CNV-- Structural Variants pipeline

public public 1yr ago Version: 1.1.3 0 bookmarks
View Workflow
Report
cnv_pipeline
cnv_pipeline
cnv_pipeline
cnv_pipeline
cnv_pipeline
View Workflow

StructuralVariants Workflow

A CNV (Copy Number Variation) pipeline is a set of bioinformatics tools and algorithms used to detect and analyze genomic variations in the number of copies of DNA segments between individuals or populations.

Code Snippets

20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
baseCommand: [Rscript]

inputs:
  input:
    type: 'File[]'
    inputBinding:
      position: 2
      itemSeparator: ','
  samples:
    type: File
    inputBinding:
      position: 3
  script:
    type: File
    inputBinding:
      position: 1
    default:
        class: File
        basename: "batch_parser.R"
        contents: |-
          args <- commandArgs(TRUE)

          bamsList <- as.vector(strsplit(args[1], ",")[[1]])
          bamsList <- sapply(strsplit(bamsList, "[/]"), "[[", 3)
          samplesFile <- read.delim(args[2], header = T, sep = " ")

          bams <- data.frame(unlist(bamsList))
          colnames(bams)[1] <- "file"
          samples <- samplesFile

          indx <- sapply(samples$sample_id, grep, bams$file)
          temp_df <- cbind(samples[unlist(indx), , drop = F], bams[unlist(indx), , drop = F])
          temp_df$index_file <- paste(temp_df$file, ".bai", sep = "")
          output <- split(temp_df, temp_df$batch)

          sapply(names(output), function(x)
            write.table(output[[x]], file = paste0("bams_x_batch_", x, ".csv"), sep = ",", row.names = F))
CWL From line 20 of tools/batch_parser.cwl 
19
20
21
22
23
24
25
baseCommand: [bedops, -u]

inputs:
  input:
    type: 'File[]'
    inputBinding:
      position: 1
CWL From line 19 of tools/bedops_union.cwl 
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
baseCommand: []
arguments:
  - position: 0
    shellQuote: false
    valueFrom: >-
      $(inputs.input_amb && inputs.input_ann && inputs.input_bwt && inputs.input_pac && inputs.input_sa ? 'echo bwa' : inputs.generate_bwa_indexes ? 'bwa index' : 'echo bwa')

inputs:
  generate_bwa_indexes:
    type: boolean?
  input_fasta:
    type: File
    inputBinding:
      position: 2
  input_amb:
    type: File?
  input_ann:
    type: File?
  input_bwt:
    type: File?
  input_pac:
    type: File?
  input_sa:
    type: File?
  algoType:
    type: string?
    inputBinding:
      position: 1
      prefix: '-a'
CWL BWA From line 22 of tools/bwa_index.cwl 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
baseCommand: [bwa, mem]

inputs:
  reads:
    type: 'File[]'
    inputBinding:
      position: 3
  reference_genome:
    type: File
    inputBinding:
      position: 2
    secondaryFiles:
      - .fai
      - .amb
      - .ann
      - .bwt
      - .pac
      - .sa
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '-t'
  read_group:
    type: string?
    default: '@RG\tID:SRR709972\tSM:NA06985\tPL:ILLUMINA\tCN:CBRA\tLB:Fragment'
    inputBinding:
      position: 4
      prefix: '-R'
CWL From line 17 of tools/bwa_mem_paired.cwl 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
baseCommand: [bwa, mem]

inputs:
  reads:
    type: File
    inputBinding:
      position: 3
  reference_genome:
    type: File
    inputBinding:
      position: 2
    secondaryFiles:
      - .fai
      - .amb
      - .ann
      - .bwt
      - .pac
      - .sa
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '-t'
  read_group:
    type: string?
    default: '@RG\tID:SRR709972\tSM:NA06985\tPL:ILLUMINA\tCN:CBRA\tLB:Fragment'
    inputBinding:
      position: 4
      prefix: '-R'
CWL From line 17 of tools/bwa_mem_unpaired.cwl 
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
baseCommand: [Rscript]

inputs:
  input:
    type: 'File[]'
    inputBinding:
      position: 2
      itemSeparator: ','
  mapping:
    type: File
    inputBinding:
      position: 3
  bed:
    type: File
    inputBinding:
      position: 4
  script:
    type: File
    inputBinding:
      position: 1
    default:
        class: File
        basename: "CODEX2.R"
        contents: |-
          # load packages
          library(CODEX2)

          # parse arguments
          args <- commandArgs(TRUE)
          args2 <- args[2]

          bamsList <- as.vector(strsplit(args[1], ",")[[1]])
          bamsList <- sapply(strsplit(bamsList, "[/]"), "[[", 3)

          bams <- read.csv(args2, header = TRUE, sep = ",") # mapping file
          bedFile <- args[3]

