pipeline/wdl/call_mutation.wdl

# mutation

task mutation_calling_umi {
    String name
    String output_dir
    String rmdup_bam
    String ref
    String bed
    String probe
    command <<<

        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        #1条call
        # 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
        # -r 3 是指有3条这样样的reads支撑
        # -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
        # hotspot 修改了 -r 3 为 -r 2  -f 0.001 为 -f 0.0005

        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
        -G ${ref} \
        -f 0.0005 \
        -N ${name} \
        -b ${rmdup_bam} \
        -UN -Q 20 -m 3 -r 2 -th 10 -z 1 -c 1 -S 2 -E 3 -g 4 ${bed} \
        |/dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
        | /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl \
        -N ${name} -E -f 0.0005 -F 0.1 > ${output_dir}/mutation/${name}.1r.vcf

        #提取>=2条矫正的序列
        bam_fetch.py ${output_dir}/alignment/${name}.rmdup.bam ${output_dir}/alignment/${name}.2r.rmdup.bam
        samtools index ${output_dir}/alignment/${name}.2r.rmdup.bam

        # 保证 1r call mut umi family 里面有2条reads
        #2条矫正的call
        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
        -G ${ref} \
        -f 0.0001 \
        -N ${name}_2r \
        -b ${output_dir}/alignment/${name}.2r.rmdup.bam \
        -UN -Q 20 -m 3 -r 1 -th 10 -z 1 -c 1 -S 2 -E 3 -g 4 ${bed} \
        |/dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
        |/dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.0001 -F 0.1 >${output_dir}/mutation/${name}.2r.vcf

        # 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。
        correct_umi_1r_plus_2r.pl \
        ${output_dir}/mutation/${name}.1r.vcf \
        ${output_dir}/mutation/${name}.2r.vcf \
        ${output_dir}/mutation/${name}.raw.vcf

        vcf_filter.py \
        -i ${output_dir}/mutation/${name}.raw.vcf \
        -e 'INFO/AF[0] >= 0.001 && INFO/VD >= 3' \
        -o ${output_dir}/mutation/${name}.raw.snp_indel.vcf

        # add msi and strandbias flag
        vcf_add_tag_msi.pl ${output_dir}/mutation/${name}.raw.snp_indel.vcf ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf ${probe} c

        # add malt flag
        grep -v ^# ${output_dir}/mutation/${name}.raw.snp_indel.vcf | awk '{OFS="\t"}{print $1,$2-1,$2}' - > \
        ${output_dir}/mutation/${name}.raw.snp_indel.vcf.bed
        samtools mpileup -aBq 20 -Q 20 -f ${ref} -l ${output_dir}/mutation/${name}.raw.snp_indel.vcf.bed \
        ${output_dir}/alignment/${name}.2r.rmdup.bam -o ${output_dir}/mutation/${name}.raw.snp_indel.vcf.pileup

        vcf_add_tag_mutalt.py ${output_dir}/mutation/${name}.raw.snp_indel.vcf.pileup \
        ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf \
        ${output_dir}/mutation/${name}.raw.addtagmsi.addmutalt.snp_indel.vcf

        cp ${output_dir}/mutation/${name}.raw.addtagmsi.addmutalt.snp_indel.vcf ${output_dir}/mutation/${name}.snp_indel.somatic.vcf

        vcf_filter.py \
        -i ${output_dir}/mutation/${name}.raw.snp_indel.vcf \
        -e 'INFO/AF[0] >= 0.1' \
        -o ${output_dir}/mutation/${name}.snp_indel.germline.vcf

