263 lines
9.0 KiB
Plaintext
263 lines
9.0 KiB
Plaintext
task mutation_calling_umi {
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String name
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String output_dir
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String rmdup_bam
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String ref
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String bed
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command <<<
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if [ ! -d ${output_dir}/mutation ];then
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mkdir ${output_dir}/mutation
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fi
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#1条call
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# 这个情况是reads数目只有1，但是如果去掉了这个reads数导致数据量减少很多
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# -r 3 是指有3条这样样的reads支撑
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# -f 是指频率 以2条方式的call出来的变异频率可以比1条的方式更可信
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
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-G ${ref} \
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-f 0.001 \
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-N ${name} \
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-b ${rmdup_bam} \
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-UN -Q 20 -m 3 -r 3 -th 10 -c 1 -S 2 -E 3 -g 4 ${bed} \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl \
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-N ${name} -E -f 0.001 > ${output_dir}/mutation/${name}.1r.snp.indel.vcf
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#提取>=2条矫正的序列
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func_fetch_bam.py ${output_dir}/alignment/${name}.rmdup.bam ${output_dir}/alignment/${name}.2r.rmdup.bam
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samtools index ${output_dir}/alignment/${name}.2r.rmdup.bam
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# 保证 1r call mut umi family 里面有2条reads
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#2条矫正的call
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar -G ${ref} \
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-f 0.0001 -N ${name}_2r -b ${output_dir}/alignment/${name}.2r.rmdup.bam \
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-UN -Q 20 -m 3 -r 1 -th 10 -c 1 -S 2 -E 3 -g 4 ${bed} | /dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.001 >${output_dir}/mutation/${name}.2r.snp.indel.vcf
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#merge突变，以1条方式call的>0.01的突变+两条方式的对一条方式的低频区域（AF<0.01）进行矫正。
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filter_snpindel_umi_1r_plus_2r.pl \
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${output_dir}/mutation/${name}.1r.snp.indel.vcf \
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${output_dir}/mutation/${name}.2r.snp.indel.vcf \
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${output_dir}/mutation/${name}.snp.indel.vcf
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>>>
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output {
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String vcf = "${output_dir}/mutation/${name}.snp.indel.vcf"
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}
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}
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task mutation_calling_tissue {
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String name
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String bed
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String ref
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String output_dir
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String rmdup_bam
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command <<<
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if [ ! -d ${output_dir}/mutation ];then
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mkdir ${output_dir}/mutation
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fi
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# vardict
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
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-G ${ref} \
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-f 0.01 \
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-N ${name} \
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-b ${rmdup_bam} \
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-UN \
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-Q 20 \
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-m 3 \
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-r 3 \
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-th 10 \
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-c 1 -S 2 -E 3 -g 4 ${bed} |/dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
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|/dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.01 >${output_dir}/mutation/${name}.snp.indel.vcf
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>>>
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output {
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String vcf = "${output_dir}/mutation/${name}.snp.indel.vcf"
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}
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}
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task mutation_calling_tissue_control {
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String name
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String bed
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String ref
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String output_dir
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String tumor_rmdup_bam
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String normal_rmdup_bam
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command <<<
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if [ ! -d ${output_dir}/mutation ];then
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mkdir ${output_dir}/mutation
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fi
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
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-G ${ref} \
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-f 0.01 \
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-N ${name} \
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-b "${tumor_rmdup_bam}|${normal_rmdup_bam}" \
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-UN \
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-Q 20 \
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-m 3 \
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-r 3 \
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-th 20 -c 1 -S 2 -E 3 -g 4 ${bed} | /dataseq/jmdna/software/VarDict-1.8.3/bin/testsomatic.R \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_paired.pl -N ${name} -f 0.01 > ${output_dir}/mutation/${name}.snp.indel.vcf
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python ~/project/pipeline/workflow/script/tools/genome_3rule.py ${name}.snp.indel.vcf ${name}.snp.indel.norm.vcf ${ref}
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python ~/project/pipeline/workflow/script/tools/vcf_filter.py -i ${name}.snp.indel.vcf \
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-o ${name}.snp.indel.germline.vcf \
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-e 'INFO/STATUS="Germline"'
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python ~/project/pipeline/workflow/script/tools/vcf_filter.py -i ${name}.snp.indel.vcf \
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-o ${name}.snp.indel.somatic.vcf \
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-e 'INFO/STATUS="StrongSomatic" | ( INFO/STATUS="LikelySomatic" && FORMAT/AF[0] > 3*FORMAT/AF[1] )'
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>>>
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output {
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String vcf = "${output_dir}/mutation/${name}.snp.indel.vcf"
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}
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}
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task mutation_calling_umi_control {
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String name
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String bed
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String ref
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String output_dir
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String tumor_rmdup_bam