          # mapping
          dirPath <- dirname(args2)
          bamsMap <- bams[bams$file %in% bamsList,]
          batch <- bamsMap$batch[[1]]
          batchname <- paste0("batch_", batch)

          # set global variables
          bamFile <- as.vector(bamsMap$file)
          bamdir <- file.path(dirPath, bamFile)
          sampname <- sapply(strsplit(bamFile, "[.]"), "[[", 1)

          bambedObj <- getbambed(bamdir = bamdir, bedFile = bedFile, sampname = sampname, projectname = batchname)

          bamdir <- bambedObj$bamdir
          sampname <- bambedObj$sampname
          ref <- bambedObj$ref
          projectname <- bambedObj$projectname

          nsamples <- length(bamFile)

          ##########################################################
          # Getting GC content and mappability
          ##########################################################
          gc <- getgc(ref)
          mapp <- getmapp(ref)

          ##########################################################
          # Getting gene names, needed for targeted sequencing, here generating gene names in silico
          ##########################################################
          gene <- rep(NA, length(ref))
          for (chr in as.matrix(unique(seqnames(ref)))) {
            chr.index <- which(seqnames(ref) == chr)
            gene[chr.index] <- paste0(chr, "_gene_", ceiling(chr.index / 30))
          }
          values(ref) <- cbind(values(ref), DataFrame(gc, mapp, gene))

          ##########################################################
          # Getting depth of coverage
          ##########################################################
          coverageObj <- getcoverage(bambedObj, mapqthres = 20)
          Y <- coverageObj$Y
          write.csv(Y, file = paste0(projectname, "_coverage.csv"), quote = FALSE)
          head(Y[, 1:nsamples])

          ##########################################################
          # Quality control
          ##########################################################
          qcObj <- qc(Y, sampname, ref, cov_thresh = c(20, Inf), length_thresh = c(20, Inf), mapp_thresh = 0.9, gc_thresh = c(20, 80))
          Y_qc <- qcObj$Y_qc
          sampname_qc <- qcObj$sampname_qc
          ref_qc <- qcObj$ref_qc
          qcmat <- qcObj$qcmat
          gc_qc <- ref_qc$gc
          write.table(qcmat, file = paste0(projectname, "_qcmat", ".txt"), sep = "\t", quote = FALSE, row.names = FALSE)

          ##########################################################
          # Estimating library size factor for each sample
          ##########################################################
          Y.nonzero <- Y_qc[apply(Y_qc, 1, function(x) { !any(x == 0) }), ]
          pseudo.sample <- apply(Y.nonzero, 1, function(x) { prod(x) ^ (1 / length(x)) })
          N <- apply(apply(Y.nonzero, 2, function(x) { x / pseudo.sample }), 2, median)
          plot(N, apply(Y, 2, sum), xlab = "Estimated library size factor", ylab = "Total sum of reads")

          ##########################################################
          # Genome-wide normalization using normalize_null
          ##########################################################
          # If there are negative control samples, use normalize_codex2_ns()
          # If there are negative control regions, use normalize_codex2_nr()
          normObj.null <- normalize_null(Y_qc = Y_qc, gc_qc = gc_qc, K = 1:nsamples, N = N)
          Yhat <- normObj.null$Yhat
          AIC <- normObj.null$AIC
          BIC <- normObj.null$BIC
          RSS <- normObj.null$RSS

          ##########################################################
          # Number of latent factors
          ##########################################################
          choiceofK(AIC, BIC, RSS, K = 1:nsamples , filename = "codex2_null_choiceofK.pdf")
          par(mfrow = c(1, 3))
          plot(1:nsamples, RSS, type = "b", xlab = "Number of latent variables", pch=20)
          plot(1:nsamples, AIC, type = "b", xlab = "Number of latent variables", pch=20)
          plot(1:nsamples, BIC, type = "b", xlab = "Number of latent variables", pch=20)
          par(mfrow = c(1,1))

