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qbic-pipelines/rnadeseq: Usage

Table of contents

Introduction

Nextflow handles job submissions on SLURM or other environments, and supervises running the jobs. Thus the Nextflow process must run until the pipeline is finished. We recommend that you put the process running in the background through screen / tmux or similar tool. Alternatively you can run nextflow within a cluster job submitted your job scheduler.

It is recommended to limit the Nextflow Java virtual machines memory. We recommend adding the following line to your environment (typically in ~/.bashrc or ~./bash_profile):

NXF_OPTS='-Xms1g -Xmx4g'

Pre-requisites

The qbic-pipelines/rnadeseq pipeline relies on the output from the nf-core/rnaseq pipeline. To be able to match the results of the nf-core/rnaseq pipeline with the metadata sheet containing the experimental design for the differential expression analysis, the filenames of the fastq files used as input to the qbic-pipelines/rnadeseq pipeline, need to start with the corresponding QBiC codes!. E.g. QBICKXXXXX_original_file_name.fastq. Once the filenames are corrected if necessary, you can run the qbic-pipelines/rnadeseq pipeline as usual.

Running the pipeline

The typical command for running the pipeline is as follows:

nextflow run qbic-pipelines/rnadeseq -r 1.1.0 -profile docker \
--rawcounts 'merged_gene_counts.txt' \
--metadata 'QXXXX_sample_preparations.tsv' \
--model 'linear_model.txt' \
--contrast_matrix 'contrasts.tsv' \
--project_summary 'QXXXX_summary.tsv' \
--multiqc 'MultiQC.zip' \
--quote 'QXXXX_signed_offer.pdf' \
--versions 'software_versions.csv' \
--report_options 'report_options.yml' \
--species Hsapiens

This will launch the pipeline with the docker configuration profile. See below for more information about profiles.

Note that the pipeline will create the following files in your working directory:

work            # Directory containing the nextflow working files
results         # Finished results (configurable, see below)
.nextflow_log   # Log file from Nextflow
# Other nextflow hidden files, eg. history of pipeline runs and old logs.

Updating the pipeline

When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline:

nextflow pull qbic-pipelines/rnadeseq

Reproducibility

It's a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since.

First, go to the qbic-pipelines/rnadeseq releases page and find the latest version number - numeric only (eg. 1.3.1). Then specify this when running the pipeline with -r (one hyphen) - eg. -r 1.3.1.

This version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future.

Mandatory arguments

-profile

Use this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments. Note that multiple profiles can be loaded, for example: -profile docker, test - the order of arguments is important!

If -profile is not specified at all the pipeline will be run locally and expects all software to be installed and available on the PATH.

  • awsbatch
    • A generic configuration profile to be used with AWS Batch.
  • conda
    • A generic configuration profile to be used with conda
    • Pulls most software from Bioconda
  • docker
  • singularity
  • test
    • A profile with a complete configuration for automated testing
    • Includes links to test data so needs no other parameters

--rawcounts

Raw count table (TSV). Column names must start with the QBiC code. Columns are samples and rows are genes. For example:

--rawcounts 'path/to/raw_count_table.tsv'

--metadata

Metadata table is the "Sample_preparations_sheet.tsv" that can be directly downloaded from the qPortal --> Browser. Rows are samples and columns contain sample grouping. Important columns are:

  • QBiC Code: is needed to match metadata with the raw counts.
  • Secondary Name, samples will be named with the pattern: QBiC code + Secondary name.
  • Condition: tag: a separated column for each of the conditions. The headers of this columns start with "Condition: ". The values of these columns should not contain spaces.

--model

Linear model function to calculate the contrasts (TXT). Variable names should be "condition_tag", where the tag matches the "Condition: tag" headers in the metadata file. E.g.

~ condition_genotype + condition_treatment

--species

Species name. For example: Hsapiens, Mmusculus. To include new species, please open an issue with the species full scientific name.

--project_summary

Project summary as downloaded from the portal: User database portlet, Projects tab, select your project and "Download Project Information". Please check first that this information is correct in the project Browser.

--multiqc

Path to the MultiQC zipped folder containing the MultiQC plots generated by the RNAseq pipeline, the MultiQC html report, and the MultiQC raw data.

--versions

Path to the Software_versions.csv file generated by the RNAseq pipeline.

Contrasts

There are three different parameters that can be used to define contrasts, which are explained in the following sections. One or multiple contrast input files can be provided, if multiple are provided, the contrasts in the multiple files will be added to the report.

Default

By default, DESeq2 will calculate some pairwise contrasts given the linear model file. If you do not provide any contrast files, the differential gene expression analysis will be performed with the default contrasts as calculated by DESeq2. Try this option first, if you are unsure about your contrasts.