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String normal_rmdup_bam
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command <<<
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if [ ! -d ${output_dir}/mutation ];then
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mkdir ${output_dir}/mutation
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fi
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# 对照样本
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
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-G ${ref} \
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-f 0.01 \
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-N ${name} \
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-b ${normal_rmdup_bam} \
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-UN \
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-Q 20 \
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-m 3 \
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-r 3 \
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-th 10 \
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-c 1 -S 2 -E 3 -g 4 ${bed} |/dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
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|/dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.01 >${output_dir}/mutation/${name}_normal.snp.indel.vcf
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# 实验样本
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
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-G ${ref} \
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-f 0.001 \
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-N ${name} \
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-b ${tumor_rmdup_bam} \
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-UN -Q 20 -m 3 -r 3 -th 10 -c 1 -S 2 -E 3 -g 4 ${bed} \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl \
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-N ${name} -E -f 0.001 > ${output_dir}/mutation/${name}.1r.snp.indel.vcf
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#提取>=2条矫正的序列
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func_fetch_bam.py ${output_dir}/alignment/${name}.rmdup.bam ${output_dir}/alignment/${name}.2r.rmdup.bam
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samtools index ${output_dir}/alignment/${name}.2r.rmdup.bam
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# 保证 1r call mut umi family 里面有2条reads
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#2条矫正的call
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java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar -G ${ref} \
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-f 0.0001 -N ${name}_2r -b ${output_dir}/alignment/${name}.2r.rmdup.bam \
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-UN -Q 20 -m 3 -r 1 -th 10 -c 1 -S 2 -E 3 -g 4 ${bed} | /dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
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| /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.001 >${output_dir}/mutation/${name}.2r.snp.indel.vcf
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# merge突变，以1条方式call的>0.01的突变+两条方式的对一条方式的低频区域（AF<0.01）进行矫正。
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filter_snpindel_umi_1r_plus_2r.pl \
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${output_dir}/mutation/${name}.1r.snp.indel.vcf \
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${output_dir}/mutation/${name}.2r.snp.indel.vcf \
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${output_dir}/mutation/${name}_tumor.snp.indel.vcf
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# 去除normal 中的突变位点
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filter_snpindel_umi_subnormal.pl \
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${output_dir}/mutation/${name}_tumor.snp.indel.vcf \
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${output_dir}/mutation/${name}_normal.snp.indel.vcf \
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${output_dir}/mutation/${name}.snp.indel.somatic.vcf
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cp ${output_dir}/mutation/${name}_normal.snp.indel.vcf ${output_dir}/mutation/${name}.snp.indel.germline.vcf
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>>>
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output {
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String vcf = "${output_dir}/mutation/${name}.snp.indel.vcf"
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}
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}
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workflow call_mutation {
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String tumor
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String tumor_rmdup_bam
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String? normal
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String? normal_rmdup_bam
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Boolean umi
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String output_dir
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String ref
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String bed
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# 双样本
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if (defined(normal)) {
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if (umi) {
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call mutation_calling_umi_control {
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input:
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name=tumor,
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output_dir=output_dir,
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ref=ref,
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bed=bed,
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tumor_rmdup_bam=tumor_rmdup_bam,
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normal_rmdup_bam=normal_rmdup_bam
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}
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}
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if (!umi) {
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call mutation_calling_tissue_control {
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input:
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name=tumor,
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output_dir=output_dir,
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ref=ref,
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bed=bed,
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tumor_rmdup_bam=tumor_rmdup_bam,
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normal_rmdup_bam=normal_rmdup_bam
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}
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}
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}
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# 单样本
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if (!defined(normal)) {
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if (umi) {
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call mutation_calling_umi {
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input:
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name=tumor,
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output_dir=output_dir,
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ref=ref,
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bed=bed,
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rmdup_bam=tumor_rmdup_bam
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}
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}
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if (!umi) {
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call mutation_calling_tissue {
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input:
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name=tumor,
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output_dir=output_dir,
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ref=ref,
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bed=bed,
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rmdup_bam=normal_rmdup_bam
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}
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}
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}
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output {
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String somatic_vcf = "${output_dir}/mutation/${tumor}.snp.indel.vcf"
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}
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} |