982-388X", + "name": "Paul Zierep" } ], "format-version": "0.1", "license": "MIT", - "release": "0.2", - "name": "Velocyto-on10X-filtered-barcodes", + "release": "0.1", + "name": "Taxonomy Profiling and Visualization with Krona", + "report": { + "markdown": "# Taxonomy Profiling and Visualisation with Krona Workflow Report\n\nIn this workflow you can identify your microbial community, but identifying all possible Taxon found in your samples, from the kingdom level down to the species level. In the application of the pathogen detection, this workflow gives an overview of the possible bacterial found in samples and what might be a possible suspect for pathogenicity.\n\nThe workflow uses Kraken2 tool and allow the user to choose any Kraken2 database or other added ones depending on the user application or the input samples. All Kraken2 tool databases are available in Galaxy. More description about these databases can be found [here](https://benlangmead.github.io/aws-indexes/k2). Other databases can be also added to the tool, just contact us anytime for that. We recommend using StandardPF database.\n\nVisualization is done using Krona Pie Chart, and you can replace it with any other tool. e.g. Phinch interactive tool, which is also available in Galaxy\n\n## Workflow Inputs:\n\nThe per-processing workflow main output (Collection of all samples reads after quality retaining and hosts filtering)\n\n## Workflow Outputs are:\n\n### Taxonomy Tabular Report\n\nThe report shows the abundance of every taxon from the kingdom level down to the species level\n\n```galaxy\nhistory_dataset_display(output=\"converted_kraken_report\")\n```\n\n### Taxonomy Profiling Visualization with Krona\nAn interactive Pie chart showing the different identified taxons along with their percentages, which is one of the ways to visualize the previous taxonomy tabular\n\n```galaxy\nhistory_dataset_as_image(output=\"krona_pie_chart\")\n```\n" + }, "steps": { "0": { - "annotation": "This can be output of CellRanger or STARsolo", + "annotation": "Output collection from the Nanopore Preprocessing workflow", "content_id": null, "errors": null, "id": 0, "input_connections": {}, "inputs": [ { - 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"uuid": "f9aef50f-b31d-44dd-aad6-fe4d520e3b1e", + "uuid": "8b130a6a-6fb3-4498-ac19-0d2df97c09e1", "when": null, "workflow_outputs": [ { - "label": "velocyto loom", - "output_name": "samples", - "uuid": "2899a85c-c198-436f-a409-9bfbdf90c95f" + "label": "krona_pie_chart", + "output_name": "output", + "uuid": "dcc857c6-f579-4c74-84ec-bb6ce3794a56" } ] } }, "tags": [ - "name:single-cell" + "name:Collection", + "name:microGalaxy", + "name:PathoGFAIR", + "name:IWC" ], - "uuid": "33862923-af05-48ba-aec5-14393981cee2", - "version": 4 + "uuid": "a55428c8-9934-4941-93c4-3920b4ba3366", + "version": 58 }, - "readme": "# Velocyto on 10X data\n\nThese workflows simply run velocyto. There are 2 workflows because one can be easily run after the 'fastq-to-matrix-10x' workflows (Velocyto-on10X-from-bundled). The other can be easily run from uploaded datasets (Velocyto-on10X-filtered-barcodes).\n\n## Input datasets\n\n- BAM files with CB and UB: A collection of BAM. It accepts BAM from cellranger or STARsolo with the CB and UB tags (if you use the fastq-to-matrix-10x workflows these tags are automatically included).\n- filtered barcodes (only for Velocyto_on10X_filtered_barcodes workflow): A collection of filtered barcodes (this is what will be used by velocyto). 'Filtered' means that these barcodes have been identified as potential cells. It should not be the whole list of 3 million possible barcodes from cellranger.\n- filtered matrices in bundle (only for Velocyto_on10X_from_bundled workflow): A collection of filtered matrices as bundled (like the one which comes from the fastq-to-matrix-10x workflows): A collection with as many items as samples. For each sample, the item is a list with 3 datasets (barcodes, genes, matrix). The workflow will then extract the items which have the 'barcodes' identifier.\n- gtf file: A file with annotations where exons are and how they are grouped into genes.\n\n## Processing\n\n- If you provided matrices, the first step is to extract barcodes.\n- For both cases velocyto cli is run to get a loom file per sample with spliced and unspliced counts.\n", - "changelog": "# Changelog\n\n## [0.2] 2024-02-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/velocyto_cli/velocyto_cli/0.17.17+galaxy2`\n## [0.1] 2024-01-26\n\nFirst release.\n" + "readme": "# Taxonomy Profiling and Visualisation with Krona\n\nIn this workflow, we identify the different organisms found in our samples by assigning taxonomy levels to the reads starting from the kingdom level down to the species level and visualise the result.\n\nIt\u2019s important to check what might be the species of a possible pathogen to be found, it gets us closer to the investigation as well as discovering possible multiple pathogenetic infections if any existed.\n\nFor taxonomy profiling Kraken2 tool is used along with one of its standard databases available on Galaxy, you can freely choose between Kraken2 different databases based on your input datasets. For visualisation multiple tools can be used, Krona pie chart (as default in this workflow), Phinch interactive tool, Pavian, etc.\n\n## Input Datasets\n- Collection of Pre-Processed Sequenced reads of all samples, ready for further analysis with the other workflows, in a `fastqsanger` or `fastqsanger.gz` format, the output of **Nanopore Preprocessing** workflow.\n\n## Output Datasets\n- Taxonomy profiling Tabular file, visualisation figures and interactive pie charts.\n\nIf you're unsure how to use this workflows, or if you want to see it in action with test datasets, it is included in our detailed training material for foodborne pathogen detection and tracking. You can find step-by-step instructions and practical examples in the following [GTN tutorial](https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.html)\n", + "changelog": "# Changelog\n\n## [0.1] 2024-04-25\n\nFirst release.\n" } ], - "path": "./workflows/scRNAseq/velocyto" + "path": "./workflows/microbiome/taxonomy-profiling-and-visualization-with-krona" }, { "version": 1.2, @@ -26691,1655 +40432,2391 @@ "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/pox-virus-half-genome.ga", + "primaryDescriptorPath": "/Gene-based-Pathogen-Identification.ga", + "testParameterFiles": [ + "/Gene-based-Pathogen-Identification-tests.yml" + ], "authors": [ { - "name": "Viktoria Isabel Schwarz", - "orcid": "0000-0001-6897-1215" + "name": "Engy Nasr", + "orcid": "0000-0001-9047-4215", + "url": "https://orcid.org/0000-0001-9047-4215" }, { - "name": "Wolfgang Maier", - "orcid": "0000-0002-9464-6640" + "name": "B\u00e9r\u00e9nice Batut", + "orcid": "0000-0001-9852-1987", + "url": "https://orcid.org/0000-0001-9852-1987" + }, + { + "name": "Paul Zierep", + "orcid": "0000-0003-2982-388X", + "url": "https://orcid.org/0000-0003-2982-388X" } ], "definition": { "a_galaxy_workflow": "true", - 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By identifying them, we can call a pathogen and its severity level\n\n- Antimicrobial Resistance genes (AMR).\n\n These type of genes have three fundamental mechanisms of antimicrobial resistance that are enzymatic degradation of antibacterial drugs, alteration of bacterial proteins that are antimicrobial targets, and changes in membrane permeability to antibiotics, which will lead to not altering the target site and spread throughput the pathogenic bacteria decreasing the overall fitness of the host.\n\nIn this workflow we:\n\n1. Perform genome assembly to get contigs, i.e. longer sequences, using metaflye (Kolmogorov et al. 2020) then assembly polishing using medaka consensus pipeline and visualizing the assembly graph using Bandage Image (Wick et al. 2015)\n2. Generate reports with AMR genes and VF using ABRicate\n\n## Input Datasets\n- Collection of Pre-Processed Sequenced reads of all samples, ready for further analysis with the other workflows, in a `fastqsanger` or `fastqsanger.gz` format, the output of **Nanopore Preprocessing** workflow.\n\n## Output Datasets\n- FASTA and Tabular files to track genes and visualise our pathogenic identification through out all samples.\n\nIf you're unsure how to use this workflows, or if you want to see it in action with test datasets, it is included in our detailed training material for foodborne pathogen detection and tracking. You can find step-by-step instructions and practical examples in the following [GTN tutorial](https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.html)\n", + "changelog": "# Changelog\n\n## [0.1] 2024-04-18\n\nFirst release.\n" + } + ], + "path": "./workflows/microbiome/gene-based-pathogen-identification" + }, + { + "version": 1.2, + "workflows": [ + { + "name": "main", + "subclass": "Galaxy", + "publish": true, + "primaryDescriptorPath": "/Nanopore-Pre-Processing.ga", + "testParameterFiles": [ + "/Nanopore-Pre-Processing-tests.yml" + ], + "authors": [ + { + "name": "B\u00e9r\u00e9nice Batut", + "orcid": "0000-0001-9852-1987", + "url": "https://orcid.org/0000-0001-9852-1987" + }, + { + "name": "Engy Nasr", + "orcid": "0000-0001-9047-4215", + "url": "https://orcid.org/0000-0001-9047-4215" + }, + { + "name": "Paul Zierep", + "orcid": "0000-0003-2982-388X", + "url": "https://orcid.org/0000-0003-2982-388X" + } + ], + "definition": { + "a_galaxy_workflow": "true", + "annotation": "Microbiome - QC and Contamination Filtering", + "comments": [ + { + "color": "lime", + "data": { + "text": "In this workflow, we recommend nanopore samples since we are using some tools that are specified for nanopore such as: Minimap2, Nanoplot porechp and fastp.\n\nIn order to switch to illumina please remove the nanoplot step, replace porechop and fastp with cutadapt or trimmomatic, and finally replace Minimap2 with Bowtie2.\n\nThis workflow also take single-end reads to switch to paired-end, you have to check this option in most of the tools used. 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"changelog": "# Changelog\n\n## [0.1]\n\nInitial version of Pox Virus Illumina Amplicon workflow (iVar based) for half-genomes sequencing data" + "readme": "# Nanopore Preprocessing\n\nBefore starting any analysis, it is always a good idea to assess the quality of your input data and to discard poor-quality base content by trimming and filtering reads.\n\nGenerally, we are not interested in the host sequences, but rather only those originating from the pathogen itself. It is important to get rid of all host sequences and to only retain sequences that might include a pathogen, both in order to speed up further steps and to avoid host sequences compromising the analysis.\n\n## Input Datasets\n\n- Collection of sequenced Nanopore reads of all samples to be analysed in a `fastqsanger` or `fastqsanger.gz` format.\n\n## Output Datasets\n\n- Collection of Pre-Processed Sequenced reads of all samples, ready for further analysis with the other workflows, in a `fastqsanger` or `fastqsanger.gz` format.\n\n- Tables indicating total number of reads before and after host sequences trimming, and the host sequences percentages found in each sample.\n\nIf you're unsure how to use this workflows, or if you want to see it in action with test datasets, it is included in our detailed training material for foodborne pathogen detection and tracking. You can find step-by-step instructions and practical examples in the following [GTN tutorial](https://training.galaxyproject.org/training-material/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.html)\n", + "changelog": "# Changelog\n\n## [0.1] 2024-04-25\n\nFirst release.\n" } ], - "path": "./workflows/virology/pox-virus-amplicon" + "path": "./workflows/microbiome/nanopore-pre-processing" }, { "version": 1.2, @@ -29009,8 +43520,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.3.8", + "release": "0.4", "name": "Purge-duplicate-contigs-VGP6", + "report": { + "markdown": "\n# Workflow Execution Report\n\nTime workflow was invoked\n\n```galaxy\ninvocation_time()\n```\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Merqury results\n\nMerqury QV:\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_QV\")\n```\n\nMerqury completeness:\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_stats\")\n```\n\nMerqury plots:\n\nspectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-cn.fl\")\n```\n\n\nspectra-asm:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-asm.fl\")\n```\n\n\nhap1/Primary spectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_01.spectra-cn.fl\")\n```\n\n\nhap2/alternate spectra-cn:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_02.spectra-cn.fl\")\n```\n\n\n\n\n## BUSCO results (Vertebrata database)\n\nPurged hap1/primary Assembly\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco on Purged Primary assembly: summary image\")\n```\n\n\n## Assembly statistics\n\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n\n## Nx and Size plots\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n\n\n## Current Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "A simple list containing PacBio data in either fasta or fastq formats with trimmed adapters. 