From d91a383dcf2a9f9044f84b92570878aaf2e8f85c Mon Sep 17 00:00:00 2001 From: pdiakumis Date: Wed, 26 Jun 2024 23:28:21 +1000 Subject: [PATCH 1/3] update/sync README + pkgdown site --- README.md | 129 ++++++++++------------- pcgrr/R/acmg.R | 2 +- pcgrr/R/utils.R | 2 +- pcgrr/pkgdown/index.md | 78 ++++++++++---- pcgrr/vignettes/CHANGELOG.Rmd | 44 ++++---- pcgrr/vignettes/annotation_resources.Rmd | 2 +- 6 files changed, 135 insertions(+), 122 deletions(-) diff --git a/README.md b/README.md index 4cd1d1ba..0322c47f 100755 --- a/README.md +++ b/README.md @@ -2,110 +2,89 @@ [![Conda install ver](https://anaconda.org/pcgr/pcgr/badges/version.svg)](https://anaconda.org/pcgr/pcgr) [![Conda install lrd](https://anaconda.org/pcgr/pcgr/badges/latest_release_date.svg)](https://anaconda.org/pcgr/pcgr) -[](https://hub.docker.com/repository/docker/sigven/pcgr/) +[](https://hub.docker.com/r/sigven/pcgr) ### Overview -The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for translation of individual tumor genomes for precision cancer medicine. +The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual tumor genomes for precision cancer medicine. It interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software classifies variants both with respect to _oncogenicity_, and _actionability_. Interactive HTML output reports allow the user to interrogate the clinical impact of the molecular findings in an individual tumor. -PCGR interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software produces interactive HTML reports intended for clinical interpretation. PCGR can perform multiple types of analyses, including: +- Variant classification + - according to *oncogenicity*: evaluating the oncogenic potential of somatic DNA aberrations (VICC/CGC/ClinGen guidelines) + - according to *actionability*: mapping the therapeutic, diagnostic, and prognostic implications of somatic DNA aberrations (ACMG/AMP guidelines) +- Tumor mutational burden (TMB) estimation +- Mutational signature analysis +- Microsatellite instability (MSI) classification +- RNA expression analysis - outlier detection, similarity analysis, and immune contexture profiling -- Variant classification - - according to *oncogenicity*: evaluating the oncogenic potential of somatic DNA aberrations (VICC/CGC/ClinGen guidelines) - - according to *actionability*: mapping the therapeutic, diagnostic, and prognostic implications of somatic DNA aberrations (ACMG/AMP guidelines) -- Tumor mutational burden (TMB) estimation -- Mutational signature analysis -- Microsatellite instability (MSI) classification -- RNA expression analysis - outlier detection, similarity analysis, and immune contexture profiling +PCGR supports both of the most recent human genome assemblies (GRCh37/GRCh38), and accepts variant calls from both tumor-control and tumor-only sequencing assays. Much of the functionality is intended for whole-exome/whole-genome sequencing assays, but you can also apply PCGR to output from targeted sequencing panels. If you are interested in the interrogation of germline variants and their relation to cancer predisposition, we recommend trying the accompanying tool [Cancer Predisposition Sequencing Reporter (CPSR)](https://github.com/sigven/cpsr). -PCGR supports both of the most recent human genome assemblies (grch37/grch38), and accepts variant calls from both tumor-control and tumor-only sequencing assays. Much of the functionality is intended for whole-exome/whole-genome sequencing assays, but you can also apply PCGR to output from targeted sequencing panels. If you are interested in the interrogation of germline variants and their relation to cancer predisposition, we recommend trying the accompanying tool [Cancer Predisposition Sequencing Reporter (CPSR)](https://github.com/sigven/cpsr). +Example screenshots from the [quarto](https://quarto.org)-based cancer genome report by PCGR: ![PCGR screenshot 1](pcgrr/pkgdown/assets/img/sc2.png) ![PCGR screenshot 2](pcgrr/pkgdown/assets/img/sc1.png) ![PCGR screenshot 3](pcgrr/pkgdown/assets/img/sc3.png) -### News +PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](http://cancergenomics.no), at the [Institute for Cancer Research, Oslo University Hospital, Norway](http://radium.no). -- *June 2024*: **2.0.0 release** - - Massive reference