          ##########################################################
          # CBS segmentation per chromosome: optimal for WGS and WES
          ##########################################################
          finalcall.CBS <- list()
          optK <- which.max(BIC)
          for (chr in unique(seqnames(ref_qc))) {
            chr.index <- which(seqnames(ref_qc) == chr)
            Yhat.null.chr <- lapply(Yhat, function(x) x[chr.index,])

            finalcall.CBS[[chr]] <- segmentCBS(Y_qc[chr.index,], Yhat = Yhat.null.chr, optK = optK, K = 1:nsamples, sampname_qc = sampname_qc, ref_qc = ranges(ref_qc)[chr.index], chr = chr, lmax = 400, mode = "integer")
          }
          # write results
          write.table(finalcall.CBS[[chr]], file = paste0(projectname, "_", optK, ".CODEX_Chrom.txt"), sep = "\t", quote = F, row.names = F)
CWL CODEX From line 21 of tools/codex.cwl 
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
baseCommand: [bash, -c]

inputs:
  script:
    type: string?
    inputBinding:
      position: 1
    default: |
      INPUT_FILE=$0
      SAMPLE_FILE=$1
      MIN_LEN=$2
      MAX_LEN=$3
      MIN_LRATIO=$4
      TEMP_NAME=${INPUT_FILE/_Chrom.txt/.filtered.txt}
      TEMP_FILE=$(echo "$TEMP_NAME" | sed "s/.*\///")
      OUTPUT_NAME=${TEMP_FILE/txt/bed}
      OUTPUT_FILE=$(echo "$OUTPUT_NAME" | sed "s/.*\///")

      tail -n +2 $INPUT_FILE | awk -v maxLen=$MAX_LEN -v minLen=$MIN_LEN -v minLRatio=$MIN_LRATIO '{ \
      chr=$2; \
      start=$4; \
      end=$5; \
      sample=$1; \
      len=$6; \
      lratio=$12; \
      st_exon=$7; \
      ed_exon=$8; \
      type=$3=="del"?"DEL":"DUP"; \
      tool="codex"; \
      if(len>minLen && \
         len<maxLen && \
         len/(ed_exon-st_exon)<50 && \
         lratio>=minLRatio){
           print chr"\t"start"\t"end"\t"sample"\t"type"\t"lratio"\t"tool}}' > ${TEMP_FILE}

      # mapping case_id with sample_id
      join -1 4 -2 2 -o 1.1,1.2,1.3,2.1,1.5,1.6,1.7 <(sort -k 4 $TEMP_FILE) <(sort -k 2 $SAMPLE_FILE) > ${OUTPUT_FILE}

  input:
    type: File
    inputBinding:
      position: 2
  samples:
    type: File
    inputBinding:
      position: 3
  min_len:
    type: string?
    inputBinding:
      position: 4
  max_len:
    type: string?
    inputBinding:
      position: 5
  min_lratio:
    type: string?
    inputBinding:
      position: 6
CWL From line 9 of tools/codex_filter.cwl 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
baseCommand: [bash, -c]

inputs:
  script:
    type: string?
    inputBinding:
      position: 1
    default: |
      INPUT_FILE=$0
      OUTPUT_NAME=${INPUT_FILE/bed/sorted.merged.bed}
      OUTPUT_FILE=$(echo "$OUTPUT_NAME" | sed "s/.*\///")

      for i in $(cat $INPUT_FILE | sed -e "s/[[:space:]]\+/\t/g" | cut -f4 | sort -u)  # FIXME: remove sed -e "s/[[:space:]]\+/\t/g" try better solution
      do
        for j in "DEL" "DUP"
        do
          grep $i $INPUT_FILE | grep $j | sed -e "s/[[:space:]]\+/\t/g" | bedtools sort | bedtools merge -c 6,7 -o max,distinct | awk -v sample=$i -v type=$j '{ \
            print $1,$2,$3,sample,type,$4,$5}' OFS="\t"
        done >> ${OUTPUT_FILE}
      done
  input:
    type: File
    inputBinding:
      position: 2
CWL BEDTools From line 17 of tools/collapse.cwl 
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
baseCommand: [Rscript]

inputs:
  input:
    type: 'File[]'
    inputBinding:
      position: 2
      itemSeparator: ','
  mapping:
    type: File
    inputBinding:
      position: 3
  reference_genome:
    type: File
    inputBinding:
      position: 4
  regions:
    type: File
    inputBinding:
      position: 5
  script:
    type: File
    inputBinding:
      position: 1
    default:
        class: File
        basename: "exomeDepth.R"
        contents: |-
          # load packages
          library(ExomeDepth)

          # parse arguments
          args <- commandArgs(TRUE)
          args2 <- args[2]

          bamsList <- as.vector(strsplit(args[1], ",")[[1]])
          bamsList <- sapply(strsplit(bamsList, "[/]"), "[[", 3)

          bams <- read.csv(args2, header = TRUE, sep = ",") # mapping file
          bed <- read.csv(args[4], sep = "\t")
          refgen <- args[3]

          # mapping
          dirPath <- dirname(args2)
          bamsMap <- bams[bams$file %in% bamsList,]
          batch <- bamsMap$batch[[1]]

