The variant_pipline_scripts from miaaltieri

variant_pipline_scripts's Introduction

| | | DeepVariant Instructions | |________________________________________|

-To get an idea of how to run this DeepVariant pipeline, we suggest you follow the instructions below -These instructions are essentially the instructions in https://github.com/google/deepvariant/blob/master/docs/deepvariant-quick-start.md -You may need to download some files, so visit that link as necessary

First set the following variables:

BIN_VERSION="0.7.2" MODEL_VERSION="0.7.2"

MODEL_NAME="DeepVariant-inception_v3-${MODEL_VERSION}+data-wgs_standard" MODEL_HTTP_DIR="https://storage.googleapis.com/deepvariant/models/DeepVariant/${MODEL_VERSION}/${MODEL_NAME}" DATA_HTTP_DIR="https://storage.googleapis.com/deepvariant/quickstart-testdata"

OUTPUT_DIR=${HOME}/quickstart-output REF=${HOME}/quickstart-testdata/ucsc.hg19.chr20.unittest.fasta BAM=${HOME}/quickstart-testdata/NA12878_S1.chr20.10_10p1mb.bam MODEL="${HOME}/${MODEL_NAME}/model.ckpt"

FINAL_OUTPUT_VCF="${OUTPUT_DIR}/output.vcf.gz"

Then call the deep variant pipeline bash deep_variant_pipline.sh
model=“${MODEL}”
ref=${REF}
bam=${BAM}
region=chr20:10000000-10010000
sample_name=NA12878
--bin_vs=${BIN_VERSION}
--model_vs=${MODEL_VERSION}
--output=${OUTPUT_DIR}
--output_vcf="${OUTPUT_DIR}/output.vcf.gz"
--log_dir=${HOME}/logs
--threads=3
cpu
To evaluate the results call the hap.py pipeline as follows bash happy_script.sh
--truth_vcf=${HOME}/quickstart-testdata/test_nist.b37_chr20_100kbp_at_10mb.vcf.gz
--final_ouput_vcf=${FINAL_OUTPUT_VCF}
--confident_bed=${HOME}/quickstart-testdata/test_nist.b37_chr20_100kbp_at_10mb.bed
--happy_output=${OUTPUT_DIR}/happy.output
--threads=3
ref=${REF}