data bundle upgrade, new report layout, oncogenicity classification++ - - Details at [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) +### Top News -- *February 2023*: **1.3.0 release** - - Details at [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) - - proritize protein-coding BIOTYPE csq ([pr201](https://github.com/sigven/pcgr/pull/201)) - - expose `--pcgrr_conda` option to flexibly activate pcgrr env via a non-default pcgrr name - - `cpsr_validate_input.py`: refactor for efficient custom gene egrep +- *June 2024*: **2.0.0 release** + - Details in [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) + - Massive reference data bundle upgrade, new report layout, oncogenicity classification++ + - Support for Singularity/Apptainer + - Major data/software updates: + - Ensembl VEP `v112` + - ClinVar (2024-06) + - CIViC (2024-06-21) + - GENCODE `v46/v19` (GRCh38/GRCh37) + - CancerMine `v50` (2023-03) + - UniProt KB `v2024_03` -- *November 2022*: **1.2.0 release** - - Keep only autosomal, X, Y, M/MT chromosomes - - Import bcftools as dependency +- *February 2023*: **1.3.0 release** + - Details in [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) + - prioritize protein-coding BIOTYPE csq ([pr201](https://github.com/sigven/pcgr/pull/201)) + - expose `--pcgrr_conda` option to flexibly activate pcgrr env via a non-default pcgrr name + - `cpsr_validate_input.py`: refactor for efficient custom gene egrep +- *November 2022*: **1.2.0 release** + - Keep only autosomal, X, Y, M/MT chromosomes + - Import bcftools as dependency -- *October 2022*: **1.1.0 release** - - - Remove Docker command wrappers - - Deprecate `--no_docker` and `--docker_uid` CLI options - - Merged PRs [pr192](https://github.com/sigven/pcgr/pull/192), [pr193](https://github.com/sigven/pcgr/pull/193), [pr194](https://github.com/sigven/pcgr/pull/194), [pr196](https://github.com/sigven/pcgr/pull/196). - - See [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) for a few more changes. - -- *May 2022*: **1.0.3 release** - - - Merged [PR #191](https://github.com/sigven/pcgr/pull/191) - -- *March 2022*: **1.0.2 release** - - - Fixed [CPSR issue #44](https://github.com/sigven/cpsr/issues/44) - -- *March 2022*: **1.0.1 release** - - - Fixed bug for huge input sets that cause JSON output crash - - huge input variant sets (WGS) are now reduced prior to reporting with R, i.e. exclusion of intronic and intergenic variants, as well as upstream/downstream gene variants ([#178](https://github.com/sigven/pcgr/issues/178)). - - Fixed bug for cases where mutational signature analysis reports \> 18 different aetiologies after fitting ([#187](https://github.com/sigven/pcgr/issues/187)). - - [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) - -- *February 2022*: **1.0.0 release** +### Example reports - - Complete restructure of Python and R components. Installation now relies on two separate [conda](https://docs.conda.io/en/latest/) packages, `pcgr` (Python component) and `pcgrr` (R component). Direct Docker support remains, with the Dockerfile simplified to rely exclusively on the installation of the above Conda packages. Significant contributon by the great [\@pdiakumis](https://github.com/pdiakumis) - - VCF validation step removed. Feedback from users suggested that Ensembl's `vcf-validator` was often too stringent so its use has been deprecated. The `--no_vcf_validate` option remains for backwards compatibility. - - New documentation site () - - Data bundle updates (CIViC, ClinVar, Open Targets Platform, CancerMine, UniProt KB, Pfam) - - [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11401431.svg)](https://doi.org/10.5281/zenodo.11401431) -- *June 30th 2021*: **0.9.2 release** +### Why use PCGR? - - Data bundle updates (CIViC, ClinVar, CancerMine, UniProt KB, PFAM) - - Software upgrades: VEP (104), R v4.1/BioConductor 3.13 - - **NEW**: TOML configuration removed - all options to PCGR are now command-line based - - **NEW**: Feed PCGR with a [CPSR report](https://github.com/sigven/cpsr) to view key germline findings in the tumor report - - [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) - - Planned for next release: Support for analysis of RNA fusions +The great complexity of acquired mutations in individual tumor genomes poses a severe challenge