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\"__rerun_remap_job_id__\": null}", + "tool_version": "9.3+galaxy1", + "type": "tool", + "uuid": "94fb5ab8-0ebf-4302-992f-b8ca42b01780", + "when": null, + "workflow_outputs": [ + { + "label": "clean_stats", + "output_name": "outfile", + "uuid": "a022ab8b-306a-4035-8604-810d39f1bde7" } ] } @@ -32435,11 +47473,11 @@ "tags": [ "VGP_curated" ], - "uuid": "4818fdda-7a91-481a-a62f-ccab45a3c0f1", - "version": 2 + "uuid": "b5d0e4ae-3041-4cbe-9d0e-a1140e5469dd", + "version": 10 }, - "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Primary Assembly (hap1) [fasta] (Generated by the contigging workflow)\n3. Alternate Assembly (hap2) [fasta] (Generated by the contigging workflow)\n4. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n5. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n6. Estimated Genome Size [txt]\n7. Name of first haplotype\n8. Name of second haplotype\n9. Lineage of you species for Busco Orthologs\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies\n", - "changelog": "# Changelog\n\n\n## [0.3.8] 2024-04-23\n\n### Added\n\n- Add Busco Gff output\n\n## [0.3.7] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n## [0.3.6] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0`\n\n## [0.3.5] 2024-03-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n\n## [0.3.4] 2024-02-15\n\n- Remove tag filtering\n- Add merqury histogram outputs\n\n## [0.3.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.3.2] - 2023-11-15\n\n### Added\n\n- more descriptive lables for inputs\n\n## [0.3.1] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.3] - 2023-11-08\n\n### Added\n\n- Made BUSCO lineage selectable from workflow launch interface\n\n### Changed\n\n- Change BUSCO lineage input parameter name from `Provide lineage for BUSCO (e.g., Vertebrata)` to `Lineage`\n\n\n## [0.2.0] - 2023-11-07\n\n### Added\n\n- Tag filtering for inputs\n- Changed parameters of gfastats for postprocessing of contigs generated with purge_dups. Specfically:\n - \"Terminal overlap selection\" is set to \"Yes\"\n - \"Generated the initial set of paths\" is set to \"No\"\n\n\n## [0.1.1] - 2023-11-01\n\n### Added\n\n- More explicit tags for readability\n\n\n## [0.1] - 2023-10-26\n\n### Added\n\n- Workflow for purging duplication in contigs\n" + "readme": "# Purge Duplicate Contigs\n\nPurge contigs marked as duplicates by purge_dups (could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Primary Assembly (hap1) [fasta] (Generated by the contigging workflow)\n3. Alternate Assembly (hap2) [fasta] (Generated by the contigging workflow)\n4. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n5. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n6. Estimated Genome Size [txt]\n7. Database for busco lineage (recommended: latest) \n8. Lineage of your species for Busco Orthologs (recommended: vertebrata)\n9. Name of first haplotype\n10. Name of second haplotype\n\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies\n", + "changelog": "# Changelog\n\n## [0.4] 2024-08-13\n\n### Added\n\n- Workflow report\n\n### Changed\n\n- Expose Busco lineage database parameter\n- Fix bug that was causing issues when merging the assembly statistics: The presence of the '#' character caused the tables to join incorrectly, and the numbers did not match the metrics\n\n## [0.3.8] 2024-04-23\n\n### Added\n\n- Add Busco Gff output\n\n## [0.3.7] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n## [0.3.6] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0`\n\n## [0.3.5] 2024-03-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n\n## [0.3.4] 2024-02-15\n\n- Remove tag filtering\n- Add merqury histogram outputs\n\n## [0.3.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.3.2] - 2023-11-15\n\n### Added\n\n- more descriptive lables for inputs\n\n## [0.3.1] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.3] - 2023-11-08\n\n### Added\n\n- Made BUSCO lineage selectable from workflow launch interface\n\n### Changed\n\n- Change BUSCO lineage input parameter name from `Provide lineage for BUSCO (e.g., Vertebrata)` to `Lineage`\n\n\n## [0.2.0] - 2023-11-07\n\n### Added\n\n- Tag filtering for inputs\n- Changed parameters of gfastats for postprocessing of contigs generated with purge_dups. Specfically:\n - \"Terminal overlap selection\" is set to \"Yes\"\n - \"Generated the initial set of paths\" is set to \"No\"\n\n\n## [0.1.1] - 2023-11-01\n\n### Added\n\n- More explicit tags for readability\n\n\n## [0.1] - 2023-10-26\n\n### Added\n\n- Workflow for purging duplication in contigs\n" } ], "path": "./workflows/VGP-assembly-v2/Purge-duplicate-contigs-VGP6" @@ -32467,6 +47505,7 @@ "definition": { "a_galaxy_workflow": "true", "annotation": "", + "comments": [], "creator": [ { "class": "Organization", @@ -32480,8 +47519,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.1.3", + "release": "0.1.4", "name": "Scaffolding-BioNano-VGP7", + "report": { + "markdown": "\n# Workflow Execution Report\n\n## Invocation time\n```galaxy\ninvocation_time()\n```\n\n## Assembly statistics\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n## Size plot\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n\n## Nx plot\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n## Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "", @@ -32589,13 +47631,7 @@ "type": "data_input", "uuid": "404dfe4f-8590-486e-b632-a0564010e213", "when": null, - "workflow_outputs": [ - { - "label": null, - "output_name": "output", - "uuid": "5957fae6-c14a-464a-aedb-0695d68d69dd" - } - ] + "workflow_outputs": [] }, "4": { "annotation": "", @@ -32647,12 +47683,7 @@ "output_name": "output" } }, - "inputs": [ - { - "description": "runtime parameter for tool gfastats", - "name": "mode_condition" - } - ], + "inputs": [], "label": null, "name": "gfastats", "outputs": [ @@ -32818,12 +47849,7 @@ "output_name": "ngs_contigs_scaffold_agp" } }, - "inputs": [ - { - "description": "runtime parameter for tool gfastats", - "name": "mode_condition" - } - ], + "inputs": [], "label": null, "name": "gfastats", "outputs": [ @@ -32883,12 +47909,7 @@ "output_name": "output" } }, - "inputs": [ - { - "description": "runtime parameter for tool gfastats", - "name": "mode_condition" - } - ], + "inputs": [], "label": null, "name": "gfastats", "outputs": [ @@ -33028,7 +48049,58 @@ }, "11": { "annotation": "", + "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", + "errors": null, "id": 11, + "input_connections": { + "infile": { + "id": 9, + "output_name": "stats" + } + }, + "inputs": [], + "label": null, + "name": "Replace", + "outputs": [ + { + "name": "outfile", + "type": "input" + } + ], + "position": { + "left": 2430.427837638421, + "top": 236.31263207430692 + }, + "post_job_actions": { + "HideDatasetActionoutfile": { + "action_arguments": {}, + "action_type": "HideDatasetAction", + "output_name": "outfile" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", + "tool_shed_repository": { + "changeset_revision": "fbf99087e067", + "name": "text_processing", + "owner": "bgruening", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"find_and_replace\": [{\"__index__\": 0, \"find_pattern\": \"#\", \"replace_pattern\": \"Number of\", \"is_regex\": false, \"global\": true, \"caseinsensitive\": false, \"wholewords\": false, \"skip_first_line\": false, \"searchwhere\": {\"searchwhere_select\": \"line\", \"__current_case__\": 0}}], \"infile\": {\"__class__\": \"RuntimeValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "9.3+galaxy1", + "type": "tool", + "uuid": "292e7cba-fa66-4f7e-935d-504d64a304cc", + "when": null, + "workflow_outputs": [ + { + "label": "clean_stats", + "output_name": "outfile", + "uuid": "4a0bdf73-d0f9-4c54-9c82-9a63e19e4695" + } + ] + }, + "12": { + "annotation": "", + "id": 12, "input_connections": { "gfa_stats": { "id": 10, @@ -33388,7 +48460,7 @@ ] } }, - "tags": "", + "tags": [], "uuid": "0d43f853-69ee-4f89-9a1d-50cfa45ec0fd" }, "tool_id": null, @@ -33397,14 +48469,14 @@ "when": null, "workflow_outputs": [] }, - "12": { + "13": { "annotation": "", "content_id": "Cut1", "errors": null, - "id": 12, + "id": 13, "input_connections": { "input": { - "id": 11, + "id": 12, "output_name": "gfastats data for plotting" } }, @@ -33436,14 +48508,14 @@ "when": null, "workflow_outputs": [] }, - "13": { + "14": { "annotation": "", "content_id": "Cut1", "errors": null, - "id": 13, + "id": 14, "input_connections": { "input": { - "id": 11, + "id": 12, "output_name": "gfastats data for plotting" } }, @@ -33475,14 +48547,14 @@ "when": null, "workflow_outputs": [] }, - "14": { + "15": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1", "errors": null, - "id": 14, + "id": 15, "input_connections": { "input1": { - "id": 12, + "id": 13, "output_name": "out_file1" } }, @@ -33528,14 +48600,14 @@ } ] }, - "15": { + "16": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1", "errors": null, - "id": 15, + "id": 16, "input_connections": { "input1": { - "id": 13, + "id": 14, "output_name": "out_file1" } }, @@ -33585,11 +48657,11 @@ "tags": [ "VGP_curated" ], - "uuid": "0c8b790c-4dce-4e9b-b942-da71a9e9b27e", - "version": 5 + "uuid": "9fd3c0de-a497-47dc-96e3-0f3e1998173d", + "version": 6 }, "readme": "# Scaffolding with Bionano\n\nScaffolding using Bionano optical map data\n\n## Inputs\n\n1. Bionano data [cmap]\n2. Estimated genome size [txt]\n3. Phased assembly generated by Hifiasm [gfa1]\n\n## Outputs\n\n1. Scaffolds\n2. Non-scaffolded contigs\n3. QC: Assembly statistics\n4. QC: Nx plot\n5. QC: Size plot", - "changelog": "# Changelog\n\n## [0.1.3] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n\n## [0.1.2] 2024-03-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.1.1] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/bionano_scaffold/bionano_scaffold/3.7.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/bionano_scaffold/bionano_scaffold/3.7.0+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1] - 2023-11-01\n\nAddition of the workflow to the iwc repository.\n" + "changelog": "# Changelog\n\n## [0.1.4] 2024-08-13\n\n- Addition of workflow report\n\n## [0.1.3] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n\n## [0.1.2] 2024-03-04\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n\n## [0.1.1] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/bionano_scaffold/bionano_scaffold/3.7.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/bionano_scaffold/bionano_scaffold/3.7.0+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1] - 2023-11-01\n\nAddition of the workflow to the iwc repository.\n" } ], "path": "./workflows/VGP-assembly-v2/Scaffolding-Bionano-VGP7" @@ -33624,8 +48696,11 @@ ], "format-version": "0.1", "license": "BSD-3-Clause", - "release": "0.1.5", + "release": "0.3", "name": "Assembly-decontamination-VGP9", + "report": { + "markdown": "\n# Workflow Execution Report\n\n### Worflow ran on: \n\n```galaxy\ninvocation_time()\n```\n\n# List of contaminants\n\n\r\n```galaxy\nhistory_dataset_as_table(output=\"contaminants_table\")\n```\r\n\n\n# List of Mitochondrial scaffolds\n\r\n```galaxy\nhistory_dataset_as_table(output=\"mito_scaff_names\")\n```\r\n\n\n\n\n## Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "", @@ -33643,8 +48718,8 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 0, - "top": 431.99609375 + "left": 0.0, + "top": 573.2100224386197 }, "tool_id": null, "tool_state": "{\"optional\": false, \"format\": [\"fasta\"], \"tag\": null}", @@ -33670,8 +48745,8 @@ "name": "Input parameter", "outputs": [], "position": { - 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"id": 13, + "id": 11, "input_connections": { "input_file": { "id": 0, "output_name": "output" }, "target_condition|exclude_bed": { - "id": 12, + "id": 10, "output_name": "out_file1" } }, @@ -34205,8 +49216,8 @@ } ], "position": { - "left": 3050.21875, - "top": 650.49609375 + "left": 2977.7819561709443, + "top": 798.078125 }, "post_job_actions": {}, "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/gfastats/gfastats/1.3.6+galaxy0", @@ -34233,10 +49244,10 @@ "tags": [ "VGP_curated" ], - "uuid": "f6d8df21-f1dc-493c-bfab-e2cbecb8873d", - "version": 1 + "uuid": "aa4960d9-198d-4990-a393-a98efcd3070a", + "version": 3 }, - "changelog": "# Changelog\n\n## [0.1.5] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n\n\n## [0.1.4] 2024-03-11\n\n- Fix regex that was causing the headers to change. \n\n\n## [0.1.