151 lines
4.1 KiB
Bash
151 lines
4.1 KiB
Bash
#!/bin/bash
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bam_s3_bucket="quantgene-wes-archive"
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upload_s3='true'
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download='true'
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index_bam='true'
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dev_suffix="dev_sref_01"
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stellarpgx_ref="stellar_references/cyp2d6_reference_pgx.bed"
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declare -A vcf_s3_dict
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declare -A bam_s3_dict
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declare -A stellarpgx_ref_dict=(
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["sref_00"]="test3.bed"
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["sref_01"]="cyp2d6_reference_pgx.bed"
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["sref_02"]="cyp2d6_reference_wes_jan6.bed"
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["sref_03"]="cyp2d6_reference_wes_march21.bed"
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)
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while getopts ':r:nx' 'OPTKEY'; do
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case ${OPTKEY} in
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'r')
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stellarpgx_ref="stellar_references/"${stellarpgx_ref_dict[$OPTARG]}
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dev_suffix="dev_"$OPTARG
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;;
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'n')
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download='false'
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;;
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'x')
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index_bam='false'
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;;
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'?')
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echo "INVALID OPTION -- ${OPTARG}" >&2
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exit 1
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;;
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':')
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echo "MISSING ARGUMENT for option -- ${OPTARG}" >&2
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exit 1
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;;
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*)
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echo "UNIMPLEMENTED OPTION -- ${OPTKEY}" >&2
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exit 1
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;;
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esac
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done
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echo "----------------------------------------------------------------"
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# ------------------------ Start PGx Engine --------------------------
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echo -n "Start Docker container: "
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docker start pgx-api
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# ------------------------ Empty data folder -------------------------
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if $download; then
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if ! [ -z "$(ls -A data)" ]; then
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echo "Remove existing files in data folder"
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rm -r data/*
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fi
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fi
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# --------------------- Download files from S3 -----------------------
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while IFS= read vcf_s3; do
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temp=($(echo $vcf_s3 | tr "/" "\n"))
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vcf_s3_bucket="${temp[1]}"
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flowcell="${temp[2]}"
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run="${temp[3]}"
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sample="${temp[4]::-4}"
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vcf_s3_prefix="s3://${vcf_s3_bucket}/${flowcell}/${run}"
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bam_s3_prefix="s3://${bam_s3_bucket}/${run}"
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vcf_s3_dict[$sample]=$vcf_s3_prefix
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bam_s3_dict[$sample]=$bam_s3_prefix
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bam_s3="${bam_s3_prefix}/${sample}.deduped.bam"
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if $download; then
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aws s3 cp $vcf_s3 data/
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aws s3 cp $bam_s3 data/
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echo "SAMPLE DOWNLOAD COMPlETE"
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fi
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done
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echo "ALL DOWNLOADS COMPlETE"
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# ------------------------ Index BAM files ---------------------------
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if $index_bam; then
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for f in data/*.bam; do
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echo "Indexing: "$f
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samtools index $f $f".bai"
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done
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fi
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# ------------------------ Run Stellar PGx ---------------------------
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echo "Starting stellar PGx"
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cp $stellarpgx_ref resources/cyp2d6/cyp_hg38/test3.bed
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./run_stellar.sh
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# ------------------- Generate final PGx Output ----------------------
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for f in data/*.vcf; do
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s=${f::-4}
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printf "\nRun PGx Engine for: ${s:5}\n"
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python3 combine_outside_calls.py $s
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curl -X 'POST' \
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'http://localhost:5000/run' \
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-H 'accept: application/json' \
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-H 'Content-Type: multipart/form-data' \
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-F "files=@${s}.vcf;type=text/x-vcard" \
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-F "files=@${s}_outside_call.tsv" \
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-o "${s}_pgx_result.zip"
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done
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# ----------------------- Stop PGx Engine ----------------------------
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echo ""
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echo -n "Stop Docker container: "
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docker stop pgx-api
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# ---------------------- Post-Processing -----------------------------
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if ! [ -z "$(ls -A pgx_results)" ]; then
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echo "Remove existing files in pgx_results folder"
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rm -r pgx_results/*
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fi
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echo "Copy PGx Output to pgx_results"
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cp data/*.zip pgx_results/
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echo "Unzip and create diplotype/rsid overview"
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python3 create_overview.py
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echo "Copy over allele files"
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python3 copy_allele_file.py
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rm -r work/*
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rm data/*outside*
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rm data/*zip
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rm data/*.alleles
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# --------------------- Upload files to S3 ---------------------------
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if $upload_s3; then
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for result in $(ls -d pgx_results/*); do
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sample="${result:12:-11}"
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vcf_s3_prefix=${vcf_s3_dict[$sample]}
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bam_s3_prefix=${bam_s3_dict[$sample]}
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aws s3 cp "${result}/output.json" "${vcf_s3_prefix}/${sample}.${dev_suffix}.json" --storage-class INTELLIGENT_TIERING
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echo -n "Compressing: "
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tar -zcvf "${result}.${dev_suffix}.tar.gz" "${result}"
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aws s3 cp "${result}.${dev_suffix}.tar.gz" "${bam_s3_prefix}/" --storage-class INTELLIGENT_TIERING
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done
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fi
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printf "\nDone\n"
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echo "----------------------------------------------------------------"
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