          # set global variables
          bamFiles <- as.vector(bamsMap$file)
          baiFiles <- as.vector(bamsMap$index_file)
          bamdir <- file.path(dirPath, bamFiles)
          baidir <- file.path(dirPath, baiFiles)

          # prepare bed file (4th column is the annotation for each region)
          bed <- bed[,1:4]
          colnames(bed) <- c("chromosome", "start", "end", "name")

          # get counts per bed region
          message('\n[INFO] Creating counts matrix')
          my.counts <- getBamCounts(bed.frame = bed, bam.files = bamdir, include.chr = FALSE, min.mapq = 20, referenceFasta = refgen, index.files = baidir)
          ExomeCount.dafr <- as(my.counts, "data.frame")

          # prepare the main matrix of read count data
          ExomeCount.mat <- as.matrix(ExomeCount.dafr[, grep(names(ExomeCount.dafr), pattern = '*.bam')])
          nsamples <- ncol(ExomeCount.mat)

          results <- data.frame(NULL) # to write results

          # start looping over each sample
          for (i in 1:nsamples) {

            sampname <- sapply(strsplit(bamsList[[i]], "[.]"), "[[", 1) # get sample name
            message(paste0("\n[INFO] Creating reference set for ", bamsList[[i]]))

            # Create the aggregate reference set for this sample
            my.choice <- select.reference.set(test.counts = ExomeCount.mat[,i],
                                              reference.counts = ExomeCount.mat[,-i],
                                              bin.length = (ExomeCount.dafr$end - ExomeCount.dafr$start)/1000,
                                              n.bins.reduced = 10000)

            my.reference.selected <- apply(X = ExomeCount.mat[, my.choice$reference.choice, drop = FALSE],
                                          MAR = 1,
                                          FUN = sum)

            message('\n[INFO] Computing correlation between sample and references...\n')
            my.test = ExomeCount.mat[, i, drop = FALSE]
            my.ref.counts = ExomeCount.mat[, my.choice$reference.choice, drop = FALSE]
            correlation = cor(my.test[,1], apply(my.ref.counts, 1, mean))
            message(paste("\n[INFO] Correlation between reference and tests count is", round(correlation,4)))

            message('\n[INFO] Creating the ExomeDepth object')
            all.exons <- new('ExomeDepth',
                            test = ExomeCount.mat[,i],
                            reference = my.reference.selected,
                            formula = 'cbind(test, reference) ~ 1')

            # Call the CNVs
            message('\n[INFO] Calling CNVs')
            all.exons <- CallCNVs(x = all.exons,
                                  transition.probability = 10^-4,
                                  chromosome = ExomeCount.dafr$space,
                                  start = ExomeCount.dafr$start,
                                  end = ExomeCount.dafr$end,
                                  name = bed$name)

            all.exons@CNV.calls$sample_id <- sampname # set sample name
            results <- rbind(results, all.exons@CNV.calls)  # append to results

          }
          message('\n[INFO] Writting results')
          output.file <- paste0("batch_", batch, ".exomeDepth.csv")
          write.csv(file = output.file, x = results, row.names = FALSE)
CWL ExomeDepth From line 21 of tools/exome_depth.cwl 
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
baseCommand: [bash, -c]

inputs:
  script:
    type: string?
    inputBinding:
      position: 1
    default: |
      INPUT_FILE=$0
      SAMPLE_FILE=$1
      MIN_LEN=$2
      MAX_LEN=$3
      MIN_BF=$4
      TEMP_NAME=${INPUT_FILE/csv/filtered.csv}
      TEMP_FILE=$(echo "$TEMP_NAME" | sed "s/.*\///")
      OUTPUT_NAME=${TEMP_FILE/csv/bed}
      OUTPUT_FILE=$(echo "$OUTPUT_NAME" | sed "s/.*\///")

      tail -n +2 $INPUT_FILE | sed 's/"//g' | awk -F"," -v maxLen=$MAX_LEN -v minLen=$MIN_LEN -v minBf=$MIN_BF '{ \
      chr=$7; \
      start=$5; \
      end=$6; \
      sample=$13; \
      bf=$9; \
      len=(end-start)/1000; \
      type=$3=="deletion"?"DEL":"DUP"; \
      tool="exomeDepth"; \
      if(len>minLen && \
         len<maxLen && \
         bf>=minBf){
           print chr"\t"start"\t"end"\t"sample"\t"type"\t"bf"\t"tool}}' > ${TEMP_FILE}