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.2] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy1`\n\n## [0.1.1] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.10.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.10.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy0`\n\n## [0.1] - 2023-11-07\n\n- Creation of workflow for Assembly decontamination\n" + "changelog": "# Changelog\n\n## [0.3] 2024-08-26\n\n- Changed the regex to only change the sequences. The workflow is now more robust to different (non VGP) scaffold names and VGP names with prefixes. \n- Reduce the number of steps in the workflow. \n\n## [0.2] 2024-08-15\n\n- Bug Fix: a missing regex caused the list of contaminants to empty out and the contaminants were not removed. \n\n## [0.1.6] 2024-06-10\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/kraken2/kraken2/2.1.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/kraken2/kraken2/2.1.3+galaxy1`\n\n## [0.1.5] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n\n\n## [0.1.4] 2024-03-11\n\n- Fix regex that was causing the headers to change. \n\n\n## [0.1.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.2] 2023-11-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy1`\n\n## [0.1.1] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.10.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_dustmasker_wrapper/2.14.1+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.10.1+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/ncbi_blast_plus/ncbi_blastn_wrapper/2.14.1+galaxy0`\n\n## [0.1] - 2023-11-07\n\n- Creation of workflow for Assembly decontamination\n" } ], "path": "./workflows/VGP-assembly-v2/Assembly-decontamination-VGP9" @@ -34264,6 +49275,7 @@ "definition": { "a_galaxy_workflow": "true", "annotation": "", + "comments": [], "creator": [ { "class": "Organization", @@ -34277,8 +49289,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.1.5", + "release": "0.1.7", "name": "kmer-profiling-hifi-VGP1", + "report": { + "markdown": "\n# Workflow Execution Report\n\n\n```galaxy\ninvocation_time()\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"GenomeScope linear plot\")\n```\n\n```galaxy\nhistory_dataset_as_image(output=\"GenomeScope log plot\")\n```\n\n```galaxy\nhistory_dataset_as_image(output=\"GenomeScope transformed linear plot\")\n```\n\n```galaxy\nhistory_dataset_as_image(output=\"GenomeScope transformed log plot\")\n```\n\n\n## Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "A simple list collection containing PacBio data in either fastq or fasta format", @@ -34296,7 +49311,7 @@ "name": "Input dataset collection", "outputs": [], "position": { - "left": 0.0, + "left": 0, "top": 86.5078125 }, "tool_id": null, @@ -34332,13 +49347,7 @@ "type": "parameter_input", "uuid": "946bcadd-8ab0-4595-9985-abb574539844", "when": null, - "workflow_outputs": [ - { - "label": null, - "output_name": "output", - "uuid": "18b69ad3-4c09-46f5-9a4c-bf4097b37fef" - } - ] + "workflow_outputs": [] }, "2": { "annotation": "Ploidy for the organism being assembled", @@ -34365,13 +49374,7 @@ "type": "parameter_input", "uuid": "e3848560-55a2-42a5-ac1a-487ccf084d92", "when": null, - "workflow_outputs": [ - { - "label": null, - "output_name": "output", - "uuid": "1fea95fa-67d6-408d-94b6-264107cc19a1" - } - ] + "workflow_outputs": [] }, "3": { "annotation": "", @@ -34522,7 +49525,7 @@ }, "6": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "errors": null, "id": 6, "input_connections": { @@ -34627,15 +49630,15 @@ "output_name": "transformed_log_plot" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "tool_shed_repository": { - "changeset_revision": "01210c4e9144", + "changeset_revision": "460fad600dce", "name": "genomescope", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"advanced_options\": {\"topology\": null, \"initial_repetitiveness\": null, \"initial_heterozygosities\": \"\", \"transform_exp\": null, \"testing\": true, \"true_params\": \"\", \"trace_flag\": false, \"num_rounds\": null}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"kmer_length\": {\"__class__\": \"ConnectedValue\"}, \"lambda\": null, \"max_kmercov\": null, \"output_options\": {\"output_files\": [\"model_output\", \"summary_output\"], \"no_unique_sequence\": false}, \"ploidy\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.0+galaxy2", + "tool_version": "2.0.1+galaxy0", "type": "tool", "uuid": "955de351-ef19-42dc-89d7-ca213994515a", "when": null, @@ -34677,11 +49680,11 @@ "Reviewed", "VGP" ], - "uuid": "7542ffba-d083-415e-b745-08d9503debc4", - "version": 4 + "uuid": "0808b15a-7e3e-4b06-b804-f3d2cc73981a", + "version": 2 }, "readme": "# VGP Workflow #1\n\nThis workflow produces a Meryl database and Genomescope outputs that will be used to determine parameters for following workflows, and assess the quality of genome assemblies. Specifically, it provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality.\n\n### Inputs\n\n- A collection of Hifi long reads in FASTQ format\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl Database of kmer counts\n- GenomeScope\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n\n ![image](https://github.com/galaxyproject/iwc/assets/4291636/565238fc-f8a9-46ac-8b31-6276410fa436)\n", - "changelog": "# Changelog\n\n## [0.1.5] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.4] 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n## [0.1.3] 2023-11-09\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2`\n\n## [0.1.2] - 2023-11-07\n### Changed\n- Added tag filtering for inputs\n\n## [0.1.1] - 2023-10-30\n### Changed\n- Names of the workflow and viles for consistency with other VGP workflows\n- Labels and tags for user readability\n \n## [0.1] - 2021-08-26\n### Added\n- First version of the workflow. \n" + "changelog": "# Changelog\n\n## [0.1.7] 2024-08-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0`\n\n## [0.1.6] 2024-07-12\n\n- Add workflow report\n\n## [0.1.5] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.4] 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n## [0.1.3] 2023-11-09\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2`\n\n## [0.1.2] - 2023-11-07\n### Changed\n- Added tag filtering for inputs\n\n## [0.1.1] - 2023-10-30\n### Changed\n- Names of the workflow and viles for consistency with other VGP workflows\n- Labels and tags for user readability\n \n## [0.1] - 2021-08-26\n### Added\n- First version of the workflow. \n" } ], "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-VGP1" @@ -34723,8 +49726,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.6", + "release": "0.7.1", "name": "Purging-duplicates-one-haplotype-VGP6b ", + "report": { + "markdown": "\n# Workflow Execution Report\n\nTime workflow was invoked\n\n```galaxy\ninvocation_time()\n```\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Merqury results\n\nMerqury QV:\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_QV\")\n```\n\nMerqury completeness:\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_stats\")\n```\n\nMerqury plots:\n\nspectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-cn.fl\")\n```\n\n\nspectra-asm:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-asm.fl\")\n```\n\n\nhap1 spectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_01.spectra-cn.fl\")\n```\n\n\nhap2 spectra-cn:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_02.spectra-cn.fl\")\n```\n\n\n\n\n## BUSCO results (Vertebrata database)\n\nPurged Assembly\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco on Purged Primary assembly: summary image\")\n```\n\n\n## Assembly statistics\n\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n\n## Nx and Size plots\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n\n\n## Current Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "", @@ -34743,7 +49749,7 @@ "outputs": [], "position": { "left": 0, - "top": 73.94776585535702 + "top": 473.0537740808015 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\"}", @@ -34770,7 +49776,7 @@ "outputs": [], "position": { "left": 558.0468791193098, - "top": 445.9442866309247 + "top": 845.0502948563692 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", @@ -34797,7 +49803,7 @@ "outputs": [], "position": { "left": 432.94921875, - "top": 976.4234574650022 + "top": 1375.5294656904466 }, "tool_id": null, "tool_state": "{\"optional\": false, \"format\": [\"fasta\"], \"tag\": \"\"}", @@ -34824,7 +49830,7 @@ "outputs": [], "position": { "left": 1972.4566892558003, - "top": 308.9738000531734 + "top": 708.0798082786179 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\"}", @@ -34843,15 +49849,15 @@ "inputs": [ { "description": "", - "name": "Assembly to leave alone (need this for merqury)" + "name": "Assembly to leave alone (For Merqury comparison)" } ], - "label": "Assembly to leave alone (need this for merqury)", + "label": "Assembly to leave alone (For Merqury comparison)", "name": "Input dataset", "outputs": [], "position": { "left": 1972.4566892558003, - "top": 428.92176735660996 + "top": 828.0277755820543 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\"}", @@ -34878,7 +49884,7 @@ "outputs": [], "position": { "left": 1693.6113702942387, - "top": 1098.9651229518047 + "top": 1498.071131177249 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\"}", @@ -34897,30 +49903,57 @@ "inputs": [ { "description": "", - "name": "Name of un-altered assembly" + "name": "Database for Busco Lineage" } ], - "label": "Name of un-altered assembly", + "label": "Database for Busco Lineage", "name": "Input parameter", "outputs": [], "position": { - "left": 2540.373300171866, - "top": 399.9460505318975 + "left": 1705.6584960887728, + "top": 1674.0155168754275 }, 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a single haplotype(could be haplotypic duplication or overlap duplication)\nThis workflow is the 6th workflow of the VGP pipeline. It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n2. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n3. Assembly to purge (e.g. hap1) [fasta] (Generated by the contigging workflow)\n4. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n5. Assembly to leave alone (used for merqury statistics) (e.g. hap2) [fasta] (Generated by the contigging workflow)\n6. Estimated Genome Size [txt]\n7. Database for busco lineage (recommended: latest)\n8. Busco lineage (recommended: vertebrata)\n9. Name of un-altered assembly\n10. Name of purged assembly\n\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies", + "changelog": "# Changelog\n\n## [0.7.1] 2024-08-13\n\n- Expose Busco parameters : \n - Lineage database \n - Lineage\n\n## [0.7] 2024-07-24\n\n### Added\n\n- Workflow report\n\n### Changed\n\n- Fix bug where the columns of the assembly statistics didn't join properly.\n- Rename some outputs for clarity\n\n## [0.6] 2024-04-23\n\n### Changed\n\n- Add Merqury histogram output\n- Add Busco gff output\n- Unhide Merqury QV output\n\n## [0.5] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n\n## [0.4] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0`\n\n## [0.2] 2024-02-19\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.5.