    >>>

    output {
        String somatic_vcf = "${output_dir}/mutation/${name}.snp_indel.somatic.vcf"
        String germline_vcf = "${output_dir}/mutation/${name}.snp_indel.germline.vcf"
        String raw_vcf = "${output_dir}/mutation/${name}.1r.vcf"
    }
}

task mutation_calling_umi_control {
    String name
    String bed
    String ref
    String output_dir
    String tumor_rmdup_bam
    String normal_rmdup_bam
    String probe

    command <<<
        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        # 对照样本
        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
        -G ${ref} \
        -f 0.01 \
        -N ${name} \
        -b ${normal_rmdup_bam} \
        -UN \
        -Q 20 \
        -m 3 \
        -r 3 \
        -th 10 \
        -c 1 -S 2 -E 3 -g 4 ${bed} |/dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
        |/dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.01 -F 0.1 >${output_dir}/mutation/${name}.normal.vcf

        # 实验样本
        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
        -G ${ref} \
        -f 0.0005 \
        -N ${name} \
        -b ${tumor_rmdup_bam} \
        -UN -Q 20 -m 3 -r 2 -th 10 -c 1 -S 2 -E 3 -g 4 ${bed} \
        | /dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
        | /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl \
        -N ${name} -E -f 0.0005 -F 0.1 > ${output_dir}/mutation/${name}.1r.vcf

        #提取>=2条矫正的序列
        bam_fetch.py ${output_dir}/alignment/${name}.rmdup.bam ${output_dir}/alignment/${name}.2r.rmdup.bam
        samtools index ${output_dir}/alignment/${name}.2r.rmdup.bam

        # 保证 1r call mut umi family 里面有2条reads
        #2条矫正的call
        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar -G ${ref} \
        -f 0.0001 -N ${name}_2r -b ${output_dir}/alignment/${name}.2r.rmdup.bam \
        -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 \
        | /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.0001 -F 0.1 >${output_dir}/mutation/${name}.2r.vcf

        # 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。
        correct_umi_1r_plus_2r.pl \
        ${output_dir}/mutation/${name}.1r.vcf \
        ${output_dir}/mutation/${name}.2r.vcf \
        ${output_dir}/mutation/${name}.pre_raw.vcf

        # 去除normal 中的突变位点
        correct_umi_subnormal.pl  \
        ${output_dir}/mutation/${name}.pre_raw.vcf \
        ${output_dir}/mutation/${name}.normal.vcf \
        ${output_dir}/mutation/${name}.raw.vcf

        vcf_filter.py \
        -i ${output_dir}/mutation/${name}.raw.vcf \
        -e 'INFO/AF[0] >= 0.001 && INFO/VD >= 3' \
        -o ${output_dir}/mutation/${name}.raw.snp_indel.vcf

        # add msi and strandbias flag
        vcf_add_tag_msi.pl ${output_dir}/mutation/${name}.raw.snp_indel.vcf ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf ${probe} c

        # add malt flag
        grep -v ^# ${output_dir}/mutation/${name}.raw.snp_indel.vcf | awk '{OFS="\t"}{print $1,$2-1,$2}' - > \
        ${output_dir}/mutation/${name}.raw.snp_indel.vcf.bed
        samtools mpileup -aBq 20 -Q 20 -f ${ref} -l ${output_dir}/mutation/${name}.raw.snp_indel.vcf.bed \
        ${output_dir}/alignment/${name}.2r.rmdup.bam -o ${output_dir}/mutation/${name}.raw.snp_indel.vcf.pileup

        vcf_add_tag_mutalt.py ${output_dir}/mutation/${name}.raw.snp_indel.vcf.pileup \
        ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf \
        ${output_dir}/mutation/${name}.raw.addtagmsi.addmutalt.snp_indel.vcf

        cp ${output_dir}/mutation/${name}.raw.addtagmsi.addmutalt.snp_indel.vcf ${output_dir}/mutation/${name}.snp_indel.somatic.vcf
        cp ${output_dir}/mutation/${name}.normal.vcf ${output_dir}/mutation/${name}.snp_indel.germline.vcf