      # mapping case_id with sample_id
      join -1 4 -2 2 -o 1.1,1.2,1.3,2.1,1.5,1.6,1.7 <(sort -k 4 $TEMP_FILE) <(sort -k 2 $SAMPLE_FILE) > ${OUTPUT_FILE}

  input:
    type: File
    inputBinding:
      position: 2
  samples:
    type: File
    inputBinding:
      position: 3
  min_len:
    type: string?
    inputBinding:
      position: 4
  max_len:
    type: string?
    inputBinding:
      position: 5
  min_bf:
    type: string?
    inputBinding:
      position: 6
CWL From line 9 of tools/exome_depth_filter.cwl 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
baseCommand: [fastp]

arguments:
  - prefix: '-o'
    valueFrom: $(inputs.fastq1.nameroot.replace(/\b.fastq\b/g, '')).trimmed.fastq
  - |
    ${
      if (inputs.fastq2){
        return '-O';
      } else {
        return '';
      }
    }
  - |
    ${
      if (inputs.fastq2){
        return inputs.fastq2.nameroot.replace(/\b.fastq\b/g, '') + '.trimmed.fastq';
      } else {
        return '';
      }
    }
  - prefix: '--unpaired1'
    valueFrom: $(inputs.fastq1.nameroot.replace(/\b.fastq\b/g, '')).unpaired.trimmed.fastq
  - |
    ${
      if (inputs.fastq2){
        return '--unpaired2';
      } else {
        return '';
      }
    }
  - |
    ${
      if (inputs.fastq2){
        return inputs.fastq2.nameroot.replace(/\b.fastq\b/g, '') + ".unpaired.trimmed.fastq";
      } else {
        return '';
      }
    }

inputs:
  fastq1:
    type: File
    inputBinding:
      prefix: -i
  fastq2:
    type: File
    inputBinding:
      prefix: -I
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '--thread'
  cut_right:
    type: boolean?
    default: true
    inputBinding:
      prefix: '--cut_right'
  cut_right_window_size:
    type: int?
    default: 5
    inputBinding:
      prefix: '--cut_right_window_size'
  cut_right_mean_quality:
    type: int?
    default: 24
    inputBinding:
      prefix: '--cut_right_mean_quality'
  trim_tail1:
    type: int?
    default: 1
    inputBinding:
      prefix: '--trim_tail1'
  length_required:
    type: int?
    default: 70
    inputBinding:
      prefix: '--length_required'
CWL fastp From line 17 of tools/fastp.cwl 
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
baseCommand: [fastqc]

arguments:
  - valueFrom: $(runtime.outdir)
    prefix: '-o'
  - valueFrom: '--noextract'

inputs:
  fastq1:
    type: 'File[]'
    inputBinding:
      position: 2
  fastq2:
    type: 'File[]'
    inputBinding:
      position: 3
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '--threads'
CWL FastQC From line 20 of tools/fastqc.cwl 
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
baseCommand: [gridss]

arguments:
  - position: 2
    prefix: '--output'
    valueFrom: $(inputs.input.nameroot.split('.')[0]).gridss.raw.vcf.gz
  - position: 5
    prefix: '--jar'
    valueFrom: "/usr/local/share/gridss-2.9.3-0/gridss.jar"

inputs:
  input:
    type: File
    secondaryFiles:
      - .bai
    inputBinding:
      position: 7
  reference_genome:
    type: File
    inputBinding:
      prefix: '--reference'
      position: 1
  assemblyFilename:
    type:
      - string?
      - "null"
    default: "gridss.assembly.bam"
    inputBinding:
      prefix: '--assembly'
      position: 3
  threads:
    type: int?
    default: 1
    inputBinding:
      prefix: '--threads'
      position: 4
  blacklist:
    type: File?
    inputBinding:
      prefix: '--blacklist'
      position: 6
CWL GRIDSS From line 21 of tools/gridss.cwl 
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
baseCommand: [bash, -c]

inputs:
  script:
    type: string?
    inputBinding:
      position: 1
    default: |
      INPUT_FILE=$0
      SAMPLE_FILE=$1
      MIN_LEN=$2
      MAX_LEN=$3
      MIN_Q=$4
      OUTPUT_NAME=${INPUT_FILE/raw/filtered}
      OUTPUT_FILE=$(echo "$OUTPUT_NAME" | sed "s/.*\///")