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1] - 2024-02-07\n\n### Added\n\n- Workflow for purging duplication in contigs in single haplotype\n" + } + ], + "path": "./workflows/VGP-assembly-v2/Purge-duplicates-one-haplotype-VGP6b" + }, + { + "version": 1.2, + 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It is meant to be run after one of the contigging steps (Workflow 3, 4, or 5)\n\n## Inputs\n\n1. Genomescope model parameters [txt] (Generated by the k-mer profiling workflow)\n1. Hifi long reads - trimmed [fastq] (Generated by Cutadapt in the contigging workflow)\n2. Assembly to purge (e.g. hap1) [fasta] (Generated by the contigging workflow)\n3. K-mer database [meryldb] (Generated by the k-mer profiling workflow)\n4. Estimated Genome Size [txt]\n5. Assembly to leave alone (used for merqury statistics) (e.g. hap2) [fasta] (Generated by the contigging workflow)\n6. Name of un-altered assembly\n7. Name of purged assembly\n\n\n## Outputs\n\n1. Haplotype 1 purged assembly (Fasta and gfa)\n2. Haplotype 2 purged assembly (Fasta and gfa)\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies", - "changelog": "# Changelog\n\n## [0.6] 2024-04-23\n\n### Changed\n\n- Add Merqury histogram output\n- Add Busco gff output\n- Unhide Merqury QV output\n\n## [0.5] 2024-04-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.28+galaxy0`\n\n## [0.4] 2024-03-25\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.27+galaxy0`\n\n## [0.2] 2024-02-19\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.24+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/minimap2/minimap2/2.26+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.5.0+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1] - 2024-02-07\n\n### Added\n\n- Workflow for purging duplication in contigs in single haplotype\n" + "uuid": "57920bf9-1741-4170-badf-39fdfcdaa2e9", + "version": 4 + } } ], - "path": "./workflows/VGP-assembly-v2/Purge-duplicates-one-haplotype-VGP6b" + "path": "./workflows/VGP-assembly-v2/Mitogenome-assembly-VGP0" }, { "version": 1.2, @@ -37648,17 +53483,17 @@ "name": "main", "subclass": "Galaxy", "publish": true, - "primaryDescriptorPath": "/Mitogenome-Assembly-VGP0.ga", + "primaryDescriptorPath": 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\"plot_title_customization\": {\"axis_customization\": \"default\", \"__current_case__\": 0}, \"gridlinecust\": \"default\", \"transform\": \"none\", \"scaling\": {\"plot_scaling\": \"Automatic\", \"__current_case__\": 0}, \"theme\": \"bw\", \"legend\": \"yes\"}, \"input1\": {\"__class__\": \"ConnectedValue\"}, \"out\": {\"unit_output_dim\": \"in\", \"width_output_dim\": \"7.0\", \"height_output_dim\": \"7.0\", \"dpi_output_dim\": \"300.0\", \"additional_output_format\": \"none\"}, \"title\": \"\", \"xlab\": \"Scaffold number\", \"xplot\": \"2\", \"ylab\": \"Cumulative Size (Mb)\", \"yplot\": \"3\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "3.4.0+galaxy1", "type": "tool", - "uuid": "5207adc9-f36a-42e9-8631-e01da77ac446", + "uuid": "3c8f4a21-e941-4e58-8d11-0f66c4a7d2c0", "when": null, "workflow_outputs": [ { - "label": "output_file", - "output_name": "output_file", - "uuid": "6f918a08-1ca1-4d6e-a4d8-7e65e13a65ed" + "label": "Size Plot", + "output_name": "output1", + "uuid": "7051d948-3249-4f85-b772-6bae20c99f4d" } ] } }, - "tags": [ - "Reviewed", - "VGP" - ], - "uuid": "57920bf9-1741-4170-badf-39fdfcdaa2e9", - "version": 4 - } + "tags": [], + "uuid": "40c0a173-1805-46c6-9005-5ead67bc9f48", + "version": 11 + }, + "readme": "## Generate Nx and Size plot for multiple assemblies\n\n\n### Inputs\n\nCollection of fasta files. The name of each item in the collection will be used as label for the Nx and Size plots.\n\n### Outputs\n\n\n1. Nx plot \n2. Size plot ", + "changelog": "# Changelog\n\n## [0.1.1] 2024-06-24\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n\n## [0.1] - 2024-05-11\n\nAddition of the workflow to the iwc repository." } ], - "path": "./workflows/VGP-assembly-v2/Mitogenome-assembly-VGP0" + "path": "./workflows/VGP-assembly-v2/Plot-Nx-Size" }, { "version": 1.2, @@ -38050,8 +54229,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.2.3", + "release": "0.2.7", "name": "Scaffolding-HiC-VGP8", + "report": { + "markdown": "# Workflow Execution Report\n\nTime workflow was invoked\n\n```galaxy\ninvocation_time()\n```\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n\n## BUSCO results (Vertebrata database)\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco Summary image\")\n```\n\n\n## Assembly statistics\n\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n\n## Nx and Size plots\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n## PretextMap\n\n### Before Scaffolding\n\n\r\n```galaxy\nhistory_dataset_as_image(output=\"Pretext Map Before HiC scaffolding\")\n```\r\n\n\n### After Scaffolding\r\n```galaxy\nhistory_dataset_as_image(output=\"Pretext Map After HiC scaffolding\")\n```\r\n\n\n\n\n## Current Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "The input GFA must conform to gfa1.2 standards, i.e. should have 'P' lines defined. Output GFAs from assemblers can be run through a GFA->GFA conversion using gfastats to ensure this. \n", @@ -38105,19 +54287,40 @@ "type": "data_input", "uuid": "13cd4c1c-968b-4077-9845-e06738a2efb8", "when": null, - "workflow_outputs": [ + "workflow_outputs": [] + }, + "2": { + "annotation": "", + "content_id": null, + "errors": null, + "id": 2, + "input_connections": {}, + "inputs": [ { - "label": null, - "output_name": "output", - "uuid": "7d2238e1-fe33-4033-b9a7-65d789cda7b7" + "description": "", + "name": "Database for Busco Lineage" } - ] + ], + "label": "Database for Busco Lineage", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 68.35425980970838, + "top": 413.51555364806376 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "1f4997fc-1880-4416-8857-2a63d3501a6c", + "when": null, + "workflow_outputs": [] }, - "2": { + "3": { "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis\n", "content_id": null, "errors": null, - 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"id": 4, + "id": 5, "input_connections": {}, "inputs": [ { @@ -38200,11 +54397,11 @@ "when": null, "workflow_outputs": [] }, - "5": { + "6": { "annotation": "Restriction enzymes used in preparation of Hi-C libraries.", "content_id": null, "errors": null, - "id": 5, + "id": 6, "input_connections": {}, "inputs": [ { @@ -38225,19 +54422,13 @@ "type": "parameter_input", "uuid": "b899a210-60c2-4e9e-8a34-e1bc82ef373d", "when": null, - "workflow_outputs": [ - { - "label": null, - "output_name": "output", - "uuid": "eeae44ef-4def-43d0-bc15-c0f0f96c6f05" - } - ] + "workflow_outputs": [] }, - "6": { + "7": { "annotation": "Estimated genome size from contiging workflow", "content_id": null, "errors": null, - "id": 6, + "id": 7, "input_connections": {}, "inputs": [ { @@ -38260,11 +54451,11 @@ "when": null, "workflow_outputs": [] }, - "7": { + "8": { "annotation": "", "content_id": null, "errors": null, - "id": 7, + "id": 8, "input_connections": {}, "inputs": [ { @@ -38285,22 +54476,16 @@ "type": "data_input", "uuid": "bc993517-ae23-417d-8eb1-891a127f544c", "when": null, - 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"27": { + "29": { "annotation": "", "content_id": "Cut1", "errors": null, - "id": 27, + "id": 29, "input_connections": { "input": { - "id": 24, + "id": 26, "output_name": "gfastats data for plotting" } }, @@ -39687,14 +55927,14 @@ "when": null, "workflow_outputs": [] }, - "28": { + "30": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy1", "errors": null, - "id": 28, + "id": 30, "input_connections": { "input": { - "id": 25, + "id": 27, "output_name": "outfile" } }, @@ -39734,14 +55974,14 @@ "when": null, "workflow_outputs": [] }, - "29": { + "31": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.30.0+galaxy2", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.31.1+galaxy0", "errors": null, - "id": 29, + "id": 31, "input_connections": { "input": { - "id": 25, + "id": 27, "output_name": "outfile" } }, @@ -39765,28 +56005,28 @@ "output_name": "output" } }, - 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"id": 26, + "id": 28, "output_name": "out_file1" } }, @@ -39839,14 +56079,14 @@ } ] }, - "31": { + "33": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1", "errors": null, - "id": 31, + "id": 33, "input_connections": { "input1": { - "id": 27, + "id": 29, "output_name": "out_file1" } }, @@ -39899,14 +56139,14 @@ } ] }, - "32": { + "34": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy2", "errors": null, - "id": 32, + "id": 34, "input_connections": { "input": { - "id": 28, + "id": 30, "output_name": "pretext_map_out" } }, @@ -39951,14 +56191,14 @@ "when": null, "workflow_outputs": [] }, - "33": { + "35": { "annotation": "", "content_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy1", "errors": null, - "id": 33, + "id": 35, "input_connections": { "infile": { - "id": 29, + "id": 31, "output_name": "output" } }, @@ -39998,14 +56238,14 @@ "when": null, "workflow_outputs": [] }, - "34": { + "36": { "annotation": "", "content_id": "__EXTRACT_DATASET__", "errors": null, - "id": 34, + "id": 36, "input_connections": { "input": { - "id": 32, + "id": 34, "output_name": "pretext_snap_out" } }, @@ -40049,11 +56289,11 @@ "tags": [ "VGP_curated" ], - "uuid": "a45c5bd9-6b56-40ff-a9ea-ba420a683f42", - "version": 3 + "uuid": "745110d9-a4ab-452e-b49a-7ee72f626975", + "version": 1 }, - "readme": "# Scaffolding with HiC data\n\nThis workflow perfoms scaffolding using HiC data with YAHS. It is designed to be run as part of one the VGP analysis trajectories. \nExample of trajectory : \n- VGP1 : Kmer profiling \n- VGP4 : Genome assembly with HiC phasing\n- VGP6 : Purge duplicated haplotigs\n- VGP8 : Scaffolding with HiC\n\n## Inputs\n\n1. Scaffolded assembly [fasta]\n2. Concatenated HiC forward reads [fastq]\n3. Concatenated HiC reverse reads [fastq]\n4. Restriction enzyme sequence [txt]\n5. Estimated genome size [txt]\n\n### Outputs\n\n1. Scaffolds in [fasta] and [gfa] format\n2. QC: Assembly statistics\n3. QC: Nx plot\n4. QC: Size plot\n5. QC: BUSCO report\n6. QC: Pretext Maps before and after scaffolding", - "changelog": "# Changelog\n\n## [0.2.3] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy1`\n\n## [0.2.2] 2024-02-05\n\n### Manual update\n\n- remove tag filtering\n- set \"Show grid\" of Pretext Snapshot to \"yes\"\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy0`\n\n\n## [0.2.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.2] - 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bwa_mem2/bwa_mem2/2.2.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bwa_mem2/bwa_mem2/2.2.1+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bellerophon/bellerophon/1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bellerophon/bellerophon/1.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.1] - 2023-10-26\n\nAdded tags for better visibility of outputs in the history, and exposure of the BUSCO lineage parameter\n\n## [0.1] - 2023-09-27\n\nCreation of the workflow and tests\n\n" + "readme": "# Scaffolding with HiC data\n\nThis workflow perfoms scaffolding using HiC data with YAHS. It is designed to be run as part of one the VGP analysis trajectories. \nExample of trajectory : \n- VGP1 : Kmer profiling \n- VGP4 : Genome assembly with HiC phasing\n- VGP6 : Purge duplicated haplotigs\n- VGP8 : Scaffolding with HiC\n\n## Inputs\n\n1. Scaffolded assembly [fasta]\n2. Database for busco lineage (recommended: latest)\n3. Busco lineage (recommended: vertebrata)\n4. Concatenated HiC forward reads [fastq]\n5. Concatenated HiC reverse reads [fastq]\n6. Restriction enzyme sequence (recommended for VGP data: Arima Hi-C 2.0)\n7. Estimated genome size [txt]\n\n\n### Outputs\n\n1. Scaffolds in [fasta] and [gfa] format\n2. QC: Assembly statistics\n3. QC: Nx plot\n4. QC: Size plot\n5. QC: BUSCO report\n6. QC: Pretext Maps before and after scaffolding", + "changelog": "# Changelog\n\n## [0.2.7] 2024-08-13\n\n- Expose Busco lineage database parameter\n\n## [0.2.6] 2024-08-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy2`\n\n## [0.2.5] 2024-07-31\n\n- Addition of Workflow report\n\n## [0.2.4] 2024-05-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.30.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bedtools/bedtools_bamtobed/2.31.1+galaxy0`\n\n## [0.2.3] 2024-04-01\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy1`\n\n## [0.2.2] 2024-02-05\n\n### Manual update\n\n- remove tag filtering\n- set \"Show grid\" of Pretext Snapshot to \"yes\"\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pretext_map/pretext_map/0.1.9+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pretext_snapshot/pretext_snapshot/0.0.3+galaxy2`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sort_header_tool/9.3+galaxy0`\n\n\n## [0.2.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.2] - 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/bwa_mem2/bwa_mem2/2.2.1+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bwa_mem2/bwa_mem2/2.2.1+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/bellerophon/bellerophon/1.