for clinical interpretation. PCGR aims to be a comprehensive reporting platform that can -- *November 30th 2020*: **0.9.1 release** +- systematically interrogate tumor-specific variants in the context of known therapeutic, diagnostic, and prognostic biomarkers +- highlight genomic aberrations with likely oncogenic potential +- provide a structured and concise summary of the most relevant findings +- present the results in a format accessible to clinical experts - - Data bundle updates (CIViC, ClinVar, CancerMine, UniProt KB) - - [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) +PCGR integrates a [comprehensive set of knowledge resources](articles/annotation_resources.html) related to tumor biology and therapeutic biomarkers, both at the gene, and at the level of individual variants. The software generates a comprehensive molecular interpretation report that supports the translation of individual cancer genomes towards molecularly guided treatment strategies. -### Example reports +### Getting started -[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11401431.svg)](https://doi.org/10.5281/zenodo.11401431) +- [Installation instructions](https://sigven.github.io/pcgr/articles/installation.html) +- [Run through an example](https://sigven.github.io/pcgr/articles/running.html#example-run) +- Learn more about: -### Getting started + 1) Details regarding [PCGR input files](https://sigven.github.io/pcgr/articles/input.html), and how they should be formatted + 2) Configuration of [key settings](https://sigven.github.io/pcgr/articles/running.html) + 3) The types and contents of [PCGR output files](https://sigven.github.io/pcgr/articles/output.html) + 4) [Variant classifications implemented in PCGR](https://sigven.github.io/pcgr/articles/variant_classification.html) + 5) [Primary tumor sites used in PCGR](https://sigven.github.io/pcgr/articles/primary_tumor_sites.html) + 6) The list of [gene and variant annotation resources](https://sigven.github.io/pcgr/articles/annotation_resources.html) used in PCGR annotation -- [Installation instructions](https://sigven.github.io/pcgr/articles/installation.html) -- [Run through an example](https://sigven.github.io/pcgr/articles/running.html#example-run) -- Learn more about - - Details regarding [PCGR input files](https://sigven.github.io/pcgr/articles/input.html), and how they should be formatted - - How to configure [key settings](https://sigven.github.io/pcgr/articles/running.html) - - The types and contents of [PCGR output files](https://sigven.github.io/pcgr/articles/output.html) - - The [variant classifications](https://sigven.github.io/pcgr/articles/variant_classification.html) implemented in PCGR - - The list of [gene and variant annotation resources](https://sigven.github.io/pcgr/articles/annotation_resources.html) used in PCGR annotation -- [Frequenty asked questions (FAQ)](https://sigven.github.io/pcgr/articles/faq.html) +- [Frequently asked questions (FAQ)](https://sigven.github.io/pcgr/articles/faq.html) ### Citation -If you use PCGR, please cite the publication: +If you use PCGR, please cite our publication: -Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, Ola Myklebost, and Eivind Hovig. **Personal Cancer Genome Reporter: variant interpretation report for precision oncology** (2017). *Bioinformatics*. 34(10):1778--1780. [doi:10.1093/bioinformatics/btx817](https://doi.org/10.1093/bioinformatics/btx817) +Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, Ola Myklebost, and Eivind Hovig. **Personal Cancer Genome Reporter: variant interpretation report for precision oncology** (2017). *Bioinformatics*. 34(10):1778--1780. [doi.org/10.1093/bioinformatics/btx817](https://doi.org/10.1093/bioinformatics/btx817) ## Contact diff --git a/pcgrr/R/acmg.R b/pcgrr/R/acmg.R index 7c1e39b0..bd992b6e 100644 --- a/pcgrr/R/acmg.R +++ b/pcgrr/R/acmg.R @@ -142,7 +142,7 @@ assign_acmg_tiers <- function( as.integer(.data$ACMG_TIER_OTHER_VARS) )) |> dplyr::mutate(ACMG_AMP_TIER = dplyr::if_else( - is.na(ACMG_AMP_TIER) & + is.na(.data$ACMG_AMP_TIER) & .data$CODING_STATUS == "noncoding", as.integer(5), as.integer(.data$ACMG_AMP_TIER) diff --git a/pcgrr/R/utils.R b/pcgrr/R/utils.R index 2d7bb183..c3ea3c71 100644 --- a/pcgrr/R/utils.R +++ b/pcgrr/R/utils.R @@ -984,7 +984,7 @@ get_genome_obj <- function(genome) { stop(glue::glue( "{pkg} is not installed on your system.\n", "Please install with:\n'BiocManager::install(\"{pkg}\")'\n", - "(or use 'mamba install -c bioconda bioconductor-bsgenome.hsapiens.ucsc.hgXX' ", + "(or use 'conda install -c bioconda bioconductor-bsgenome.hsapiens.ucsc.hgXX' ", "if inside a conda environment)." )) } diff --git a/pcgrr/pkgdown/index.md b/pcgrr/pkgdown/index.md index 7273de29..81121eb8 100644 --- a/pcgrr/pkgdown/index.md +++ b/pcgrr/pkgdown/index.md @@ -4,23 +4,54 @@ editor_options: wrap: 72 --- +## Personal Cancer Genome Reporter (PCGR) -# Personal Cancer Genome Reporter +## Overview -