      # mapping case_id with sample_id
      SAMPLE_ID=(${OUTPUT_FILE//./ })
      CASE_ID=$(awk -v search="$SAMPLE_ID" '$0 ~ search{print $1}' "$SAMPLE_FILE")

      tail -n +2 $INPUT_FILE | awk -v maxLen=$MAX_LEN -v minLen=$MIN_LEN -v minQ=$MIN_Q '{ \
      chr=$1; \
      start=$2; \
      end=$6; \
      sample="'$CASE_ID'"; \
      q=$11; \
      len=(end-start)/1000; \
      type=$7; \
      tool="gridss"; \
      if(len>minLen && \
         len<maxLen && \
         q>=minQ && \
         (type=="DEL" || type=="DUP")){
           print chr"\t"start"\t"end"\t"sample"\t"type"\t"q"\t"tool}}' > ${OUTPUT_FILE}

  input:
    type: File
    inputBinding:
      position: 2
  samples:
    type: File
    inputBinding:
      position: 3
  min_len:
    type: string?
    inputBinding:
      position: 4
  max_len:
    type: string?
    inputBinding:
      position: 5
  min_q:
    type: string?
    inputBinding:
      position: 6
CWL GRIDSS From line 9 of tools/gridss_filter.cwl 
17
18
19
20
21
22
23
24
25
26
27
28
29
baseCommand: []
arguments:
  - position: 0
    shellQuote: false
    valueFrom: >-
      $(inputs.input_fasta.nameext == '.gz' ? 'gunzip -c' : 'echo gunzip')


inputs:
  input_fasta:
    type: File
    inputBinding:
      position: 2
CWL From line 17 of tools/gunzip.cwl 
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
arguments:
  - position: 0
    valueFrom: "/usr/local/share/manta-1.6.0-0/bin/configManta.py"
    shellQuote: false
  - position: 2
    valueFrom: $(";{runDir}/runWorkflow.py".replace(/\{runDir\}/g, inputs.runDir))
    shellQuote: false

inputs:
  input:
    type: File
    secondaryFiles:
      - .bai
    inputBinding:
      prefix: '--bam'
      position: 1
      shellQuote: false
  reference_genome:
    type: File
    secondaryFiles:
      - .fai
      - .amb
      - .ann
      - .bwt
      - .pac
      - .sa
    inputBinding:
      prefix: '--referenceFasta'
      position: 1
      shellQuote: false
  exome:
    type: boolean?
    inputBinding:
      prefix: "--exome"
      position: 1
      shellQuote: false
  regions:
    type: File
    secondaryFiles:
      - .tbi
    inputBinding:
      prefix: '--callRegions'
      position: 1
      shellQuote: false
  runDir:
    type: string?
    default: "generated"
    inputBinding:
      prefix: '--runDir'
      position: 1
      shellQuote: false
CWL From line 22 of tools/manta.cwl 
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
baseCommand: [bash, -c]

inputs:
  script:
    type: string?
    inputBinding:
      position: 1
    default: |
      INPUT_FILE=$0
      SAMPLE_FILE=$1
      MIN_LEN=$2
      MAX_LEN=$3
      MIN_Q=$4
      OUTPUT_NAME=${INPUT_FILE/raw/filtered}
      OUTPUT_FILE=$(echo "$OUTPUT_NAME" | sed "s/.*\///")

      # mapping case_id with sample_id
      SAMPLE_ID=(${OUTPUT_FILE//./ })
      CASE_ID=$(awk -v search="$SAMPLE_ID" '$0 ~ search{print $1}' "$SAMPLE_FILE")

      tail -n +2 $INPUT_FILE | awk -v maxLen=$MAX_LEN -v minLen=$MIN_LEN -v minQ=$MIN_Q '{ \
      chr=$1; \
      start=$2; \
      end=$6; \
      sample="'$CASE_ID'"; \
      q=$8; \
      len=(end-start)/1000; \
      type=$11; \
      tool="manta"; \
      if(len>minLen && \
        len<maxLen && \
        q>=minQ && \
        (type=="DEL" || type=="DUP")){
          print chr"\t"start"\t"end"\t"sample"\t"type"\t"q"\t"tool}}' > ${OUTPUT_FILE}

  input:
    type: File
    inputBinding:
      position: 2
  samples:
    type: File
    inputBinding:
      position: 3
  min_len:
    type: string?
    inputBinding:
      position: 4
  max_len:
    type: string?
    inputBinding:
      position: 5
  min_q:
    type: string?
    inputBinding:
      position: 6
CWL manta From line 9 of tools/manta_filter.cwl 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
baseCommand: [bash, -c]

inputs:
  script:
    type: string?
    inputBinding:
      position: 1
    default: |
      INPUT_FILE=$0
      OUTPUT_NAME=${INPUT_FILE/bed/sorted.merged.bed}
      OUTPUT_FILE=$(echo "$OUTPUT_NAME" | sed "s/.*\///")