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/bellerophon/bellerophon/1.0+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/yahs/yahs/1.2a.2+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.1] - 2023-10-26\n\nAdded tags for better visibility of outputs in the history, and exposure of the BUSCO lineage parameter\n\n## [0.1] - 2023-09-27\n\nCreation of the workflow and tests\n\n" } ], "path": "./workflows/VGP-assembly-v2/Scaffolding-HiC-VGP8" @@ -40104,8 +56344,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.1.10", + "release": "0.2.2", "name": "Assembly-Hifi-HiC-phasing-VGP4", + "report": { + "markdown": "\n# Workflow Execution Report\n\nTime workflow was invoked:\n\n```galaxy\ninvocation_time()\n```\nGalaxy version :\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Raw unitig graph\n\n```galaxy\nhistory_dataset_as_image(output=\"raw unitig graph image\")\n```\n\n## Merqury results\n\n### Merqury QV\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_qv\")\n```\n\n### Merqury completeness\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_stats\")\n```\n\n### Merqury plots\n\n\nspectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-cn.fl\")\n```\n\nspectra-asm:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-asm.fl\")\n```\n\nhap1 spectra-cn:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_01.spectra-cn.fl\")\n```\n\nhap2 spectra-cn:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_02.spectra-cn.fl\")\n```\n\n## BUSCO results (Vertebrata database)\n\nHap1\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco Summary Image Hap1\")\n```\n\nHap2\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco Summary Image Hap2\")\n```\n\n## Assembly statistics\n\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n\n## Nx and Size plots\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n\n\n## Current Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "A simple list containing PacBio data in either fasta or fastq formats.", @@ -40243,11 +56486,44 @@ "workflow_outputs": [] }, "5": { - "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis", + "annotation": "", "content_id": null, "errors": null, "id": 5, "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Database for Busco Lineage" + } + ], + "label": "Database for Busco Lineage", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 81.55189123074645, + "top": 666.080035105452 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "245a5b51-c40d-4425-81ca-2baf3c157022", + "when": null, + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "07c8cb5a-ff7f-4e51-8f81-74b2f7630f2e" + } + ] + }, + "6": { + "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis", + "content_id": null, + "errors": null, + "id": 6, + "input_connections": {}, "inputs": [ { "description": "Taxonomic lineage for the organism being assembled for Busco analysis", @@ -40258,8 +56534,8 @@ "name": "Input parameter", "outputs": [], "position": { - 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"workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "34ed45e3-2132-4c67-af2a-b72a8cbcf55c" + } + ] }, - "7": { + "8": { "annotation": "", "content_id": null, "errors": null, - "id": 7, + "id": 8, "input_connections": {}, "inputs": [ { @@ -40312,8 +56600,8 @@ "name": "Input parameter", "outputs": [], "position": { - "left": 78.38870701261258, - "top": 769.8272396352553 + "left": 130.80851045942487, + "top": 939.8716854194543 }, "tool_id": null, "tool_state": "{\"default\": \"Hap2\", \"parameter_type\": \"text\", \"optional\": true}", @@ -40321,13 +56609,19 @@ "type": "parameter_input", "uuid": "6d5afa06-c3e8-4eb7-8819-8cfe8300c462", "when": null, - "workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "8c9ba587-c3e2-4200-8794-2b18ba08fc9e" + } + ] }, - "8": { + "9": { "annotation": "Defaults to 37 if not specified. 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\"__current_case__\": 0}}], \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "9.3+galaxy1", + "type": "tool", + "uuid": "7528118f-3c8c-47a8-86e8-6085145c38d1", + "when": null, + "workflow_outputs": [ + { + "label": "clean_stats", + "output_name": "outfile", + "uuid": "0d69a8ab-29c1-4fef-97d9-af243ca8eb83" } ] } @@ -43532,11 +60202,11 @@ "VGP", "Reviewed" ], - "uuid": "cf273c22-e0eb-4a5f-8248-4a5d5102db1c", + "uuid": "cb0e2983-13df-451c-85a2-ee78c94a2bd2", "version": 1 }, "readme": "# Contiging Solo w/HiC:\n\nGenerate phased assembly based on PacBio Hifi Reads using HiC data from the same individual for phasing.\n\n## Inputs\n\n1. Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n## Outputs\n\n1. Haplotype 1 assembly ([fasta] and [gfa])\n2. Haplotype 2 assembly ([fasta] and [gfa])\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblies", - "changelog": "# Changelog\n\n\n\n## [0.1.10] 2024-04-23\n\n### Changed\n\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.9] 2024-04-19\n\n### Manual Updates\n\n- Add the option to provide Homozygous Read coverage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n\n## [0.1.8] 2024-03-25\n\n### Manual update\n\n- Remove tag filtering\n- Add merqury histogram output\n- Add output for cutadapt\n- Output Gff files in Busco \n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n## [0.1.7] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.5] 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.5.0+galaxy0`\n\n## [0.1.4] 2023-11-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.3] - 2023-11-08\n\n- Added tags `hifiasm_Assembly_Haplotype_1` and `hifiasm_Assembly_Haplotype_2` to fasta outputs of hifiasm, so they can be easily identified for feeding to purge_dups workflow\n- Made BUSCO lineages selectable from workflow launch interface\n\n## [0.1.2] - 2023-11-07\n\n- Added input filtering based on tags. Rearranged input ordering.\n\n## [0.1] - 2023-09-27\n\n- Creation of workflow for HiFi assembly with Hi-C phasing.\n" + "changelog": "# Changelog\n\n## [0.2.2] 2024-08-07\n\n- Expose parameter: Busco lineage database\n\n## [0.2.1] 2024-07-29\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.9+galaxy0`\n\n## [0.2] 2024-07-12\n\n### Added \n\n- Workflow report\n\n### Changed\n\n- Fix bug where the columns of the assembly statistics didn't join properly. \n \n\n## [0.1.11] 2024-05-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n\n\n\n## [0.1.10] 2024-04-23\n\n### Changed\n\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.9] 2024-04-19\n\n### Manual Updates\n\n- Add the option to provide Homozygous Read coverage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n\n## [0.1.8] 2024-03-25\n\n### Manual update\n\n- Remove tag filtering\n- Add merqury histogram output\n- Add output for cutadapt\n- Output Gff files in Busco \n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n## [0.1.7] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.5] 2023-11-15\n\n### Added\n\n- more descriptive labels for inputs\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.5.0+galaxy0`\n\n## [0.1.4] 2023-11-08\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.3] - 2023-11-08\n\n- Added tags `hifiasm_Assembly_Haplotype_1` and `hifiasm_Assembly_Haplotype_2` to fasta outputs of hifiasm, so they can be easily identified for feeding to purge_dups workflow\n- Made BUSCO lineages selectable from workflow launch interface\n\n## [0.1.2] - 2023-11-07\n\n- Added input filtering based on tags. Rearranged input ordering.\n\n## [0.1] - 2023-09-27\n\n- Creation of workflow for HiFi assembly with Hi-C phasing.\n" } ], "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-HiC-phasing-VGP4" @@ -43577,7 +60247,7 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.1.3", + "release": "0.1.4", "name": "kmer-profiling-hifi-trio-VGP2", "steps": { "0": { @@ -44005,7 +60675,7 @@ }, "9": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "errors": null, "id": 9, "input_connections": { @@ -44110,15 +60780,15 @@ "output_name": "transformed_log_plot" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "tool_shed_repository": { - "changeset_revision": "01210c4e9144", + "changeset_revision": "460fad600dce", "name": "genomescope", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"advanced_options\": {\"topology\": null, \"initial_repetitiveness\": null, \"initial_heterozygosities\": \"\", \"transform_exp\": null, \"testing\": true, \"true_params\": \"\", \"trace_flag\": false, \"num_rounds\": null}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"kmer_length\": {\"__class__\": \"ConnectedValue\"}, \"lambda\": null, \"max_kmercov\": null, \"output_options\": {\"output_files\": [\"model_output\", \"summary_output\"], \"no_unique_sequence\": false}, \"ploidy\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.0+galaxy2", + "tool_version": "2.0.1+galaxy0", "type": "tool", "uuid": "12e75ec0-5722-4ad7-b333-636c3c9ad9c8", "when": null, @@ -44292,7 +60962,7 @@ }, "13": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "errors": null, "id": 13, "input_connections": { @@ -44396,15 +61066,15 @@ "output_name": "transformed_log_plot" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "tool_shed_repository": { - "changeset_revision": "01210c4e9144", + "changeset_revision": "460fad600dce", "name": "genomescope", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"advanced_options\": {\"topology\": null, \"initial_repetitiveness\": null, \"initial_heterozygosities\": \"\", \"transform_exp\": null, \"testing\": false, \"true_params\": \"\", \"trace_flag\": false, \"num_rounds\": null}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"kmer_length\": {\"__class__\": \"ConnectedValue\"}, \"lambda\": null, \"max_kmercov\": null, \"output_options\": {\"output_files\": [\"model_output\", \"summary_output\"], \"no_unique_sequence\": false}, \"ploidy\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.0+galaxy2", + "tool_version": "2.0.1+galaxy0", "type": "tool", "uuid": "c65bd0f5-d8d5-4d1d-81bf-6d05458bc160", "when": null, @@ -44433,7 +61103,7 @@ }, "14": { "annotation": "", - "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "errors": null, "id": 14, "input_connections": { @@ -44537,15 +61207,15 @@ "output_name": "transformed_log_plot" } }, - "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2", + "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0", "tool_shed_repository": { - "changeset_revision": "01210c4e9144", + "changeset_revision": "460fad600dce", "name": "genomescope", "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, "tool_state": "{\"advanced_options\": {\"topology\": null, \"initial_repetitiveness\": null, \"initial_heterozygosities\": \"\", \"transform_exp\": null, \"testing\": false, \"true_params\": \"\", \"trace_flag\": false, \"num_rounds\": null}, \"input\": {\"__class__\": \"ConnectedValue\"}, \"kmer_length\": {\"__class__\": \"ConnectedValue\"}, \"lambda\": null, \"max_kmercov\": null, \"output_options\": {\"output_files\": [\"model_output\", \"summary_output\"], \"no_unique_sequence\": false}, \"ploidy\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", - "tool_version": "2.0+galaxy2", + "tool_version": "2.0.1+galaxy0", "type": "tool", "uuid": "87497ba1-5c23-4852-9e2f-0bd78dc86753", "when": null, @@ -44581,7 +61251,7 @@ "version": 9 }, "readme": "# VGP Workflow #1\n\nThis workflow collects the metrics on the properties of the genome under consideration by analyzing the *k*-mer frequencies. It provides information about the genomic complexity, such as the genome size and levels of heterozygosity and repeat content, as well about the data quality. It uses reads from two parental genomes to partition long reads from the offspring into haplotype-specific *k*-mer databases.\n\n### Inputs\n\n- Collection of Hifi long reads [fastq] (Collection)\n- Paternal short-read Illumina sequencing reads [fastq] (Collection)\n- Maternal short-read Illumina sequencing reads [fastq] (Collection)\n- *k*-mer length\n- Ploidy\n\n### Outputs\n\n- Meryl databases of k-mer counts\n - Child\n - Paternal haplotype\n - Maternal haplotype\n- GenomeScope metrics for child and the two parental genomes (three GenomeScope profiles in total)\n - Linear plot\n - Log plot\n - Transformed linear plot\n - Transformed log plot\n - Summary\n - Model\n - Model parameteres\n \n ![image](https://github.com/galaxyproject/iwc/assets/4291636/35282f8e-d021-44f6-8e03-7b58b32d6d00)\n", - "changelog": "# Changelog\n\n## [0.1.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.2] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2`\n\n## [0.1] - 2023-10-30\n\n### Added\n- Clearer labels\n\n### Removed\n- Interlacing step that was unneccessary\n- Requirement for paired list inputs for the Illumina parental reads. A dataset collection list is sufficient now.\n- Unnecessary workflow intputs\n\n## [0.1] - 2021-08-26\n### Added\n- First version of the workflow. \n" + "changelog": "# Changelog\n\n## [0.1.4] 2024-08-05\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0.1+galaxy0`\n\n## [0.1.3] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1.2] 2023-11-09\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/genomescope/genomescope/2.0+galaxy2`\n\n## [0.1] - 2023-10-30\n\n### Added\n- Clearer labels\n\n### Removed\n- Interlacing step that was unneccessary\n- Requirement for paired list inputs for the Illumina parental reads. A dataset collection list is sufficient now.