+The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual tumor genomes for precision cancer medicine. It interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software classifies variants both with respect to _oncogenicity_, and _actionability_. Interactive HTML output reports allow the user to interrogate the clinical impact of the molecular findings in an individual tumor. -The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual tumor genomes for precision cancer medicine. It interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software [classifies variants](articles/variant_classification.html) both with respect to _oncogenicity_, and _actionability_. Interactive HTML output reports allow the user to interrogate the clinical impact of the molecular findings in an individual tumor. +- Variant classification + - according to *oncogenicity*: evaluating the oncogenic potential of somatic DNA aberrations (VICC/CGC/ClinGen guidelines) + - according to *actionability*: mapping the therapeutic, diagnostic, and prognostic implications of somatic DNA aberrations (ACMG/AMP guidelines) +- Tumor mutational burden (TMB) estimation +- Mutational signature analysis +- Microsatellite instability (MSI) classification +- RNA expression analysis - outlier detection, similarity analysis, and immune contexture profiling -PCGR supports both of the most recent human genome assemblies (grch37/grch38), and accepts variant calls from both tumor-control and tumor-only sequencing assays. Much of the functionality is intended for whole-exome/whole-genome sequencing assays, but you can also apply PCGR to output from targeted sequencing panels. If you are interested in the interrogation of germline variants and their relation to cancer predisposition, we recommend trying the accompanying tool [Cancer Predisposition Sequencing Reporter (CPSR)](https://github.com/sigven/cpsr). +PCGR supports both of the most recent human genome assemblies (GRCh37/GRCh38), and accepts variant calls from both tumor-control and tumor-only sequencing assays. Much of the functionality is intended for whole-exome/whole-genome sequencing assays, but you can also apply PCGR to output from targeted sequencing panels. If you are interested in the interrogation of germline variants and their relation to cancer predisposition, we recommend trying the accompanying tool [Cancer Predisposition Sequencing Reporter (CPSR)](https://github.com/sigven/cpsr). Example screenshots from the [quarto](https://quarto.org)-based cancer genome report by PCGR: -![](img/sc2.png) -![](img/sc1.png) -![](img/sc3.png) +![PCGR screenshot 1](img/sc2.png) +![PCGR screenshot 2](img/sc1.png) +![PCGR screenshot 3](img/sc3.png) PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](http://cancergenomics.no), at the [Institute for Cancer Research, Oslo University Hospital, Norway](http://radium.no). +### Top News + +- *June 2024*: **2.0.0 release** + - Details in [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) + - Massive reference data bundle upgrade, new report layout, oncogenicity classification++ + - Support for Singularity/Apptainer + - Major data/software updates: + - Ensembl VEP `v112` + - ClinVar (2024-06) + - CIViC (2024-06-21) + - GENCODE `v46/v19` (GRCh38/GRCh37) + - CancerMine `v50` (2023-03) + - UniProt KB `v2024_03` + +- *February 2023*: **1.3.0 release** + - Details in [CHANGELOG](http://sigven.github.io/pcgr/articles/CHANGELOG.html) + - prioritize protein-coding BIOTYPE csq ([pr201](https://github.com/sigven/pcgr/pull/201)) + - expose `--pcgrr_conda` option to flexibly activate pcgrr env via a non-default pcgrr name + - `cpsr_validate_input.py`: