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#!/bin/bash
########################
## In this gist, we'll reuse the commands from our 3.6 tutorial to align reads and generate BAM files.
## Check out the full post at https://medium.com/@johnnyisraeli/accelerating-germline-and-somatic-genomic-analysis-of-whole-genomes-and-exomes-with-nvidia-clara-e3deeae2acc9
and Gists at:
## https://gist.github.com/edawson/e84b2785db75d3c0aea9cc6a59969d45#file-full_pipeline_and_data_prep_parabricks3-6-sh
## and
## https://gist.github.com/edawson/e84b2785db75d3c0aea9cc6a59969d45#file-step_1_align_reads_parabricks3-6-sh
###########
###########
## We'll run this tutorial on a GCP VM with 64 vCPUs, 240GB of RAM, and 8x NVIDIA V100 GPUs
## To save costs, you can also run this on a GCP VM with 32 vCPUS, 120GB of RAM, and 4x V100 GPUs
###########
## After aligning our reads, we'll rerun the variant calling stages of our past gist
## since we've updated the haplotypecaller and DeepVariant tools. We'll
## also run Strelka2 as an additional variant caller.
##
## After that, we'll merge our VCFs to generate a union callset and an intersection VCF
## with variants called by all three variant callers, annotate our new intersection VCF,
## and remove variants that fail certain criteria for population frequency.
## Finally, we'll run our vcfqc and vcfqcbybam tools to generate simple quality control reports.
#############
################
## HaplotypeCaller
## This step should take roughly 15 minutes on our 8xV100 VM.
################
time pbrun haplotypecaller \
--ref ~/refs/Homo_sapiens_assembly38.fasta \
--in-bam HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.bam \
--in-recal-file HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.BQSR-REPORT.txt \
--out-variants HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.haplotypecaller.vcf
################
## DeepVariant
## This step should take approximately 20 minutes on an 8xV100 VM
################
time pbrun deepvariant \
--ref Homo_sapiens_assembly38.fasta \
--in-bam HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.bam \
--out-variants HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.deepvariant.vcf
###############
## Strelka
## This step should take ~10 minutes on a 64-core VM.
###############
time pbrun strelka \
--ref Homo_sapiens_assembly38.fasta \
--in-bams HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.bam \
--out-prefix HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.strelka \
--num-threads 64
## Copy strelka results to current directory.
cp HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.strelka.strelka_work/results/variants/variants.vcf.gz* .
## BGZIP and tabix-index the deepvariant VCFs
bgzip -@16 HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.deepvariant.vcf
tabix HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.deepvariant.vcf.gz
## BGZIP and tabix index the haplotypecaller VCFs
bgzip -@16 HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.haplotypecaller.vcf
tabix HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.haplotypecaller.vcf.gz
## Run the votebasedvcfmerger tool to generate a union and intersection VCF.
time pbrun votebasedvcfmerger \
--in-vcf strelka:variants.vcf.gz \
--in-vcf deepvariant:HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.deepvariant.vcf.gz \
--in-vcf haplotypecaller:HG002.hiseqx.pcr-free.30x.dedup.grch37.bam2fq.hg38.pb.haplotypecaller.vcf.gz \
--min-votes 3
--out-dir HG002.realign.vbvm
## The HG002.realign.vbvm directory should now contain a
## unionVCF.vcf file with the union callset of HaplotypeCaller, Strelka, and DeepVariant
## and aa filteredVCF.vcf file with only calls produced by all three callers.
## Annotate the intersection VCF with gnomAD, ClinVar, 1000 Genomes
## Download our annotation VCFs and tabix indices
wget https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz
wget https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz.tbi
wget https://storage.googleapis.com/gcp-public-data--gnomad/release/2.1.1/liftover_grch38/vcf/exomes/gnomad.exomes.r2.1.1.sites.liftover_grch38.vcf.bgz
wget https://storage.googleapis.com/gcp-public-data--gnomad/release/2.1.1/liftover_grch38/vcf/exomes/gnomad.exomes.r2.1.1.sites.liftover_grch38.vcf.bgz.tbi
wget http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/release/20181203_biallelic_SNV/ALL.wgs.shapeit2_integrated_v1a.GRCh38.20181129.sites.vcf.gz
wget http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000_genomes_project/release/20181203_biallelic_SNV/ALL.wgs.shapeit2_integrated_v1a.GRCh38.20181129.sites.vcf.gz.tbi
## Download an Ensembl GTF to annotate the VCF file with gene names
wget http://ftp.ensembl.org/pub/release-105/gtf/homo_sapiens/Homo_sapiens.GRCh38.105.gtf.gz
## Unzip the GTF file and add the "chr" prefix to the chromosome names (Ensembl excludes this prefix by default.
gunzip Homo_sapiens.GRCh38.105.gtf.gz
awk '{if($0 !~ /^#/) print "chr"$0; else print $0}' Homo_sapiens.GRCh38.105.gtf > Homo_sapiens.GRCh38.105.chr.gtf
time pbrun snpswift \
--input-vcf HG002.realign.vbvm/filteredVCF.vcf \
--anno-vcf 1000Genomes:ALL.wgs.shapeit2_integrated_v1a.GRCh38.20181129.sites.vcf.gz \
--anno-vcf gnomad_v2.1.1:gnomad.exomes.r2.1.1.sites.liftover_grch38.vcf.bgz \
--anno-vcf ClinVar:clinvar.vcf.gz \
--ensembl Homo_sapiens.GRCh38.105.chr.gtf \
--output-vcf HG002.realign.3callers.annotated.vcf
##################
## frequencyfiltration
## Next we'll filter our VCF to remove variants with 1000Genomes allele frequency > 0.05
## and gnomAD AF < 0.05
##################
time pbrun frequencyfiltration \
--in-vcf HG002.realign.3callers.annotated.vcf \
--and-expression "1000Genomes_AF < 0.05" \
--and-expression "gnomad_v2.1.1_AF < 0.05" \
--out-vcf HG002.realign.3callers.annotated.filtered.vcf
##################
## Finally, we'll run our automated vcfqc tool to generate some
## basic QC stats. The vcfqcbybam tool could also be run
## to produce QC stats using an auxilliary BAM file (e.g., when variant calls don't have the desired fields).
##################
time pbrun vcfqc --in-vcf HG002.realign.3callers.annotated.filtered.vcf \
--output-dir HG002.realign.3callers.annotated.filtered.qc \
--depth haplotypecaller_DP --allele-depth deepvariant_AD
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