\n- Unnecessary workflow intputs\n\n## [0.1] - 2021-08-26\n### Added\n- First version of the workflow. \n" } ], "path": "./workflows/VGP-assembly-v2/kmer-profiling-hifi-trio-VGP2" @@ -44623,8 +61293,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.1.4", + "release": "0.2", "name": "Assembly-Hifi-Trio-phasing-VGP5", + "report": { + "markdown": "\n# Workflow Execution Report\n\nTime workflow was invoked:\n\n```galaxy\ninvocation_time()\n```\nGalaxy version :\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Raw unitig graph\n\n```galaxy\nhistory_dataset_as_image(output=\"raw unitig graph image\")\n```\n\n## Merqury results\n\n### Merqury QV\n\n```galaxy\nhistory_dataset_as_table(output=merqury_stats)\n```\n\n### Merqury completeness\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_stats\")\n```\n\n### Merqury plots\n\n\nspectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-cn.fl\")\n```\n\nspectra-asm:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-asm.fl\")\n```\n\n\nhap1 spectra-cn:\n\n\r\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_01.spectra-cn.fl\")\n```\r\n\n\nhap2 spectra-cn:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_02.spectra-cn.fl\")\n```\n\n## BUSCO results (Vertebrata database)\n\nHap1\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco Summary Image Hap1\")\n```\n\nHap2\n\n```galaxy\nhistory_dataset_as_image(output=\"Busco Summary Image Hap2\")\n```\n\n## Assembly statistics\n\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n\n## Nx and Size plots\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n\n\n## Current Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "", @@ -44804,8 +61477,8 @@ "name": "Input parameter", "outputs": [], "position": { - "left": 16.973703852699934, - "top": 875.4758102675167 + "left": 14.278967454027603, + "top": 893.0522085856591 }, "tool_id": null, "tool_state": "{\"default\": 37, \"parameter_type\": \"integer\", \"optional\": true}", @@ -44813,14 +61486,53 @@ "type": "parameter_input", "uuid": "a5987ed3-6fdb-49c7-92d0-5b2f78a9bbb9", "when": null, - "workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "1bb5df96-d731-4e12-b902-ec6e1d723b07" + } + ] }, "7": { - "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis", + "annotation": "", "content_id": null, "errors": null, "id": 7, "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Database for Busco Lineage" + } + ], + "label": "Database for Busco Lineage", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 28.142955132748718, + "top": 1078.9295496884674 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "ca553be3-e5c9-4770-bd61-d50ed05c69ae", + "when": null, + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "9829d67c-d793-44c9-9b53-9c3ebd2155a8" + } + ] + }, + "8": { + "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis", + "content_id": null, + "errors": null, + "id": 8, + "input_connections": {}, "inputs": [ { "description": "Taxonomic lineage for the organism being assembled for Busco analysis", @@ -44831,8 +61543,8 @@ "name": "Input parameter", "outputs": [], "position": { - "left": 36.34366195032787, - "top": 998.1239416236981 + "left": 61.152110333438976, + "top": 1189.4200518565176 }, "tool_id": null, "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", @@ -44840,13 +61552,19 @@ "type": "parameter_input", "uuid": "9762d451-eb6f-4f0c-8203-7094f46ea771", "when": null, - "workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "9dff2868-bf8a-4443-87c9-52f5b8975bdb" + } + ] }, - "8": { + "9": { "annotation": "If empty, read coverage will be estimated from the Genomescope parameters. ", "content_id": null, "errors": null, - "id": 8, + "id": 9, "input_connections": {}, "inputs": [ { @@ -44858,8 +61576,8 @@ "name": "Input parameter", "outputs": [], "position": { - "left": 65.73786407849795, - "top": 1111.7501052118992 + "left": 98.92882500063175, + "top": 1275.4014318043698 }, "tool_id": null, "tool_state": "{\"parameter_type\": \"integer\", \"optional\": true}", @@ -44867,13 +61585,19 @@ "type": "parameter_input", "uuid": "ffcf874f-594d-4d58-99dc-73ef566bcc88", "when": null, - "workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "28a260f0-a63e-4743-ba41-6544e4f423a9" + } + ] }, - "9": { + "10": { "annotation": "GenomeScope model parameters generated by K-mer profiling workflow", "content_id": null, "errors": null, - "id": 9, + "id": 10, "input_connections": {}, "inputs": [ { @@ -44885,8 +61609,8 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 101.3532659049146, - "top": 1219.9729028733702 + "left": 146.82808789081685, + "top": 1368.9007539001223 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": null}", @@ -44896,11 +61620,11 @@ "when": null, "workflow_outputs": [] }, - "10": { + "11": { "annotation": "", "content_id": null, "errors": null, - "id": 10, + "id": 11, "input_connections": {}, "inputs": [ { @@ -44912,8 +61636,8 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 150.24297371017008, - "top": 1347.367362010912 + "left": 217.51082966945373, + "top": 1473.9095926545822 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": null}", @@ -44923,11 +61647,11 @@ "when": null, "workflow_outputs": [] }, - "11": { + "12": { "annotation": "--trio-dual option", "content_id": null, "errors": null, - "id": 11, + "id": 12, "input_connections": {}, "inputs": [ { @@ -44939,8 +61663,8 @@ "name": "Input parameter", "outputs": [], "position": { - "left": 227.5310800942477, - "top": 1472.080580726721 + "left": 306.5808483755939, + "top": 1565.8147646057243 }, "tool_id": null, "tool_state": "{\"default\": true, \"parameter_type\": \"boolean\", \"optional\": true}", @@ -44948,13 +61672,19 @@ "type": "parameter_input", "uuid": "eb8c0bcc-14c8-4b3d-b73f-442eae454b82", "when": null, - "workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "b178a102-00b1-45ae-8404-2c7c544cdeee" + } + ] }, - "12": { + "13": { "annotation": "", "content_id": null, "errors": null, - "id": 12, + "id": 13, "input_connections": {}, "inputs": [ { @@ -44975,13 +61705,19 @@ "type": "data_input", "uuid": "80ff22ac-1a58-4f89-bf52-48f18d8f71f9", "when": null, - "workflow_outputs": [] + "workflow_outputs": [ + { + "label": null, + "output_name": "output", + "uuid": "c2cf45d3-af1d-49d6-9d77-41065f57fcdb" + } + ] }, - "13": { + "14": { "annotation": "", "content_id": null, "errors": null, - "id": 13, + "id": 14, "input_connections": {}, "inputs": [ { @@ -45002,13 +61738,19 @@ "type": "parameter_input", 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"toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0", + "tool_id": "toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy1", "tool_shed_repository": { - "changeset_revision": "b1c926deaa2d", + "changeset_revision": "5eb7e84243f2", "name": "cutadapt", "owner": "lparsons", "tool_shed": "toolshed.g2.bx.psu.edu" }, - "tool_state": "{\"adapter_options\": {\"action\": \"trim\", \"error_rate\": \"0.1\", \"no_indels\": false, \"times\": \"1\", \"overlap\": \"35\", \"match_read_wildcards\": false, \"no_match_adapter_wildcards\": true, \"revcomp\": true}, \"filter_options\": {\"discard_trimmed\": true, \"discard_untrimmed\": false, \"minimum_length\": null, \"maximum_length\": null, \"max_n\": null, \"pair_filter\": \"any\", \"max_expected_errors\": null, \"max_average_error_rate\": null, \"discard_cassava\": false}, \"library\": {\"type\": \"single\", \"__current_case__\": 0, \"input_1\": {\"__class__\": \"RuntimeValue\"}, \"r1\": {\"adapters\": [], 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"toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", + "errors": null, + "id": 53, + "input_connections": { + "infile": { + "id": 52, + "output_name": "output" + } + }, + "inputs": [], + "label": null, + "name": "Replace", + "outputs": [ + { + "name": "outfile", + "type": "input" + } + ], + "position": { + "left": 5346.826883826449, + "top": 86.40715310618705 + }, + "post_job_actions": { + "HideDatasetActionoutfile": { + "action_arguments": {}, + "action_type": "HideDatasetAction", + "output_name": "outfile" + } + }, + "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/9.3+galaxy1", + "tool_shed_repository": { + "changeset_revision": "fbf99087e067", + "name": "text_processing", + "owner": "bgruening", + "tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"find_and_replace\": [{\"__index__\": 0, \"find_pattern\": \"#\", \"replace_pattern\": \"Number of\", \"is_regex\": false, \"global\": true, \"caseinsensitive\": false, \"wholewords\": false, \"skip_first_line\": false, \"searchwhere\": {\"searchwhere_select\": \"line\", \"__current_case__\": 0}}], \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "9.3+galaxy1", + "type": "tool", + "uuid": "68545a0f-7aa4-43e3-bf1a-5dcb75108c51", + "when": null, + "workflow_outputs": [ + { + "label": "clean_stats", + "output_name": "outfile", + "uuid": "fe375d8e-3e97-4373-b3ac-0d2e409d0145" } ] } @@ -48033,11 +65177,11 @@ "VGP", "Reviewed" ], - "uuid": "d8fd9266-a2f8-4a6e-9c12-8d312bdd2ca7", - "version": 6 + "uuid": "3cacf798-0f32-43b9-82c0-2d8f76312c80", + "version": 8 }, "readme": "# Assembly with Hifi reads and Trio Data\n\nGenerate phased assembly based on PacBio Hifi Reads using parental Illumina data for phasing\n\n## Inputs\n\n1. Hifi long reads [fastq]\n2. Concatenated Illumina reads : Paternal [fastq]\n3. Concatenated Illumina reads : Maternal [fastq]\n4. K-mer database [meryldb]\n5. Paternal hapmer database [meryldb]\n6. Maternal hapmer database [meryldb]\n7. Genome profile summary generated by Genomescope [txt]\n8. Genome model parameters generated by Genomescope [tabular]\n9. Homozygous read coverage (Estimated from the Genomescope model if not provided)\n10. Lineage of the species being assembled\n11. Bloom Filter\n12. Name of first haplotype\n13. Name of second haplotype\n\n## Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. Merqury report for both assemblies\n5. Assembly statistics for both assemblies\n6. Nx Plot for both assemblies\n7. Size plot for both assemblies\n\n\n", - "changelog": "# Changelog\n\n## [0.1.4] 2024-04-22\n\n### Added\n\n- Add Homozygous Read coverage parameter and calculation\n- Expose Lineage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.3] 2024-03-25\n\n### Manual update\n\n- Add gff output to Busco\n- Add histogram output to Merqury\n- Label subworkflows\n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.1] 2023-11-20\n\n- Fix author in dockstore\n\n\n## [0.1] - 2023-09-27\n\nCreation of workflow for Trio assembly. \n\n" + "changelog": "# Changelog\n\n## [0.2] 2024-08-12\n\n### Added\n\n- Workflow report\n\n### Changed \n\n- Expose the Busco lineage database parameter\n- Fix a bug happening when merging assembly statistics : The presence of the '#' character caused the tables to join incorrectly, and the numbers did not match the metrics\n\n## [0.1.8] 2024-07-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy1`\n\n## [0.1.7] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.9+galaxy0`\n\n## [0.1.6] 2024-05-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n\n## [0.1.5] 2024-05-06\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n\n## [0.1.4] 2024-04-22\n\n### Added\n\n- Add Homozygous Read coverage parameter and calculation\n- Expose Lineage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.3] 2024-03-25\n\n### Manual update\n\n- Add gff output to Busco\n- Add histogram output to Merqury\n- Label subworkflows\n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n## [0.1.1] 2023-11-20\n\n- Fix author in dockstore\n\n\n## [0.1] - 2023-09-27\n\nCreation of workflow for Trio assembly. \n\n" } ], "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-Trio-phasing-VGP5" @@ -48079,8 +65223,11 @@ ], "format-version": "0.1", "license": "CC-BY-4.0", - "release": "0.1.5", + "release": "0.2.1", "name": "Assembly-Hifi-only-VGP3", + "report": { + "markdown": "\n# Workflow Execution Report\n\nTime workflow was invoked:\n\n```galaxy\ninvocation_time()\n```\nGalaxy version :\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Raw unitig graph\n\n```galaxy\nhistory_dataset_as_image(output=\"raw unitig graph image\")\n```\n\n## Merqury results\n\n### Merqury QV\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_qv\")\n```\n\n### Merqury completeness\n\n```galaxy\nhistory_dataset_as_table(output=\"merqury_stats\")\n```\n\n### Merqury plots\n\n\nspectra-cn:\n\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-cn.fl\")\n```\n\nspectra-asm:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.spectra-asm.fl\")\n```\n\nhap1 spectra-cn:\n\n```galaxy\nhistory_dataset_as_image(output=\"output_merqury.assembly_01.spectra-cn.fl\")\n```\n\n\n## BUSCO