    >>>

    output {
        String somatic_vcf = "${output_dir}/mutation/${name}.snp_indel.somatic.vcf"
        String germline_vcf = "${output_dir}/mutation/${name}.snp_indel.germline.vcf"
        String raw_vcf = "${output_dir}/mutation/${name}.1r.vcf"
    }
}

task mutation_calling_tissue {
    String name
    String bed
    String ref
    String output_dir
    String rmdup_bam
    String probe

    command <<<
        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        # vardict
        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
        -G ${ref} \
        -f 0.005 \
        -N ${name} \
        -b ${rmdup_bam} \
        -UN \
        -Q 20 \
        -m 3 \
        -r 2 \
        -z 1 \
        -th 10 \
        -c 1 -S 2 -E 3 -g 4 ${bed} \
        |/dataseq/jmdna/software/VarDict-1.8.3/bin/teststrandbias.R \
        |/dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_valid.pl -N ${name} -E -f 0.005 -F 0.1 \
        >${output_dir}/mutation/${name}.raw.vcf

        vcf_filter.py \
        -i ${output_dir}/mutation/${name}.raw.vcf \
        -e 'INFO/AF[0] >= 0.01 && INFO/VD >= 3' \
        -o ${output_dir}/mutation/${name}.raw.snp_indel.vcf

        # add msi and strandbias flag
        vcf_add_tag_msi.pl ${output_dir}/mutation/${name}.raw.snp_indel.vcf ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf ${probe} t

        cp ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf ${output_dir}/mutation/${name}.snp_indel.somatic.vcf

        vcf_filter.py \
        -i ${output_dir}/mutation/${name}.raw.snp_indel.vcf \
        -e 'INFO/AF[0] > 0.1' \
        -o ${output_dir}/mutation/${name}.snp_indel.germline.vcf

    >>>

    output {
        String somatic_vcf = "${output_dir}/mutation/${name}.snp_indel.somatic.vcf"
        String germline_vcf = "${output_dir}/mutation/${name}.snp_indel.germline.vcf"
        String raw_vcf = "${output_dir}/mutation/${name}.raw.vcf"
    }
}

task mutation_calling_tissue_control {
    String name
    String bed
    String ref
    String output_dir
    String tumor_rmdup_bam
    String normal_rmdup_bam
    String probe

    command <<<
        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        java -jar /dataseq/jmdna/software/VarDict-1.8.3/lib/VarDict-1.8.3.jar \
        -G ${ref} \
        -f 0.005 \
        -N ${name} \
        -b "${tumor_rmdup_bam}|${normal_rmdup_bam}" \
        -UN \
        -Q 20 \
        -m 3 \
        -r 2 \
        -th 20 \
        -z 1 -c 1 -S 2 -E 3 -g 4 ${bed} | /dataseq/jmdna/software/VarDict-1.8.3/bin/testsomatic.R \
        | /dataseq/jmdna/software/VarDict-1.8.3/bin/var2vcf_paired.pl -N ${name} -f 0.005 -F 0.1 \
        >${output_dir}/mutation/${name}.raw.vcf

        vcf_filter.py \
        -i ${output_dir}/mutation/${name}.raw.vcf \
        -e 'INFO/AF[0] >= 0.01 && INFO/VD >= 3' \
        -o ${output_dir}/mutation/${name}.raw.snp_indel.vcf

        # add msi and strandbias flag
        vcf_add_tag_msi.pl ${output_dir}/mutation/${name}.raw.snp_indel.vcf ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf ${probe} t

        vcf_filter.py -i ${output_dir}/mutation/${name}.raw.addtagmsi.snp_indel.vcf \
        -o ${output_dir}/mutation/${name}.snp_indel.somatic.vcf \
        -e 'INFO/STATUS="StrongSomatic" | ( INFO/STATUS="LikelySomatic" && FORMAT/AF[0] > 3*FORMAT/AF[1] )'

        vcf_filter.py -i ${output_dir}/mutation/${name}.raw.snp_indel.vcf \
        -o ${output_dir}/mutation/${name}.snp_indel.germline.vcf \
        -e 'INFO/STATUS="Germline" && FORMAT/AF[0] > 0.1 && FORMAT/AF[1] > 0.1'

