BioWDL: gatk-variantcalling

A pipeline that calls variants on a group of BAM files.

Please be aware that the page you are currently viewing is not for the latest available version!

This workflow can be used to generate a multisample VCF file from BAM files using GATK HaplotypeCaller.

This workflow is part of BioWDL developed by the SASC team at Leiden University Medical Center.

Usage

This workflow can be run using Cromwell:

java -jar cromwell-<version>.jar run -i inputs.json multisample-variantcalling.wdl

The pipeline can be integrated into other pipelines as well. It has been split up into three parts for convenience.

Inputs

Inputs are provided through a JSON file. The minimally required inputs are described below and a template containing all possible inputs can be generated using Womtool as described in the WOMtool documentation. For an overview of all available inputs, see this page.

{
  "MultisampleCalling.referenceFasta": "A reference fasta file",
  "MultisampleCalling.referenceFastaFai": "The index for the reference fasta",
  "MultisampleCalling.referenceFastaDict": "The dict file for the reference fasta",
  "MultisampleCalling.bamFilesAndGenders": "A list of structs. Each struct contains the bam file, the index and the gender of the sample. The gender is optional. " 
 }

gender can be set to null. Actionable values are female, male, F, f, M, or m. Any other values and null will handle the sample as an “unknown” gender.

The following actions are taken for each gender:

Some additional inputs which may be of interest are:

{
  "MultisampleCalling.dbsnpVCF": "A dbSNP VCF file with known variants.",
  "MultisampleCalling.dbsnpVCFIndex": "Index (.tbi) for the dbSNP VCF file",
  "MultisampleCalling.regions": "The path to a bed file containing the regions for which variant calling will be performed",
  "MultisampleCalling.scatterSize": "The size of scatter regions (see explanation of scattering below), defaults to 10,000,000",
  "MultisampleCalling.vcfBasename": "The basename of the to be outputed VCF files, defaults to 'multisample'",
  "MultisampleCalling.XNonParRergions": "Bed file with the non-PAR regions of X. Required for gender-aware variant calling.",
  "MultisampleCalling.YNonParRegions": "Bed file with the non-PAR regions of Y. Required for gender-aware variant calling.",
  "MultisampleCalling.singleSampleGvcf": "Output Gvcfs for every single sample."
}

When the X and Y non-PAR regions are not both provided, GATK will call all chromosomes with ploidy 2 naively.

By default GVCFs are not created for every single sample as it requires a lot of extra space and write actions. If the option to output single sample GVCFs is turned on, this will happen in parallel with the creation of the multisample GVCF file.

An output directory can be set using an options.json file. See the cromwell documentation for more information.

Example options.json file:

{
"final_workflow_outputs_dir": "my-analysis-output",
"use_relative_output_paths": true,
"default_runtime_attributes": {
  "docker_user": "$EUID"
  }
}

Alternatively an output directory can be set with MultisampleCalling.outputDir. MultisampleCalling.outputDir must be mounted in the docker container. Cromwell will need a custom configuration to allow this.

Example

{
  "MultisampleCalling.dbsnpVCF": "/home/user/genomes/human/dbsnp/dbsnp-151.vcf.gz",
  "MultisampleCalling.dbsnpVCFIndex": "/home/user/genomes/human/dbsnp/dbsnp-151.vcf.gz.tbi",
  "MultisampleCalling.referenceFasta": "/home/user/genomes/human/GRCh38.fasta",
  "MultisampleCalling.referenceFastaFai": "/home/user/genomes/human/GRCh38.fasta.fai",
  "MultisampleCalling.referenceFastaDict": "/home/user/genomes/human/GRCh38.dict",
  "MultisampleCalling.vcfBasename": "s1",
  "MultisampleCalling.XNonParRegions": "/home/user/genomes/human/x_non_par.bed",
  "MultisampleCalling.YNonParRegions": "/home/user/genomes/human/y_non_par.bed",
  "MultisampleCalling.outputDir": "/home/user/analysis/results/",
  "MultisampleCalling.bamFilesAndGenders": [
    {"file": "/home/user/mapping/results/s1_1.bam",
     "index":  "/home/user/mapping/results/s1_1.bai",
     "gender":"male"},
    {"file": "/home/user/mapping/results/s1_2.bam",
     "index": "/home/user/mapping/results/s1_2.bai",
     "gender": "female"},
    {"file": "/home/user/mapping/results/s1_3.bam",
     "index":  "/home/user/mapping/results/s1_3.bai",
     "gender": null}
   ]
}

Dependency requirements and tool versions

Biowdl pipelines use docker images to ensure reproducibility. This means that biowdl pipelines will run on any system that has docker installed. Alternatively they can be run with singularity.

For more advanced configuration of docker or singularity please check the cromwell documentation on containers.

Images from biocontainers are preferred for biowdl pipelines. The list of default images for this pipeline can be found in the default for the dockerImages input.

output

A multisample vcf file and a multisample gvcf file.

Scattering

This pipeline performs scattering to speed up analysis on grid computing clusters. This is done by splitting the reference genome into regions of roughly equal size (see the scatterSize input). Each of these regions will be analyzed in separate jobs, allowing them to be processed in parallel.

For each BAM file input in the pipeline these scatters will be used. For example, with 5 BAM files and 4 scatters, 20 jobs will run to genotype the BAM files. The resulting GVCF files will be merged. Then GatkGenotypeGVCF will be scattered over the 4 scatters to create a VCF per scatters. The output is merged into a multisample vcf.

Contact

For any question related to this workflow, please use the github issue tracker or contact the SASC team directly at: sasc@lumc.nl.