refactor for efficient custom gene egrep + +- *November 2022*: **1.2.0 release** + - Keep only autosomal, X, Y, M/MT chromosomes + - Import bcftools as dependency + ## Example reports [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11401431.svg)](https://doi.org/10.5281/zenodo.11401431) @@ -29,26 +60,27 @@ PCGR originates from the [Norwegian Cancer Genomics Consortium (NCGC)](http://ca The great complexity of acquired mutations in individual tumor genomes poses a severe challenge for clinical interpretation. PCGR aims to be a comprehensive reporting platform that can -- systematically interrogate tumor-specific variants in the context of known therapeutic, diagnostic, and prognostic biomarkers -- highlight genomic aberrations with likely oncogenic potential -- provide a structured and concise summary of the most relevant findings -- present the results in a format accessible to clinical experts +- systematically interrogate tumor-specific variants in the context of known therapeutic, diagnostic, and prognostic biomarkers +- highlight genomic aberrations with likely oncogenic potential +- provide a structured and concise summary of the most relevant findings +- present the results in a format accessible to clinical experts PCGR integrates a [comprehensive set of knowledge resources](articles/annotation_resources.html) related to tumor biology and therapeutic biomarkers, both at the gene, and at the level of individual variants. The software generates a comprehensive molecular interpretation report that supports the translation of individual cancer genomes towards molecularly guided treatment strategies. ## Getting started -- [Installation instructions](articles/installation.html) -- [Run through an example](articles/running.html#example-run) -- Learn more about - 1) Details regarding [PCGR input files](articles/input.html), and how they should be formatted - 2) Configuration of [key settings](articles/running.html#key-settings) - 3) The types and contents of [PCGR output files](articles/output.html) - 4) [Variant classifications implemented in PCGR](articles/variant_classification.html) - 5) [Primary tumor sites used in PCGR](articles/primary_tumor_sites.html) - 6) The list of [gene and variant annotation resources](articles/annotation_resources.html) available in PCGR -
-- [Frequenty asked questions (FAQ)](articles/faq.html) +- [Installation instructions](articles/installation.html) +- [Run through an example](articles/running.html#example-run) +- Learn more about: + + 1) Details regarding [PCGR input files](articles/input.html), and how they should be formatted + 2) Configuration of [key settings](articles/running.html) + 3) The types and contents of [PCGR output files](articles/output.html) + 4) [Variant classifications implemented in PCGR](articles/variant_classification.html) + 5) [Primary tumor sites used in PCGR](articles/primary_tumor_sites.html) + 6) The list of [gene and variant annotation resources](articles/annotation_resources.html) used in PCGR annotation + +- [Frequently asked questions (FAQ)](articles/faq.html) ## Citation @@ -58,4 +90,4 @@ Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, Ola Mykleb ## Contact -[sigven\@ifi.uio.no](mailto:sigven@ifi.uio.no){.email} +sigven AT ifi.uio.no diff --git a/pcgrr/vignettes/CHANGELOG.Rmd b/pcgrr/vignettes/CHANGELOG.Rmd index a593fb4a..b900940e 100644 --- a/pcgrr/vignettes/CHANGELOG.Rmd +++ b/pcgrr/vignettes/CHANGELOG.Rmd @@ -50,26 +50,26 @@ pdiakumis <- user("pdiakumis") * Date: **2024-06-26** * Major data updates - * ClinVar - * NCI Thesaurus - * Open Targets Platform - * CIViC - * Cancer Biomarkers database (CGI) - * GENCODE + * ClinVar (2024-06) + * NCI Thesaurus `v24.05d` + * Open Targets Platform `v2024.06` + * CIViC (2024-06-21) + * CGI Cancer Biomarkers database (2022/10/17) + * GENCODE `v46/v19` (GRCh38/GRCh37) * Cancer Gene Census - * CancerMine - * Pfam + * CancerMine `v50` (2023-03) + * Pfam `v35.0` (November 2021) * Disease Ontology/EFO - * UniProt KB + * UniProt KB `v2024_03` * Major software updates - * VEP + * Ensembl VEP `v112` -##### Added/changed +### Added/changed - New report generation framework - [quarto](https://quarto.org) - - multiple options related to Rmarkdown output are now deprecated + - multiple options related to RMarkdown output