Description:

• A GPU-accelarated snakemake workflow that calls variants from multi-sample illumina reads using Deepvariant and GLnexus

Files to prepare:

• A sample sheet - sample_sheet.csv: a comma delimited file with 3 columns (no column name):
  • sample, path to illumina read1, path to illumina read2
• Modify configuration file - config.yaml:
  • reference: path to reference fasta file
  • sample_sheet: path to the sample sheet prepared above
  • outdir: path to the output directory
  • suffix: illumina reads' suffix of forward reads and reverse reads. For example:
    • test1_R1.fastq.gz and test1_R2.fastq.gz should be ["_R1","_R2"]
  • cpu: number of cores provided to the pipeline, should be the same as the command line parameter
  • w_size: non-overlapping window size of reporting average depth along the genome.

Environment:

• Make sure snakemake is installed in current environment.
• Docker is required.
• Install docker image: nvcr.io/nvidia/clara/clara-parabricks:4.0.0-1
• Install docker image: google/deepvariant:1.4.0-gpu

Usage:

snakemake --cores [cpu] --use-conda