    >>>

    output {
        String somatic_vcf = "${output_dir}/mutation/${name}.snp_indel.somatic.vcf"
        String germline_vcf = "${output_dir}/mutation/${name}.snp_indel.germline.vcf"
        String raw_vcf = "${output_dir}/mutation/${name}.raw.vcf"
    }
}

task hotspot {
    String name
    String output_dir
    String raw_vcf
    Float threshold

    command <<<
        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        # hotspot
#        vcf_filter.py \
#        -i ${raw_vcf} \
#        -e 'INFO/AF[0] < ${threshold}' \
#        -o ${output_dir}/mutation/${name}.raw.hotspot.vcf

#        vcf_operations.py ${output_dir}/mutation/${name}.raw.hotspot.vcf \
#        -b $PUBLIC/hotspot/hotspot_delins.bed \
#        -o ${output_dir}/mutation/${name}.raw.hotspot.delins.vcf

        vcf_operations.py ${raw_vcf} \
        -b $PUBLIC/hotspot/hotspot_delins.bed \
        -o ${output_dir}/mutation/${name}.raw.hotspot.delins.vcf

        vcf_operations.py ${raw_vcf} \
        -b $PUBLIC/hotspot/hotspot_snpindel.bed \
        -o ${output_dir}/mutation/${name}.raw.hotspot.snpindel.vcf \
        -s

        vcf_operations.py ${raw_vcf} \
        -v $PUBLIC/hotspot/hotspot_snv.vcf \
        -o ${output_dir}/mutation/${name}.raw.hotspot.snv.vcf

        vcf_operations.py ${output_dir}/mutation/${name}.raw.hotspot.snv.vcf \
        -v ${output_dir}/mutation/${name}.raw.hotspot.delins.vcf \
        -o ${output_dir}/mutation/${name}.raw.hotspot.snv_delins.vcf \
        -m

        vcf_operations.py ${output_dir}/mutation/${name}.raw.hotspot.snv_delins.vcf \
        -v ${output_dir}/mutation/${name}.raw.hotspot.snpindel.vcf \
        -o ${output_dir}/mutation/${name}.hotspot.vcf \
        -m

    >>>

    output {
        String hotspot_vcf = "${output_dir}/mutation/${name}.hotspot.vcf"
    }
}

task annovar {
    String prefix
    String output_dir
    String ref
    String vcf

    command <<<

        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        # 有突变记录的进行注释
        if grep -E -q "^[^#]" ${vcf}; then

        table_annovar.pl \
        ${vcf} \
        /dataseq/jmdna/software/annovar/humandb/ \
        -buildver hg19 -nastring . -vcfinput -remove -otherinfo \
        -protocol refGene,avsnp150,cosmic91,clinvar_20220320,1000g2015aug_all,1000g2015aug_eas,esp6500siv2_all,exac03nontcga,gnomad_genome,dbnsfp35c,cytoBand \
        -argument '-splicing_threshold 2 -hgvs ',,,,,,,,,, \
        -intronhgvs 50 \
        -operation g,f,f,f,f,f,f,f,f,f,r \
        -outfile ${output_dir}/mutation/${prefix} \
        -dot2underline

        else

        # 无突变记录创建文件
        touch ${output_dir}/mutation/${prefix}.hg19_multianno.txt ${output_dir}/mutation/${prefix}.hg19_multianno.vcf
        fi

    >>>
    output {
        String anno_txt = "${output_dir}/mutation/${prefix}.hg19_multianno.txt"
        String anno_vcf = "${output_dir}/mutation/${prefix}.hg19_multianno.txt"
    }
}

task filter_umi {
    String name
    String file
    String project
    String sample_type
    String pipeline
    String output_dir
    String tumor_rmdup_bam

    command <<<

        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        filter_snpindel.pl \
        ${file} \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter_pre.txt \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.tag.txt \
        ${project} \
        ${sample_type} \
        ${pipeline}

        if [ "${pipeline}"  = 'hotspot' ] ;then
        cp ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter_pre.txt \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter.txt
        else
        correct_umi_overlap_reads.py \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter_pre.txt \
        ${tumor_rmdup_bam} \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter.txt
        fi

