Simple workflow to call short variants in somatic whole genome data
This snakemake workflow takes .bam
files, which were prepped according to
GATK best practices,
and calls SNVs and small Indels. The workflow can process tumor samples
paired with normals or be run as a tumor-only analysis.
The variant calling is done according to this tutorial and requires a panel of normals (PoN).
Calling variants with VarDict is performed as as indicated in the respective repository.
To run this workflow, the following tools need to be available:
- Add all sample ids to
samples.tsv
in the columnsample
. - Add sample type information, normal or tumor, to
units.tsv
. - Use the
analysis_output
folder from wgs_std_viper as input. - If a PoN was not created earlier, use the
analysis_output
folder from wgs_somatic_pon as input.
- You need a reference
.fasta
file representing the genome used for mapping. For the different tools to work, you also need to prepare index files and a.dict
file.
- The required files for the human reference genome GRCh38 can be downloaded from
google cloud.
The download can be manually done using the browser or using
gsutil
via the command line:
gsutil cp gs://genomics-public-data/resources/broad/hg38/v0/Homo_sapiens_assembly38.fasta /path/to/download/dir/
- If those resources are not available for your reference you may generate them yourself:
samtools faidx /path/to/reference.fasta
gatk CreateSequenceDictionary -R /path/to/reference.fasta -O /path/to/reference.dict
- A VarDict
.bed
file containing all these genomic regions, which Vardict should call variants in. The regions should be split by 5 MBp or less. - Mutect2 requires a panel of normals (PoN) which should be supplied. If you do not
have a PoN you can simply leave
""
instead to link the workflow to the output from wgs_somatic_pon. - Mutect2 also requires a modified gnomad database
as a
.vcf.gz
. For GRCh38, the file can be retrieved from google cloud as described under 1. - Add the paths of the different files to the
config.yaml
. The index files should be in the same directory as the reference.fasta
. - Make sure that the docker container versions are correct.
The workflow repository contains a small test dataset .tests/integration
which can be run like so:
cd .tests/integration
snakemake -s ../../workflow/Snakefile -j1 --use-singularity
The workflow is designed for WGS data meaning huge datasets which require a lot of compute power. For HPC clusters, it is recommended to use a cluster profile and run something like:
snakemake -s /path/to/Snakefile --profile my-awesome-profile