      for i in $(cat $INPUT_FILE | sed -e "s/[[:space:]]\+/\t/g" | cut -f4 | sort -u)  # FIXME: remove sed -e "s/[[:space:]]\+/\t/g" try better solution
      do
        for j in "DEL" "DUP"
        do
          grep $i $INPUT_FILE | grep $j | sed -e "s/[[:space:]]\+/\t/g" | bedtools sort | bedtools merge -c 6,7 -o collapse | awk -v sample=$i -v type=$j '{ \
            print $1,$2,$3,sample,type,$4,$5}' OFS="\t"
        done >> ${OUTPUT_FILE}
      done
  input:
    type: File
    inputBinding:
      position: 2
CWL BEDTools From line 17 of tools/merge_all.cwl 
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
baseCommand: [picard, MarkDuplicates]

arguments:
  - position: 2
    valueFrom: OUTPUT=$(inputs.input.nameroot).dedup.bam
  - position: 3
    valueFrom: METRICS_FILE=$(inputs.input.nameroot).dedup.metrics.txt
  - position: 4
    valueFrom: ASSUME_SORTED=TRUE

inputs:
  input:
    type: File
    inputBinding:
      position: 1
      prefix: 'INPUT='
      separate: false
CWL From line 19 of tools/picard_markduplicates.cwl 
18
19
20
21
22
23
24
25
26
27
28
29
30
31
baseCommand: []
arguments:
  - position: 0
    shellQuote: false
    valueFrom: >-
      $(inputs.input_index ? 'echo samtools faidx' : 'samtools faidx')

inputs:
  input_fasta:
    type: File
    inputBinding:
      position: 1
  input_index:
    type: File?
CWL SAMtools From line 18 of tools/samtools_faidx.cwl 
19
20
21
22
23
24
25
26
27
28
29
baseCommand: [samtools, index]

arguments:
  - position: 1
    valueFrom: -b

inputs:
  input:
    type: File
    inputBinding:
      position: 2
CWL From line 19 of tools/samtools_index.cwl 
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
baseCommand: [samtools, merge, -f]

arguments:
  - position: 2
    valueFrom: $(inputs.paired.nameroot.split('.')[0]).sorted.bam

inputs:
  paired:
    type: File
    inputBinding:
      position: 3
  unpaired_R1:
    type: File
    inputBinding:
      position: 4
  unpaired_R2:
    type: File
    inputBinding:
      position: 5
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '--threads'
CWL From line 21 of tools/samtools_merge.cwl 
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
baseCommand: [samtools, sort]

arguments:
  - position: 3
    prefix: '-o'
    valueFrom: $(inputs.input.nameroot).sorted.bam

inputs:
  input:
    type: File
    inputBinding:
      position: 2
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '--threads'
CWL From line 19 of tools/samtools_sort.cwl 
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
baseCommand: [samtools, view]

arguments:
  - position: 5
    prefix: '-o'
    valueFrom: $(inputs.input.nameroot).filtered.bam

inputs:
  input:
    type: File
    inputBinding:
      position: 4
  min_mapping_quality:
    type: int
    inputBinding:
      position: 2
      prefix: '-q'
  bits_set:
    type: int
    inputBinding:
      position: 3
      prefix: '-F'
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '--threads'
CWL From line 16 of tools/samtools_view.cwl 
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
baseCommand: [samtools, view]

arguments:
  - position: 3
    prefix: '-o'
    valueFrom: $(inputs.input.nameroot).bam

inputs:
  input:
    type: File
    inputBinding:
      position: 2
      prefix: '-bS'
  threads:
    type: int?
    default: 1
    inputBinding:
      position: 1
      prefix: '--threads'
CWL From line 19 of tools/samtools_view_sam2bam.cwl 
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
baseCommand: [Rscript]

inputs:
  input:
    type: File
    inputBinding:
      position: 2
  script:
    type: File
    inputBinding:
      position: 1
    default:
        class: File
        basename: "gridss.R"
        contents: |-
          library(stringr)
          library("VariantAnnotation")
          library("StructuralVariantAnnotation")

          args <- commandArgs(TRUE)
          vcfFile <- args[1]
          bedFile <- paste(sub('\\.vcf.gz$', '', vcfFile), ".bed", sep = "")

          simpleEventType <- function(gr) {
            return(
              ifelse(seqnames(gr) != seqnames(partner(gr)), "Translocation",
                     ifelse(gr$insLen >= abs(gr$svLen) * 0.7, "Insertion",
                            ifelse(strand(gr) == strand(partner(gr)), "Inversion",
                                   ifelse(xor(start(gr) < start(partner(gr)), strand(gr) == "-"), "DEL",
                                          "DUP")))))
          }
          options(scipen=999)
          full_vcf <- readVcf(vcfFile)
          gr <- breakpointRanges(full_vcf)
          bedpe <- data.frame(
            chrom1=seqnames(gr),
            start1=start(gr) - 1,
            end1=end(gr),
            chrom2=seqnames(partner(gr)),
            start2=start(partner(gr)) - 1,
            end2=end(partner(gr)),
            type=simpleEventType(gr),
            svLen=gr$svLen,
            insLen=gr$insLen,
            name=names(gr),
            score=gr$QUAL,
            strand1=strand(gr),
            strand2=strand(partner(gr))
          )