    >>>
    output {
        String snvindel_filtered= "${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter.txt"
    }
}

task filter_tissue {
    String name
    String file
    String project
    String sample_type
    String pipeline
    String output_dir

    command <<<

        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        filter_snpindel.pl \
        ${file} \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter.txt \
        ${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.tag.txt \
        ${project} \
        ${sample_type} \
        ${pipeline}

    >>>
    output {
        String snvindel_filtered= "${output_dir}/mutation/${name}.snp_indel.${pipeline}.hg19_multianno.filter.txt"
    }
}

task mutation_sum {
    String name
    String somatic_txt
    String germline_txt
    String hotspot_txt
    String output_dir
    String cancer

    command <<<

        if [ ! -d ${output_dir}/mutation ];then
        mkdir ${output_dir}/mutation
        fi

        { head -n 1 ${somatic_txt} ; tail -n +2 ${somatic_txt} ; tail -n +2 ${hotspot_txt} ;} |\
        { head -n 1 ; awk -F '\t' '{$1 = 1; OFS="\t" ; key=""; for (i=3; i<=7; i++) { key = key $i "," } \
        if (key in data) { data[key] = data[key] ";" $NF; } \
        else { data[key] = $0; }} END { for (i in data) { print data[i]; } }' ; } > \
        ${output_dir}/mutation/${name}.snp_indel.somatic.hg19_multianno.filter.sum.txt

        target_therapy_snpindel.pl ${output_dir}/mutation/${name}.snp_indel.somatic.hg19_multianno.filter.sum.txt \
        ${output_dir}/mutation/${name}.snp_indel.somatic.hg19_multianno.filter.sum ${cancer}

    >>>
    output {
        String snvindel_filtered_sum = "${output_dir}/mutation/${name}.snp_indel.somatic.hg19_multianno.filter.sum.txt"
    }
}

workflow call_mutation {

    Boolean run=true

    String tumor
    String tumor_rmdup_bam
    String? normal
    String? normal_rmdup_bam
    Boolean umi
    String output_dir
    String ref
    String bed
    String project
    String cancer
    String probe

    # pipe 执行 mutation_calling => annovar => filter
    if (run) {
        # 单样本
        if (!defined(normal)) {
            if (umi) {
                call mutation_calling_umi {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        ref=ref,
                        bed=bed,
                        rmdup_bam=tumor_rmdup_bam,
                        probe=probe
                }
                call hotspot as hotspot_calling_umi {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        raw_vcf=mutation_calling_umi.raw_vcf,
                        threshold=0.1
                }
                call annovar as anno_somatic_umi {
                    input:
                        prefix="${tumor}.snp_indel.somatic",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_umi.somatic_vcf
                }
                call annovar as anno_germline_umi {
                    input:
                        prefix="${tumor}.snp_indel.germline",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_umi.germline_vcf
                }
                call annovar as anno_hotspot_umi {
                    input:
                        prefix="${tumor}.hotspot",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=hotspot_calling_umi.hotspot_vcf
                }
                call filter_umi as filter_somatic_umi {
                    input:
                        name=tumor,
                        file=anno_somatic_umi.anno_txt,
                        project=project,
                        sample_type='c',
                        pipeline='somatic',
                        output_dir=output_dir,
                        tumor_rmdup_bam = tumor_rmdup_bam

                }
                call filter_umi as filter_hotspot_umi {
                    input:
                        name=tumor,
                        file=anno_hotspot_umi.anno_txt,
                        project=project,
                        sample_type='c',
                        pipeline='hotspot',
                        output_dir=output_dir,
                        tumor_rmdup_bam = tumor_rmdup_bam