results (Vertebrata database)\n\n\n\n## Assembly statistics\n\n\n```galaxy\nhistory_dataset_as_table(output=\"clean_stats\")\n```\n\n\n## Nx and Size plots\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Nx Plot\")\n```\n\n\n```galaxy\nhistory_dataset_as_image(output=\"Size Plot\")\n```\n\n\n\n## Current Workflow\n```galaxy\nworkflow_display()\n```\n" + }, "steps": { "0": { "annotation": "", @@ -48245,11 +65392,38 @@ "workflow_outputs": [] }, "6": { - "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis", + "annotation": "", "content_id": null, "errors": null, "id": 6, "input_connections": {}, + "inputs": [ + { + "description": "", + "name": "Database for Busco Lineage" + } + ], + "label": "Database for Busco Lineage", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 422.96681360823476, + "top": 1352.5435082963184 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "af7ad6ad-2718-4a16-ad1f-6858b1b4fb50", + "when": null, + "workflow_outputs": [] + }, + "7": { + "annotation": "Taxonomic lineage for the organism being assembled for Busco analysis", + "content_id": null, + "errors": null, + "id": 7, 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"tool_shed": "toolshed.g2.bx.psu.edu" + }, + "tool_state": "{\"find_and_replace\": [{\"__index__\": 0, \"find_pattern\": \"#\", \"replace_pattern\": \"Number of\", \"is_regex\": false, \"global\": true, \"caseinsensitive\": false, \"wholewords\": false, \"skip_first_line\": false, \"searchwhere\": {\"searchwhere_select\": \"line\", \"__current_case__\": 0}}], \"infile\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_version": "9.3+galaxy1", + "type": "tool", + "uuid": "ec90b8f9-bcc2-4b8a-88ee-03b3e19979ba", + "when": null, + "workflow_outputs": [ + { + "label": "clean_stats", + "output_name": "outfile", + "uuid": "365867c1-fec9-4c10-8b31-3f615992910a" } ] } @@ -51199,11 +68746,11 @@ "VGP", "Reviewed" ], - "uuid": "f6f4cac5-6900-440b-8f1d-52420f635420", + "uuid": "2988562a-fa7a-4135-bf67-943ab03d1517", "version": 1 }, - "readme": "## Contiging Solo w/HiC:\n\nGenerate phased assembly based on PacBio Hifi Reads using HiC data from the same individual for phasing.\n\n\n### Inputs\n\n\n1. Hifi long reads [fastq]\n2. HiC forward reads (if multiple input files, concatenated in same order as reverse reads) [fastq]\n3. HiC reverse reads (if multiple input files, concatenated in same order as forward reads) [fastq]\n4. K-mer database [meryldb]\n5. Genome profile summary generated by Genomescope [txt]\n6. Name of first assembly\n7. Name of second assembly\n\n\n### Outputs\n\n1. Haplotype 1 assembly\n2. Haplotype 2 assembly\n3. QC: BUSCO report for both assemblies\n4. QC: Merqury report for both assemblies\n5. QC: Assembly statistics for both assemblies\n6. QC: Nx plot for both assemblies\n7. QC: Size plot for both assemblie\n", - "changelog": "# Changelog\n\n\n## [0.1.5] 2024-04-23\n\n### Changed\n\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.4] 2024-04-19\n\n### Manual Updates\n\n- Add Homozygous Read coverage parameter and calculation\n- Expose Lineage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n## [0.1.3] 2024-03-25\n\n### Manual Updates\n- Add Gff outputs to Busco\n- Add histogram outputs to Merqury\n- Add labels to subworkflows\n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n\n## [0.1.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1] - 2023-09-26\n\nAddition of the workflow to the iwc repository.\n" + "readme": "## Contiging Solo:\n\nGenerate assembly based on PacBio Hifi Reads.\n\n\n### Inputs\n\n\n1. Hifi long reads [fastq]\n2. K-mer database [meryldb]\n3. Genome profile summary generated by Genomescope [txt]\n4. Homozygous Read Coverage. Optional, use if you think the estimation from Genomescope is inacurate. \n5. Genomescope Model Parameters generated by Genomescope [tabular]\n6. Database for busco lineage (recommended: latest)\n7. Busco lineage (recommended: vertebrata)\n8. Name of first assembly\n9. Name of second assembly\n\n\n### Outputs\n\n1. Primary assembly\n2. Alternate assembly\n3. QC: Bandage image for the raw unitigs\n4. QC: BUSCO report for both assemblies\n5. QC: Merqury report for both assemblies\n6. QC: Assembly statistics for both assemblies\n7. QC: Nx plot for both assemblies\n8. QC: Size plot for both assemblie\n", + "changelog": "# Changelog\n\n## [0.2.1] 2024-08-13\n\n- Expose Busco lineage database parameter\n\n## [0.2] 2024-08-01\n\n### Added\n\n- Add bandage image\n- Add workflow report\n\n### Changed\n\n- Fix bug in merging assembly statistics\n\n## [0.1.8] 2024-07-22\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy1`\n\n## [0.1.7] 2024-07-15\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.9+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.9+galaxy0`\n\n## [0.1.6] 2024-05-20\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.1.0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/pick_value/pick_value/0.2.0`\n\n\n## [0.1.5] 2024-04-23\n\n### Changed\n\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.8+galaxy0`\n\n\n## [0.1.4] 2024-04-19\n\n### Manual Updates\n\n- Add Homozygous Read coverage parameter and calculation\n- Expose Lineage parameter\n\n### Automatic update\n\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_easyjoin_tool/9.3+galaxy1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy4`\n\n## [0.1.3] 2024-03-25\n\n### Manual Updates\n- Add Gff outputs to Busco\n- Add histogram outputs to Merqury\n- Add labels to subworkflows\n\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_grep_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_replace_in_line/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/1.1.2` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_awk_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/1.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_sed_tool/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/0.1.1` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.7+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy1`\n\n\n## [0.1.2] 2023-11-14\n\n### Automatic update\n- `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.0+galaxy1` was updated to `toolshed.g2.bx.psu.edu/repos/lparsons/cutadapt/cutadapt/4.4+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.16.1+galaxy4` was updated to `toolshed.g2.bx.psu.edu/repos/bgruening/hifiasm/hifiasm/0.19.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.3.2+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/busco/busco/5.4.6+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/merqury/merqury/1.3+galaxy3`\n- `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.1.0+galaxy2` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/datamash_ops/datamash_ops/1.8+galaxy0`\n- `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.0` was updated to `toolshed.g2.bx.psu.edu/repos/devteam/add_value/addValue/1.0.1`\n- `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy0` was updated to `toolshed.g2.bx.psu.edu/repos/iuc/ggplot2_point/ggplot2_point/3.4.0+galaxy1`\n\n\n## [0.1.1] 2023-11-20\n\n- Fix author in dockstore\n\n## [0.1] - 2023-09-26\n\nAddition of the workflow to the iwc repository.\n" } ], "path": "./workflows/VGP-assembly-v2/Assembly-Hifi-only-VGP3" From 1ca1e43a65cf351d9c19e0e0821ba5e0138fd8a9 Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:40 -0400 Subject: [PATCH 18/74] Drop astro --- showcase_astro/.gitignore | 24 - showcase_astro/README.md | 54 - showcase_astro/astro.config.mjs | 9 - showcase_astro/package-lock.json | 13683 ---------------- showcase_astro/package.json | 21 - showcase_astro/public/favicon.svg | 9 - showcase_astro/src/components/Card.astro | 61 - .../src/components/WorkflowDetail.vue | 22 - .../src/components/WorkflowList.vue | 56 - .../src/data/workflow_manifest.json | 1 - showcase_astro/src/env.d.ts | 1 - showcase_astro/src/layouts/Layout.astro | 53 - showcase_astro/src/pages/index.astro | 70 - .../src/pages/workflow/[...slug].astro | 31 - showcase_astro/src/styles/tailwind.css | 105 - showcase_astro/tailwind.config.mjs | 56 - showcase_astro/tsconfig.json | 6 - showcase_astro/yarn.lock | 4179 ----- 18 files changed, 18441 deletions(-) delete mode 100644 showcase_astro/.gitignore delete mode 100644 showcase_astro/README.md delete mode 100644 showcase_astro/astro.config.mjs delete mode 100644 showcase_astro/package-lock.json delete mode 100644 showcase_astro/package.json delete mode 100644 showcase_astro/public/favicon.svg delete mode 100644 showcase_astro/src/components/Card.astro delete mode 100644 showcase_astro/src/components/WorkflowDetail.vue delete mode 100644 showcase_astro/src/components/WorkflowList.vue delete mode 120000 showcase_astro/src/data/workflow_manifest.json delete mode 100644 showcase_astro/src/env.d.ts delete mode 100644 showcase_astro/src/layouts/Layout.astro delete mode 100644 showcase_astro/src/pages/index.astro delete mode 100644 showcase_astro/src/pages/workflow/[...slug].astro delete mode 100644 showcase_astro/src/styles/tailwind.css delete mode 100644 showcase_astro/tailwind.config.mjs delete mode 100644 showcase_astro/tsconfig.json delete mode 100644 showcase_astro/yarn.lock diff --git a/showcase_astro/.gitignore b/showcase_astro/.gitignore deleted file mode 100644 index 016b59ea1..000000000 --- a/showcase_astro/.gitignore +++ /dev/null @@ -1,24 +0,0 @@ -# build output -dist/ - -# generated types -.astro/ - -# dependencies -node_modules/ - -# logs -npm-debug.log* -yarn-debug.log* -yarn-error.log* -pnpm-debug.log* - -# environment variables -.env -.env.production - -# macOS-specific files -.DS_Store - -# jetbrains setting folder -.idea/ diff --git a/showcase_astro/README.md b/showcase_astro/README.md deleted file mode 100644 index 1db3fb399..000000000 --- a/showcase_astro/README.md +++ /dev/null @@ -1,54 +0,0 @@ -# Astro Starter Kit: Basics - -```sh -npm create astro@latest -- --template basics -``` - -[![Open in StackBlitz](https://developer.stackblitz.com/img/open_in_stackblitz.svg)](https://stackblitz.com/github/withastro/astro/tree/latest/examples/basics) -[![Open with CodeSandbox](https://assets.codesandbox.io/github/button-edit-lime.svg)](https://codesandbox.io/p/sandbox/github/withastro/astro/tree/latest/examples/basics) -[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/withastro/astro?devcontainer_path=.devcontainer/basics/devcontainer.json) - -> 🧑‍🚀 **Seasoned astronaut?** Delete this file. Have fun! - -![just-the-basics](https://github.com/withastro/astro/assets/2244813/a0a5533c-a856-4198-8470-2d67b1d7c554) - -## 🚀 Project Structure - -Inside of your Astro project, you'll see the following folders and files: - -```text -/ -├── public/ -│ └── favicon.svg -├── src/ -│ ├── components/ -│ │ └── Card.astro -│ ├── layouts/ -│ │ └── Layout.astro -│ └── pages/ -│ └── index.astro -└── package.json -``` - -Astro looks for `.astro` or `.md` files in the `src/pages/` directory. Each page is exposed as a route based on its file name. - -There's nothing special about `src/components/`, but that's where we like to put any Astro/React/Vue/Svelte/Preact components. - -Any static assets, like images, can be placed in the `public/` directory. - -## 🧞 Commands - -All commands are run from the root of the project, from a terminal: - -| Command | Action | -| :------------------------ | :----------------------------------------------- | -| `npm install` | Installs dependencies | -| `npm run dev` | Starts local dev server at `localhost:4321` | -| `npm run build` | Build your production site to `./dist/` | -| `npm run preview` | Preview your build locally, before deploying | -| `npm run astro ...` | Run CLI commands like `astro add`, `astro check` | -| `npm run astro -- --help` | Get help using the Astro CLI | - -## 👀 Want to learn more? - -Feel free to check [our documentation](https://docs.astro.build) or jump into our [Discord server](https://astro.build/chat). diff --git a/showcase_astro/astro.config.mjs b/showcase_astro/astro.config.mjs deleted file mode 100644 index 03021b498..000000000 --- a/showcase_astro/astro.config.mjs +++ /dev/null @@ -1,9 +0,0 @@ -import { defineConfig } from 'astro/config'; -import vue from "@astrojs/vue"; - -import tailwind from "@astrojs/tailwind"; - -// https://astro.build/config -export default defineConfig({ - integrations: [vue(), tailwind()] -}); \ No newline at end of file diff --git a/showcase_astro/package-lock.json b/showcase_astro/package-lock.json deleted file mode 100644 index 7468a329a..000000000 --- a/showcase_astro/package-lock.json +++ /dev/null @@ -1,13683 +0,0 @@ -{ - "name": "showcase", - "version": "0.0.1", - "lockfileVersion": 2, - "requires": true, - "packages": { - "": { - "name": "showcase", - "version": "0.0.1", - "dependencies": { - "@astrojs/check": "^0.7.0", - "@astrojs/tailwind": "^5.1.0", - "@astrojs/vue": "^4.2.0", - "astro": "^4.8.6", - "tailwindcss": "^3.4.3", - "typescript": "^5.4.5", - "vue": "^3.4.27" - } - }, - "node_modules/@alloc/quick-lru": { - "version": "5.2.0", - "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz", - "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==", - 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"start": "astro dev", - "build": "astro check && astro build", - "preview": "astro preview", - "astro": "astro" - }, - "dependencies": { - "@astrojs/check": "^0.7.0", - "@astrojs/tailwind": "^5.1.0", - "@astrojs/vue": "^4.2.0", - "astro": "^4.8.6", - "tailwindcss": "^3.4.3", - "typescript": "^5.4.5", - "vue": "^3.4.27" - } -} diff --git a/showcase_astro/public/favicon.svg b/showcase_astro/public/favicon.svg deleted file mode 100644 index f157bd1c5..000000000 --- a/showcase_astro/public/favicon.svg +++ /dev/null @@ -1,9 +0,0 @@ - - - - diff --git a/showcase_astro/src/components/Card.astro b/showcase_astro/src/components/Card.astro deleted file mode 100644 index bd6d5971e..000000000 --- a/showcase_astro/src/components/Card.astro +++ /dev/null @@ -1,61 +0,0 @@ ---- -interface Props { - title: string; - body: string; - href: string; -} - -const { href, title, body } = Astro.props; ---- - -