--relevel

Sometimes condition factors have obvious levels. By default, the base level of a factor will be the first one when sorted alphabetically. In order to manually sort factors, to set them as the denominator for your contrasts, you can use this parameter to provide a tsv file for releveling the factor(s) for your contrast(s). An example input tsv file is shown here:

factor  level
condition_genotype  wild_type
condition_treatment control

--contrast_matrix

Table in tsv format indicating which contrasts to consider. Each contrast is specified in one column, each row corresponds to the each of the expanded terms of the linear model. If you are unsure about how the linear model expanded terms look like, run the pipeline once without specifying contrasts, then the coefficient terms for the provided model will be stored under "differential_gene_expression/metadata/DESeq2_coefficients.tsv". An example input tsv file is shown here:

coefficient treatment_treated_vs_control  genotype_KO_vs_WT
intercept 0 0
condition_treatment_treated 1 0
condition_genotype_KO 0  1

--contrast_list

Table in tsv format indicating which contrasts to consider. Each contrast is specified in one row. The columns correspond to the factor, the level to be considered in the numerator and the level to be considered in the denominator of the contrast. For example:

factor  numerator denominator
condition_treatment treated control
condition_genotype  KO  WT

`--contrast_pairs``

Table in tsv format indicating pairs of contrasts to consider. This is used to calculate interaction effects between contrasts. Each row corresponds to an interaction effect. The first column indicates the desired contrast name, the second column the first contrast in the numerator and the third column the contrast in the denominator, of the interaction.

contrast_name contrast_numerator contrast_denominator
interaction_effect condition_treatment_treated_vs_control  condition_genotype_KO_vs_WT

Optional arguments

--logFCthreshold

Threshold (int) to apply to Log 2 Fold Change to consider a gene as differentially expressed. There is no threshold applied by default to Log2 Fold Change.

--genelist

List of genes (one per line) of which to plot heatmaps for normalized counts across all samples. The gene list should contain gene HUGO symbols (no Ensemble IDs).

--batch_effect

Option needed to account for batch effects in the data. Please check the section Controlling for batch effects to do so.

--quote

Path to the signed copy of the QBiC offer as pdf, to be included in the report.

--report_options

Configuration file describing the sections that need to be present in the report, text can also be specified that is desired to be added to the outlook section. Check here an example file.

--kegg_blacklist

Text file containing KEGG pathways codes to be excluded from pathway plotting (e.g. because kegg pathways xml contain errors in the KEGG resource).

Special cases

Controlling for batch effects

To control for batch effects follow ALL these steps:

  • Include the batch effect in the metadata file in a column with the header batch.

  • Your design file needs to additionally include the batch effect in the linear model. E.g.:

    ~ batch + condition_genotype

  • Use the --batch_effect option when running the pipeline to generate an extra PCA plot with the corrected batch effects.

Then the DESeq2 script calculates the contrasts as usual, the batch effect just needs to be considered during the design definition. For more information, please check the DESeq2 vignette.

AWS Batch specific parameters

Running the pipeline on AWS Batch requires a couple of specific parameters to be set according to your AWS Batch configuration. Please use the -awsbatch profile and then specify all of the following parameters.

--awsqueue

The JobQueue that you intend to use on AWS Batch.

--awsregion

The AWS region to run your job in. Default is set to eu-west-1 but can be adjusted to your needs.

The syntax for this reference configuration is as follows:

Job resources

Automatic resubmission

Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with an error code of 143 (exceeded requested resources) it will automatically resubmit with higher requests (2 x original, then 3 x original). If it still fails after three times then the pipeline is stopped.

Custom resource requests

Wherever process-specific requirements are set in the pipeline, the default value can be changed by creating a custom config file. See the files hosted at nf-core/configs for examples.

If you are likely to be running qbic-pipelines pipelines regularly it may be a good idea to request that your custom config file is uploaded to the nf-core/configs git repository. Before you do this please can you test that the config file works with your pipeline of choice using the -c parameter (see definition below). You can then create a pull request to the nf-core/configs repository with the addition of your config file, associated documentation file (see examples in nf-core/configs/docs), and amending nfcore_custom.config to include your custom profile.

If you have any questions or issues please send us a message on Slack.

Other command line parameters

-c

Specify the path to a specific config file (this is a core NextFlow command).

NB: Single hyphen (core Nextflow option)

Note - you can use this to override pipeline defaults.

--custom_config_version

Provide git commit id for custom Institutional configs hosted at nf-core/configs. This was implemented for reproducibility purposes. Default is set to master.

## Download and use config file with following git commid id
--custom_config_version d52db660777c4bf36546ddb188ec530c3ada1b96

--custom_config_base

If you're running offline, nextflow will not be able to fetch the institutional config files from the internet. If you don't need them, then this is not a problem. If you do need them, you should download the files from the repo and tell nextflow where to find them with the custom_config_base option. For example:

## Download and unzip the config files
cd /path/to/my/configs
wget https://github.com/nf-core/configs/archive/master.zip
unzip master.zip

## Run the pipeline
cd /path/to/my/data
nextflow run /path/to/pipeline/ --custom_config_base /path/to/my/configs/configs-master/

Note that the nf-core/tools helper package has a download command to download all required pipeline files + singularity containers + institutional configs in one go for you, to make this process easier.

--max_memory

Use to set a top-limit for the default memory requirement for each process. Should be a string in the format integer-unit. eg. --max_memory '8.GB'

--max_time

Use to set a top-limit for the default time requirement for each process. Should be a string in the format integer-unit. eg. --max_time '2.h'

--max_cpus

Use to set a top-limit for the default CPU requirement for each process. Should be a string in the format integer-unit. eg. --max_cpus 1

--plaintext_email

Set to receive plain-text e-mails instead of HTML formatted.

--monochrome_logs

Set to disable colourful command line output and live life in monochrome.

--multiqc_config

Specify a path to a custom MultiQC configuration file.