                }
                call filter_umi as filter_germline_umi {
                    input:
                        name=tumor,
                        file=anno_germline_umi.anno_txt,
                        project=project,
                        sample_type='c',
                        pipeline='germline',
                        output_dir=output_dir,
                        tumor_rmdup_bam = tumor_rmdup_bam
                }
                call mutation_sum as mutation_sum_umi {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        somatic_txt=filter_somatic_umi.snvindel_filtered,
                        germline_txt=filter_germline_umi.snvindel_filtered,
                        hotspot_txt=filter_hotspot_umi.snvindel_filtered,
                        cancer=cancer
                }

            }

            if (!umi) {
                call mutation_calling_tissue {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        ref=ref,
                        bed=bed,
                        rmdup_bam=tumor_rmdup_bam,
                        probe=probe
                }
                call hotspot as hotspot_calling_tissue {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        raw_vcf=mutation_calling_tissue.raw_vcf,
                        threshold=0.1
                }
                call annovar as anno_somatic_tissue {
                    input:
                        prefix="${tumor}.snp_indel.somatic",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_tissue.somatic_vcf
                }
                call annovar as anno_germline_tissue {
                    input:
                        prefix="${tumor}.snp_indel.germline",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_tissue.germline_vcf
                }
                call annovar as anno_hotspot_tissue {
                    input:
                        prefix="${tumor}.hotspot",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=hotspot_calling_tissue.hotspot_vcf
                }
                call filter_tissue as filter_somatic_tissue {
                    input:
                        name=tumor,
                        file=anno_somatic_tissue.anno_txt,
                        project=project,
                        sample_type='t',
                        pipeline='somatic',
                        output_dir=output_dir,

                }
                call filter_tissue as filter_hotspot_tissue {
                    input:
                        name=tumor,
                        file=anno_hotspot_tissue.anno_txt,
                        project=project,
                        sample_type='t',
                        pipeline='hotspot',
                        output_dir=output_dir,

                }
                call filter_tissue as filter_germline_tissue {
                    input:
                        name=tumor,
                        file=anno_germline_tissue.anno_txt,
                        project=project,
                        sample_type='t',
                        pipeline='germline',
                        output_dir=output_dir,
                }
                call mutation_sum as mutation_sum_tissue {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        somatic_txt=filter_somatic_tissue.snvindel_filtered,
                        germline_txt=filter_germline_tissue.snvindel_filtered,
                        hotspot_txt=filter_hotspot_tissue.snvindel_filtered,
                        cancer=cancer
                }
            }
        }
        # 双样本
        if (defined(normal)) {
            if (umi) {
                call mutation_calling_umi_control {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        ref=ref,
                        bed=bed,
                        tumor_rmdup_bam=tumor_rmdup_bam,
                        normal_rmdup_bam=normal_rmdup_bam,
                        probe=probe

                }
                call hotspot as hotspot_calling_umi_control {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        raw_vcf=mutation_calling_umi_control.raw_vcf,
                        threshold=0.1
                }
                call annovar as anno_somatic_umi_control {
                    input:
                        prefix="${tumor}.snp_indel.somatic",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_umi_control.somatic_vcf
                }
                call annovar as anno_germline_umi_control {
                    input:
                        prefix="${tumor}.snp_indel.germline",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_umi_control.germline_vcf
                }
                call annovar as anno_hotspot_umi_control {
                    input:
                        prefix="${tumor}.hotspot",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=hotspot_calling_umi_control.hotspot_vcf
                }
                call filter_umi as filter_somatic_umi_control {
                    input:
                        name=tumor,
                        file=anno_somatic_umi_control.anno_txt,
                        project=project,
                        sample_type='c',
                        pipeline='somatic',
                        output_dir=output_dir,
                        tumor_rmdup_bam = tumor_rmdup_bam

                }
                call filter_umi as filter_hotspot_umi_control {
                    input:
                        name=tumor,
                        file=anno_hotspot_umi_control.anno_txt,
                        project=project,
                        sample_type='c',
                        pipeline='hotspot',
                        output_dir=output_dir,
                        tumor_rmdup_bam = tumor_rmdup_bam