  • - -

    - {title} - → -

    -

    - {body} -

    -     -
    • - diff --git a/showcase_astro/src/components/WorkflowDetail.vue b/showcase_astro/src/components/WorkflowDetail.vue deleted file mode 100644 index 9e8a80ff0..000000000 --- a/showcase_astro/src/components/WorkflowDetail.vue +++ /dev/null @@ -1,22 +0,0 @@ - - - - \ No newline at end of file diff --git a/showcase_astro/src/components/WorkflowList.vue b/showcase_astro/src/components/WorkflowList.vue deleted file mode 100644 index a7e081cea..000000000 --- a/showcase_astro/src/components/WorkflowList.vue +++ /dev/null @@ -1,56 +0,0 @@ - - - - - \ No newline at end of file diff --git a/showcase_astro/src/data/workflow_manifest.json b/showcase_astro/src/data/workflow_manifest.json deleted file mode 120000 index 2fa18ab1a..000000000 --- a/showcase_astro/src/data/workflow_manifest.json +++ /dev/null @@ -1 +0,0 @@ -../../../workflow_manifest.json \ No newline at end of file diff --git a/showcase_astro/src/env.d.ts b/showcase_astro/src/env.d.ts deleted file mode 100644 index 8c34fb45e..000000000 --- a/showcase_astro/src/env.d.ts +++ /dev/null @@ -1 +0,0 @@ -/// \ No newline at end of file diff --git a/showcase_astro/src/layouts/Layout.astro b/showcase_astro/src/layouts/Layout.astro deleted file mode 100644 index 38f3da107..000000000 --- a/showcase_astro/src/layouts/Layout.astro +++ /dev/null @@ -1,53 +0,0 @@ ---- -import "../styles/tailwind.css"; - -interface Props { - title: string; -} - -const { title } = Astro.props; ---- - - - - - - - - - - {title} - - - - - - diff --git a/showcase_astro/src/pages/index.astro b/showcase_astro/src/pages/index.astro deleted file mode 100644 index 4481d541a..000000000 --- a/showcase_astro/src/pages/index.astro +++ /dev/null @@ -1,70 +0,0 @@ ---- -import Layout from '../layouts/Layout.astro'; -import manifest from '../data/workflow_manifest.json'; -import WorkflowList from "../components/WorkflowList.vue"; - ---- - - -
    -

    Intergalactic Workflow Commission Gallery

    - -
    -     - - diff --git a/showcase_astro/src/pages/workflow/[...slug].astro b/showcase_astro/src/pages/workflow/[...slug].astro deleted file mode 100644 index 0cfed24d7..000000000 --- a/showcase_astro/src/pages/workflow/[...slug].astro +++ /dev/null @@ -1,31 +0,0 @@ ---- -import { Astro, getStaticPaths, getStaticProps } from 'astro'; -import WorkflowDetail from '../../components/WorkflowDetail.vue'; -import manifest from '../../data/workflow_manifest.json'; - -// Define getStaticPaths to generate paths for each workflow -export const getStaticPaths = async () => { - const paths = manifest.map((workflow) => { - // Extract the slug from the workflow path - const slug = workflow.path.replace('./workflows/', ''); - return { params: { slug: slug.split('/') } }; - }); - - return { paths }; -}; - -// Define getStaticProps to fetch data for each page -export const getStaticProps = async ({ params }) => { - const slugPath = params.slug.join('/'); - const workflow = manifest.find((w) => w.path === `./workflows/${slugPath}`); - return { props: { workflow } }; -}; - -// Get the slug from params -const { props } = Astro; -const { workflow } = props; ---- - - - - \ No newline at end of file diff --git a/showcase_astro/src/styles/tailwind.css b/showcase_astro/src/styles/tailwind.css deleted file mode 100644 index 5c32a7c59..000000000 --- a/showcase_astro/src/styles/tailwind.css +++ /dev/null @@ -1,105 +0,0 @@ -/* @import "./prose.css"; */ -@tailwind base; -@tailwind components; -@tailwind utilities; - - -@layer components { - .button { - @apply font-sans inline-flex h-14 items-center justify-center gap-4 rounded-full border border-astro-gray-100 px-10 text-center text-base font-medium leading-none tracking-wide text-white no-underline transition hover:bg-white/10; - } - - .button.button-primary { - @apply border-none bg-blue-purple-gradient text-white hover:bg-blue-purple-gradient hover:brightness-75; - } - - .button.button-white { - @apply border-none bg-astro-gray-100 text-astro-blue hover:brightness-75; - } - - .button.button-sm { - @apply h-10 gap-2 px-6 text-sm tracking-wide; - } - .button.button-xs { - @apply h-6 gap-2 px-3 text-xs tracking-wide; - } -} - -@layer utilities { - /* Hide scrollbar for Chrome, Safari and Opera */ - .no-scrollbar::-webkit-scrollbar { - display: none; - } - /* Hide scrollbar for IE, Edge and Firefox */ - .no-scrollbar { - -ms-overflow-style: none; /* IE and Edge */ - scrollbar-width: none; /* Firefox */ - } -} - -@layer typography { - :root { - --sans-weight-normal: 200; - --sans-weight-bold: 600; - --sans-wght: "wght" var(--sans-weight); - --sans-case: "case" on; - --sans-ss03: "ss03" on; - --sans-cpsp: "cpsp" on; - --sans-cv03: "cv03" on; - --sans-cv04: "cv04" on; - --sans-cv05: "cv05" on; - --sans-cv06: "cv06" on; - - --mono-style-italic: "ital" 1; - --mono-style-normal: "ital" 0; - --mono-calt: "calt" on; - --mono-zero: "zero" on; - --mono-style: var(--mono-style-normal); - --mono-ital: var(--mono-style); - - --heading-style-normal: "slnt" 0; - --heading-style-italic: "slnt" 8; - --heading-weight-light: 290; - --heading-weight-normal: 380; - --heading-weight-bold: 475; - --heading-weight: var(--heading-weight-light); - --heading-style: var(--heading-style-normal); - --heading-wght: "wght" var(--heading-weight); - --heading-salt: "salt" on; - --heading-ss06: "ss06" on; - --heading-ss11: "ss11" on; - --heading-cv09: "cv09" on; - --heading-liga: "liga" on; - --heading-calt: "calt" on; - } - - .font-italic { - --mono-style: var(--mono-style-italic); - --heading-style: var(--mono-style-normal); - } - - .font-strong { - --sans-weight: var(--sans-weight-bold); - --heading-weight: var(--heading-weight-bold); - } - - .font-sans { - font-family: Inter, inter-fallback, system-ui, sans-serif; - font-variation-settings: var(--sans-wght); - font-feature-settings: var(--sans-case), var(--sans-ss03), var(--sans-cpsp), var(--sans-cv03), - var(--cv04), var(--cv05), var(--cv06); - } - - .font-mono { - font-family: MDIO, md-io-fallback, monospace; - font-variation-settings: var(--mono-ital); - font-feature-settings: var(--mono-calt), var(--mono-zero); - } - - .font-heading { - font-family: Obviously, obviously-fallback, system-ui, sans-serif; - font-variation-settings: var(--heading-wdth), var(--heading-wght), var(--heading-slnt); - font-feature-settings: var(--heading-salt), var(--heading-ss06), var(--heading-ss11), - var(--heading-cv09), var(--heading-liga), var(--heading-calt); - } -} \ No newline at end of file diff --git a/showcase_astro/tailwind.config.mjs b/showcase_astro/tailwind.config.mjs deleted file mode 100644 index c95fb5f5b..000000000 --- a/showcase_astro/tailwind.config.mjs +++ /dev/null @@ -1,56 +0,0 @@ -/** @type {import('tailwindcss').Config} */ -export default { - content: ['./src/**/*.{astro,html,js,jsx,md,mdx,svelte,ts,tsx,vue}'], - theme: { - theme: { - fontFamily: {}, - extend: { - colors: { - black: "#0D0F14", - // TODO: replace with brand off-white color - white: "#ffffff", - "astro-gray": { - 100: "#F2F6FA", - 200: "#BFC1C9", - 300: "#858B98", - 400: "#545864", - 500: "#343841", - 600: "#23262D", - 700: "#17191E", - }, - "astro-blue": "#3245FF", - "astro-purple": "#BC52EE", - "astro-purple-dark": "#3F224D", - "astro-red": "#D83333", - "astro-pink": { - light: "#E8C4F9", - DEFAULT: "#F041FF", - }, - "astro-orange": "#F8E42E", - "astro-yellow": "#FF7D54", - "astro-hover": "#E8C4F9", - }, - backgroundImage: { - "blue-purple-gradient": "linear-gradient(83.21deg, #3245FF 0%, #B845ED 100%)", - "blue-green-gradient": "linear-gradient(247.23deg, #4AF2C8 0%, #2F4CB3 100%)", - "red-pink-gradient": "linear-gradient(66.77deg, #D83333 0%, #F041FF 100%)", - "orange-yellow-gradient": "linear-gradient(266.93deg, #F8E42E 0%, #FF7D54 100%)", - }, - height: { - header: "5rem", - }, - lineHeight: { - prose: "1.8125", - }, - maxWidth: { - prose: "768px", - }, - zIndex: { - blur: "-1", - grid: "-2", - }, - }, - }, - }, - plugins: [], -} diff --git a/showcase_astro/tsconfig.json b/showcase_astro/tsconfig.json deleted file mode 100644 index 30cf17bb8..000000000 --- a/showcase_astro/tsconfig.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "extends": "astro/tsconfigs/strict", - "compilerOptions": { - "jsx": "preserve" - } -} \ No newline at end of file diff --git a/showcase_astro/yarn.lock b/showcase_astro/yarn.lock deleted file mode 100644 index e2f5d4971..000000000 --- a/showcase_astro/yarn.lock +++ /dev/null @@ -1,4179 +0,0 @@ -# THIS IS AN AUTOGENERATED FILE. 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Click to scroll-to. --- website/components/WorkflowList.vue | 24 +++++++++++++----------- 1 file changed, 13 insertions(+), 11 deletions(-) diff --git a/website/components/WorkflowList.vue b/website/components/WorkflowList.vue index 4610022fa..6879b3247 100644 --- a/website/components/WorkflowList.vue +++ b/website/components/WorkflowList.vue @@ -5,7 +5,7 @@
    • {{ workflow.definition.name }}
      • @@ -13,8 +13,10 @@ -
      - +
      + @@ -37,7 +39,7 @@ const props = defineProps({ }); const searchQuery = ref(''); -const selectedWorkflows = ref([]); +const workflowContainer = ref(null); const allWorkflows = computed(() => props.workflowCollections.flatMap(collection => collection.workflows) @@ -49,16 +51,16 @@ const filteredWorkflows = computed(() => ) ); -function selectWorkflow(workflow: Workflow) { - const index = selectedWorkflows.value.findIndex(w => w.definition.uuid === workflow.definition.uuid); - if (index === -1) { - selectedWorkflows.value.push(workflow); - } else { - selectedWorkflows.value.splice(index, 1); +function scrollToWorkflow(workflow: Workflow) { + const element = document.getElementById(`workflow-${workflow.definition.uuid}`); + if (element && workflowContainer.value) { + workflowContainer.value.scrollTop = element.offsetTop - workflowContainer.value.offsetTop; } } \ No newline at end of file From b90d7d92b16c7b3cf13427efc1ab7c9c7fea080a Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:40 -0400 Subject: [PATCH 25/74] Fix individiual page access. --- website/app.config.ts | 4 ++-- website/components/WorkflowList.vue | 14 +++++++------- website/pages/workflow/[id].vue | 29 ++++++++++++++++++++--------- 3 files changed, 29 insertions(+), 18 deletions(-) diff --git a/website/app.config.ts b/website/app.config.ts index c328e8a2b..e5c4cb081 100644 --- a/website/app.config.ts +++ b/website/app.config.ts @@ -1,6 +1,6 @@ export default defineAppConfig({ ui: { - primary: 'green', - gray: 'cool', + primary: 'amber', + gray: 'neutral', } }) \ No newline at end of file diff --git a/website/components/WorkflowList.vue b/website/components/WorkflowList.vue index 6879b3247..3c8e88d66 100644 --- a/website/components/WorkflowList.vue +++ b/website/components/WorkflowList.vue @@ -1,7 +1,7 @@ \ No newline at end of file From c194a44e8cb2876734de33e0984a3100c7cb4bbc Mon Sep 17 00:00:00 2001 From: Dannon Baker Date: Tue, 10 Sep 2024 08:24:40 -0400 Subject: [PATCH 26/74] Adjust list display --- website/components/WorkflowList.vue | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/website/components/WorkflowList.vue b/website/components/WorkflowList.vue index 3c8e88d66..285f5223a 100644 --- a/website/components/WorkflowList.vue +++ b/website/components/WorkflowList.vue @@ -1,7 +1,7 @@