are now deprecated - Re-organized data bundle structure - - Users need to download an assembly-specific VEP cache separately from PCGR/CPSR, and provide its path to the new required argument `--vep_dir` in the `pcgr` command + - Users need to download an assembly-specific VEP cache separately from the Ensembl VEP website, and provide its path to the new required argument `--vep_dir` in the `pcgr` command - Re-engineered data bundle generation pipeline - Improved data bundle documentation - An HTML report with an overview of the contents of the data bundle is shipped with the reference data itself, also available [here (grch38)](https://rpubs.com/sigven/pcgr_refdata). @@ -88,24 +88,26 @@ pdiakumis <- user("pdiakumis") - `--tmb_af_min` - Minimum allele frequency for a position to be considered for TMB calculation (default: 0) - requires allelic support information from VCF - A multi-sheet Excel workbook output with analysis output is provided, suitable e.g. for aggregation of results across samples - argument name changes to `pcgr`: - - `--pcgr_dir` is now named `--refdata_dir` - - `--clinvar_ignore_noncancer` is now named `--clinvar_report_noncancer`, meaning that variants found in ClinVar, yet attributed to _non-cancer related_ phenotypes, are now excluded from reporting by default) - - `--vep_gencode_all` is now named `--vep_gencode_basic`, meaning that the gene variant annotation is now using _all_ GENCODE transcripts by default, not only the _basic_ set) - - `--preserved_info_tags` is now named `--retained_info_tags` - - `--basic` is now named `--no_reporting` - - `--target_size_mb` is now named `--effective_target_size_mb` + - `--pcgr_dir` renamed to `--refdata_dir` + - `--clinvar_ignore_noncancer` renamed to `--clinvar_report_noncancer`, meaning that variants found in ClinVar, yet attributed to _non-cancer related_ phenotypes, are now excluded from reporting by default + - `--vep_gencode_all` renamed to `--vep_gencode_basic`, meaning that the gene variant annotation is now using _all_ GENCODE transcripts by default, not only the _basic_ set + - `--preserved_info_tags` renamed to `--retained_info_tags` + - `--basic` renamed to `--no_reporting` + - `--target_size_mb` renamed to `--effective_target_size_mb` - LOFTEE plugin in VEP removed as loss-of-function variant classifier (due to low level of maintenance, and outdated dependency requirements). For now, a simplified LoF-annotation is used as a replacement, looking primarily at CSQ types (`stop_gained`, `frameshift_variant`, `splice_acceptor_variant`, `splice_donor_variant`). Furthermore, frameshift/stop-gain variants that are found within the last 5% of the coding sequence length are deemed non-LOF, as are splice donor variants not disrupting the canonical site (GC>GT). An even more advanced LoF-annotation is planned for a future release. - Biomarkers are matched much more comprehensively than in previous versions, matching at the genomic level, codon, exon, amino acid and gene level (both principal and non-principal transcript matches) -##### Removed +### Removed -- Options for configuring Rmarkdown output, i.e. `--report_theme`, `report_nonfloating_toc` +- Options for configuring RMarkdown output, i.e. `--report_theme`, `report_nonfloating_toc` - `--cpsr_report` and `--include_trials`, which can provide the report with associated pathogenic germline variants (from CPSR) and potential clinical trial oppertunities is currenly on hold for a forthcoming release - `--no_vcf_validate` - VCF validation is simplified, not relying on _vcf-validator_ anymore - Options to filter tumor-only calls using 1000 Genomes Project database, i.e. `--maf_onekg_eur`, `--maf_onekg_amr`, `--maf_onekg_eas`, `--maf_onekg_afr`, `--maf_onekg_sas`, `--maf_onekg_global` - `--cell_line` - `--logr_gain`, and `--logr_homdel` +--- + ## v1.5.0rc - Date: **2023-xx-xx** diff --git a/pcgrr/vignettes/annotation_resources.Rmd b/pcgrr/vignettes/annotation_resources.Rmd index f1a3da26..dbeda1e5 100644 --- a/pcgrr/vignettes/annotation_resources.Rmd +++ b/pcgrr/vignettes/annotation_resources.Rmd @@ -17,7 +17,7 @@ output: rmarkdown::html_document ### Variant databases of clinical utility * [ClinVar](http://www.ncbi.nlm.nih.gov/clinvar/) - database of clinically related variants (June 