                }
                call filter_umi as filter_germline_umi_control {
                    input:
                        name=tumor,
                        file=anno_germline_umi_control.anno_txt,
                        project=project,
                        sample_type='c',
                        pipeline='germline',
                        output_dir=output_dir,
                        tumor_rmdup_bam = tumor_rmdup_bam
                }
                call mutation_sum as mutation_sum_umi_control {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        somatic_txt=filter_somatic_umi_control.snvindel_filtered,
                        germline_txt=filter_germline_umi_control.snvindel_filtered,
                        hotspot_txt=filter_hotspot_umi_control.snvindel_filtered,
                        cancer=cancer
                }
            }

            if (!umi) {
                call mutation_calling_tissue_control {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        ref=ref,
                        bed=bed,
                        tumor_rmdup_bam=tumor_rmdup_bam,
                        normal_rmdup_bam=normal_rmdup_bam,
                        probe=probe

                }
                call hotspot as hotspot_calling_tissue_control {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        raw_vcf=mutation_calling_tissue_control.raw_vcf,
                        threshold=0.1
                }
                call annovar as anno_somatic_tissue_control {
                    input:
                        prefix="${tumor}.snp_indel.somatic",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_tissue_control.somatic_vcf
                }
                call annovar as anno_germline_tissue_control {
                    input:
                        prefix="${tumor}.snp_indel.germline",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=mutation_calling_tissue_control.germline_vcf
                }
                call annovar as anno_hotspot_tissue_control {
                    input:
                        prefix="${tumor}.hotspot",
                        output_dir=output_dir,
                        ref=ref,
                        vcf=hotspot_calling_tissue_control.hotspot_vcf
                }
                call filter_tissue as filter_somatic_tissue_control {
                    input:
                        name=tumor,
                        file=anno_somatic_tissue_control.anno_txt,
                        project=project,
                        sample_type='t',
                        pipeline='somatic',
                        output_dir=output_dir,
                }
                call filter_tissue as filter_hotspot_tissue_control {
                    input:
                        name=tumor,
                        file=anno_hotspot_tissue_control.anno_txt,
                        project=project,
                        sample_type='t',
                        pipeline='hotspot',
                        output_dir=output_dir,

                }
                call filter_tissue as filter_germline_tissue_control {
                    input:
                        name=tumor,
                        file=anno_germline_tissue_control.anno_txt,
                        project=project,
                        sample_type='t',
                        pipeline='germline',
                        output_dir=output_dir,
                }
                call mutation_sum as mutation_sum_tissue_control {
                    input:
                        name=tumor,
                        output_dir=output_dir,
                        somatic_txt=filter_somatic_tissue_control.snvindel_filtered,
                        germline_txt=filter_germline_tissue_control.snvindel_filtered,
                        hotspot_txt=filter_hotspot_tissue_control.snvindel_filtered,
                        cancer=cancer
                }
            }
        }
    }

    output {
        String raw_vcf = "${output_dir}/mutation/${tumor}.raw.snp_indel.vcf"
        String somatic_vcf = "${output_dir}/mutation/${tumor}.snp_indel.somatic.vcf"
        String germline_vcf = "${output_dir}/mutation/${tumor}.snp_indel.germline.vcf"
        String hotspot_vcf = "${output_dir}/mutation/${tumor}.hotspot.vcf"
        String somatic_anno_txt = "${output_dir}/mutation/${tumor}.snp_indel.somatic.hg19_multianno.txt"
        String somatic_filter = "${output_dir}/mutation/${tumor}.snp_indel.somatic.hg19_multianno.filter.txt"
        String germline_filter = "${output_dir}/mutation/${tumor}.snp_indel.germline.hg19_multianno.filter.txt"
        String hotspot_filter = "${output_dir}/mutation/${tumor}.snp_indel.hotspot.hg19_multianno.filter.txt"
    }
}