          bedpe <- bedpe[str_detect(bedpe$name, "gridss.+o"),]
          write.table(bedpe, bedFile, quote=FALSE, sep='\t', row.names=FALSE, col.names=FALSE)
CWL stringr VariantAnnotation StructuralVariantAnnotation From line 19 of tools/structural_variants.cwl 
20
21
22
23
24
25
26
27
28
29
30
31
32
baseCommand: [svtools, vcftobedpe]

arguments:
  - position: 2
    prefix: '-o'
    valueFrom: $(inputs.input.nameroot.replace('vcf', 'bed'))

inputs:
  input:
    type: File
    inputBinding:
      position: 1
      prefix: '-i'
CWL From line 20 of tools/svtools.cwl
ShowHide 17 more snippets with no or duplicated tags.

Login to post a comment if you would like to share your experience with this workflow.

Do you know this workflow well? If so, you can request seller status , and start supporting this workflow.

Free

Created: 1yr ago
Updated: 1yr ago
Maitainers: public
URL: https://gitlab.bsc.es/lrodrig1/structuralvariants_poc/-/tree/1.1.3/structuralvariants/cwl
Name: cnv_pipeline
Version: 1.1.3
Badge:
workflow icon

Insert copied code into your website to add a link to this workflow.

Downloaded: 0
Copyright: Public Domain
License: Boost Software License 1.0
  • Future updates

Related Workflows

psychip_snakemake
Show Details View Workflow
ENCODE pipeline for histone marks developed for the psychENCODE project
public

public

psychip pipeline is an improved version of the ENCODE pipeline for histone marks developed for the psychENCODE project. The o...
raw sequence reads Alignment Sequence alignment report macs2 ucsc-bedclip bedGraphToBigWig BEDTools BWA Picard SAMtools Snakemake
Free
74
ncov_2
Show Details View Workflow
Near-real time tracking of SARS-CoV-2 in Connecticut
public

public

Repository containing scripts to perform near-real time tracking of SARS-CoV-2 in Connecticut using genomic data. This pipeli...
JSON nextclade Augur Biopython FOCUS Pandas Snakemake bs4 epiweeks geopy matplotlib numpy pycountry pycountry-convert uszipcode
Free
28
cellranger-snakemake-gke
Show Details View Workflow
snakemake workflow to run cellranger on a given bucket using gke.
public

public

A Snakemake workflow for running cellranger on a given bucket using Google Kubernetes Engine. The usage of this workflow ...
macs2 ucsc-bedclip bedGraphToBigWig BEDTools BWA Picard SAMtools Snakemake
Free
74
atlas
Show Details View Workflow
ATLAS - Three commands to start analyzing your metagenome data
public

public

Metagenome-atlas is a easy-to-use metagenomic pipeline based on snakemake. It handles all steps from QC, Assembly, Binning, t...
raw sequence reads Genome assembly Annotation track checkm2 gunc prodigal snakemake-wrapper-utils MEGAHIT Atlas BBMap Biopython BioRuby Bwa-mem2 cd-hit CheckM DAS Diamond eggNOG-mapper v2 MetaBAT 2 Minimap2 MMseqs MultiQC Pandas Picard pyfastx SAMtools SemiBin Snakemake SPAdes SqueezeMeta TADpole VAMB CONCOCT ete3 gtdbtk h5py networkx numpy plotly psutil utils metagenomics
Free
175
rna-seq-star-deseq2
Show Details View Workflow
RNA-seq workflow using STAR and DESeq2
public

public

This workflow performs a differential gene expression analysis with STAR and Deseq2. The usage of this workflow is described ...
raw sequence reads Gene expression profiling ID list snakemake-wrapper-utils biomaRt PCAtools BiocParallel BWA Cutadapt DESeq2 GFFutils MultiQC Pandas SAMtools Snakemake STAR cli stringr tidyverse RNA-Seq
Free
41
dna-seq-gatk-variant-calling
Show Details View Workflow
This Snakemake pipeline implements the GATK best-practices workflow
public

public

This Snakemake pipeline implements the GATK best-practices workflow for calling small germline variants. The usage of thi...
VCF raw sequence reads Variant calling genetic variants gatk rust-bio-tools snakemake-wrapper-utils tabix BCFtools BWA FastQC MultiQC Pandas Picard SAMtools Snakemake Trimmomatic Variant Effect Predictor (VEP) common matplotlib numpy seaborn DNA
Free
57