Deepvariant

Introduction

DeepVariant is a deep learning-based variant caller that takes aligned reads (in BAM or CRAM format), produces pileup image tensors from them, classifies each tensor using a convolutional neural network, and finally reports the results in a standard VCF or gVCF file.

For more information, please check:
Home page: https://github.com/google/deepvariant

Versions

  • 1.0.0

  • 1.1.0

Commands

  • call_variants

  • get-pip.py

  • make_examples

  • model_eval

  • model_train

  • postprocess_variants

  • run-prereq.sh

  • run_deepvariant

  • run_deepvariant.py

  • settings.sh

  • show_examples

  • vcf_stats_report

Module

You can load the modules by:

module load biocontainers
module load deepvariant

Example job

Warning

Using #!/bin/sh -l as shebang in the slurm job script will cause the failure of some biocontainer modules. Please use #!/bin/bash instead.

To run deepvariant on our clusters:

#!/bin/bash
#SBATCH -A myallocation     # Allocation name
#SBATCH -t 1:00:00
#SBATCH -N 1
#SBATCH -n 4
#SBATCH --job-name=deepvariant
#SBATCH --mail-type=FAIL,BEGIN,END
#SBATCH --error=%x-%J-%u.err
#SBATCH --output=%x-%J-%u.out

module --force purge
ml biocontainers deepvariant

INPUT_DIR="${PWD}/quickstart-testdata"
DATA_HTTP_DIR="https://storage.googleapis.com/deepvariant/quickstart-testdata"
mkdir -p ${INPUT_DIR}
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/NA12878_S1.chr20.10_10p1mb.bam
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/NA12878_S1.chr20.10_10p1mb.bam.bai
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/test_nist.b37_chr20_100kbp_at_10mb.bed
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/test_nist.b37_chr20_100kbp_at_10mb.vcf.gz
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/test_nist.b37_chr20_100kbp_at_10mb.vcf.gz.tbi
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/ucsc.hg19.chr20.unittest.fasta
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/ucsc.hg19.chr20.unittest.fasta.fai
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/ucsc.hg19.chr20.unittest.fasta.gz
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/ucsc.hg19.chr20.unittest.fasta.gz.fai
wget -P ${INPUT_DIR} "${DATA_HTTP_DIR}"/ucsc.hg19.chr20.unittest.fasta.gz.gzi

run_deepvariant --model_type=WGS --ref="${INPUT_DIR}"/ucsc.hg19.chr20.unittest.fasta  --reads="${INPUT_DIR}"/NA12878_S1.chr20.10_10p1mb.bam  --regions "chr20:10,000,000-10,010,000"  --output_vcf="output/output.vcf.gz"  --output_gvcf="output/output.g.vcf.gz" --intermediate_results_dir "output/intermediate_results_dir"  --num_shards=4