2024) - * [CIViC](http://civic.genome.wustl.edu) - clinical interpretations of variants in cancer (June 21st 2024) + * [CIViC](https://civicdb.org) - clinical interpretations of variants in cancer (June 21st 2024) * [CGI](http://www.cancergenomeinterpreter.org/biomarkers) - Cancer Genome Interpreter Cancer Biomarkers Database (CGI) (October 18th 2022) ### Protein domains/functional features From edd0512c6feebc6d212e8a815ad07bb00bdf8924 Mon Sep 17 00:00:00 2001 From: pdiakumis Date: Wed, 26 Jun 2024 23:56:06 +1000 Subject: [PATCH 2/3] add diff to changelog --- pcgrr/pkgdown/index.md | 2 -- pcgrr/vignettes/CHANGELOG.Rmd | 37 ++++++++++++++++++----------------- 2 files changed, 19 insertions(+), 20 deletions(-) diff --git a/pcgrr/pkgdown/index.md b/pcgrr/pkgdown/index.md index 81121eb8..1aa54160 100644 --- a/pcgrr/pkgdown/index.md +++ b/pcgrr/pkgdown/index.md @@ -6,8 +6,6 @@ editor_options: ## Personal Cancer Genome Reporter (PCGR) -## Overview - The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual tumor genomes for precision cancer medicine. It interprets primarily somatic SNVs/InDels and copy number aberrations, and has additional support for interpretation of bulk RNA-seq expression data. The software classifies variants both with respect to _oncogenicity_, and _actionability_. Interactive HTML output reports allow the user to interrogate the clinical impact of the molecular findings in an individual tumor. - Variant classification diff --git a/pcgrr/vignettes/CHANGELOG.Rmd b/pcgrr/vignettes/CHANGELOG.Rmd index b900940e..fa2ef1ee 100644 --- a/pcgrr/vignettes/CHANGELOG.Rmd +++ b/pcgrr/vignettes/CHANGELOG.Rmd @@ -48,21 +48,22 @@ pdiakumis <- user("pdiakumis") ## v2.0.0 -* Date: **2024-06-26** -* Major data updates - * ClinVar (2024-06) - * NCI Thesaurus `v24.05d` - * Open Targets Platform `v2024.06` - * CIViC (2024-06-21) - * CGI Cancer Biomarkers database (2022/10/17) - * GENCODE `v46/v19` (GRCh38/GRCh37) - * Cancer Gene Census - * CancerMine `v50` (2023-03) - * Pfam `v35.0` (November 2021) - * Disease Ontology/EFO - * UniProt KB `v2024_03` -* Major software updates - * Ensembl VEP `v112` +- Date: **2024-06-26** +- Major data updates + - ClinVar (2024-06) + - NCI Thesaurus `v24.05d` + - Open Targets Platform `v2024.06` + - CIViC (2024-06-21) + - CGI Cancer Biomarkers database (2022/10/17) + - GENCODE `v46/v19` (GRCh38/GRCh37) + - Cancer Gene Census + - CancerMine `v50` (2023-03) + - Pfam `v35.0` (November 2021) + - Disease Ontology/EFO + - UniProt KB `v2024_03` +- Major software updates + - Ensembl VEP `v112` +- `r diff("2.0.0", "1.4.1")` ### Added/changed @@ -108,10 +109,10 @@ pdiakumis <- user("pdiakumis") --- -## v1.5.0rc +## v1.4.1 -- Date: **2023-xx-xx** -- `r diff("1.5.0", "1.4.0")` +- Date: **2023-03-14** +- `r diff("1.4.1", "1.4.0")` ### Changes From dd88823228532e81b044be3792b38eb6c6a21abe Mon Sep 17 00:00:00 2001 From: pdiakumis Date: Thu, 27 Jun 2024 00:05:39 +1000 Subject: [PATCH 3/3] update links --- pcgrr/vignettes/annotation_resources.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pcgrr/vignettes/annotation_resources.Rmd b/pcgrr/vignettes/annotation_resources.Rmd index dbeda1e5..41be3124 100644 --- a/pcgrr/vignettes/annotation_resources.Rmd +++ b/pcgrr/vignettes/annotation_resources.Rmd @@ -22,10 +22,10 @@ output: rmarkdown::html_document ### Protein domains/functional features * [UniProt/SwissProt KnowledgeBase](http://www.uniprot.org) - resource on protein sequence and functional information (2024_03) - * [Pfam](http://pfam.xfam.org) - database of protein families and domains (v35.0, November 2021) + * [Pfam](https://www.ebi.ac.uk/interpro/entry/pfam/#table) - database of protein families and domains (v35.0, November 2021) ### Knowledge resources on gene and protein targets - * [CancerMine](https://zenodo.org/record/4925789#.YNT8K5MzY7Q) - Literature-mined database of tumor suppressor genes/proto-oncogenes (v50, March 2023) + * [CancerMine](https://zenodo.org/records/7689627) - Literature-mined database of tumor suppressor genes/proto-oncogenes (v50, March 2023) * [Open Targets Platform](https://www.targetvalidation.org/) - Database on disease-target associations, molecularly targeted drugs and tractability aggregated from multiple sources (literature, pathways, mutations) (2024.06) ### Notes on variant annotation datasets