81 lines
3.0 KiB
Bash
Executable File
81 lines
3.0 KiB
Bash
Executable File
outputDir=$1
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name=$2
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tumor=$3
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codes_dir=$4
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ref="/dataseq/jmdna/database/genome/hg19/hg19.fa"
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neoDir="$outputDir/neoantigen"
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max_peptide_length=11
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##step1:vep annotation and variant filter
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vep \
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--input_file $outputDir/mutation/${name}.snp.indel.Somatic.hc.vcf --output_file ${neoDir}/${name}_somatic_vepanno.vcf \
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--format vcf --vcf --symbol --terms SO --tsl \
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--hgvs --fasta /dataseq/jmdna/database/genome/hg19/ \
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--offline --cache --dir /dataseq/jmdna/software/.vep/ \
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--plugin Downstream --plugin Wildtype --plugin Frameshift \
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--pick \
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--transcript_version 100 \
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--force_overwrite
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vep \
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--input_file $outputDir/mutation/${name}.snp.indel.Germline.vcf --output_file ${neoDir}/${name}_germline_vepanno.vcf \
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--format vcf --vcf --symbol --terms SO --tsl \
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--hgvs --fasta /dataseq/jmdna/database/genome/hg19/ \
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--offline --cache --dir /dataseq/jmdna/software/.vep/ \
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--plugin Downstream --plugin Wildtype --plugin Frameshift \
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--pick \
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--transcript_version 100 \
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--force_overwrite
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perl ${codes_dir}/neoantigen.variant.filter.pl germline ${tumor} ${name} ${neoDir}/${name}_germline_vepanno.vcf ${neoDir}
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perl ${codes_dir}/neoantigen.variant.filter.pl somatic ${tumor} ${name} ${neoDir}/${name}_somatic_vepanno.vcf ${neoDir}
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##step2 phasing variant
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java -jar $GATK MergeVcfs -I ${neoDir}/${name}_somatic_vepanno_filter.vcf -I ${neoDir}/${name}_germline_vepanno_filter.vcf -O ${neoDir}/${name}_combined_somatic_plus_germline.vcf
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java -Xmx16g -jar $PICARD SortVcf \
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I=${neoDir}/${name}_combined_somatic_plus_germline.vcf \
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O=${neoDir}/${name}_combined_somatic_plus_germline.sorted.vcf \
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SEQUENCE_DICTIONARY=/dataseq/jmdna/database/genome/hg19/hg19.dict
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java -Xmx16g -jar /dataseq/jmdna/software/GenomeAnalysisTK.3.7.jar \
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-T ReadBackedPhasing \
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-R ${ref} \
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-I $outputDir/alignment/${tumor}.rmdup.bam \
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--variant ${neoDir}/${name}_combined_somatic_plus_germline.sorted.vcf \
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-L ${neoDir}/${name}_combined_somatic_plus_germline.sorted.vcf \
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--cacheWindowSize 90 \
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-o ${neoDir}/${name}.phased.vcf
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##step3:bgzip and index the VCF
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bgzip -c ${neoDir}/${name}.phased.vcf > ${neoDir}/${name}.phased.vcf.gz
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tabix -p vcf ${neoDir}/${name}.phased.vcf.gz
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bgzip -c ${neoDir}/${name}_somatic_vepanno_filter.vcf > ${neoDir}/${name}_somatic_vepanno_filter.vcf.gz
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tabix -p vcf ${neoDir}/${name}_somatic_vepanno_filter.vcf.gz
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HLA=`head -n 2 ${neoDir}/HLA/*tsv | tail -n 1 | awk '{OFS=","}{print "HLA-"$2,"HLA-"$3,"HLA-"$4,"HLA-"$5,"HLA-"$6,"HLA-"$7}'|xargs echo -n`
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#IEDB recommed NetMHCpan. but NetMHCcons is also outperformed(PMID: 31204427)
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#8,9,10,11
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docker run --rm -u $UID:1012 -v ${neoDir}:/data griffithlab/pvactools:2.0.7 pvacseq run \
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-e1 9,10,11 \
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--iedb-install-directory /opt/iedb/ \
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-t 10 \
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-k \
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--normal-sample-name NORMAL \
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-p /data/${name}.phased.vcf.gz \
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/data/${name}_somatic_vepanno_filter.vcf.gz \
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${tumor} \
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$HLA \
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NetMHCpan \
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/data
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#--netmhc-stab
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#--net-chop-method cterm \
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#--net-chop-threshold 0 \
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#--pass-only \
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`dos2unix ${neoDir}/MHC_Class_I/*.all_epitopes.tsv`
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perl ${codes_dir}/netchop.pl $outputDir $name $tumor $max_peptide_length
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