Low-Pass Whole Genome Sequencing Copy Number Calling Workflow (LPWGS)

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This is a snakemake workflow to get copy number calls from low-pass whole genome sequencing. It aligns fastq files, performs some QC and then runs QDNAseq.

Usage

Step 1: Install workflow

If you simply want to use this workflow, download and extract the latest release . If you intend to modify and further extend this workflow or want to work under version control, fork this repository as outlined in Advanced . The latter way is recommended.

Step 2: Configure workflow

Configure the workflow according to your needs via editing the file config.yaml .

Step 3: Execute workflow

Make sure you have snakemake installed on your hpc. If running on apocrita (QMUL hpc) you may need to install it in an environment. eg I run the following to activate an environment with snakemake installed. 

source /data/home/hfx042/bin/snakemake/bin/activate

Code Snippets

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shell:
    """
    echo "Merging fastq files R1"
    echo "fastq files: "
    echo {input.R1}
    cat {input.R1} > {output.tempfastqR1}
    echo "Merging fastq files R2"
    echo "fastq files: "
    echo {input.R2}
    cat {input.R2} > {output.tempfastqR2}
    echo "Finished merging fastqfiles"
    """
SnakeMake From line 13 of rules/align.smk 
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shell:
    """
    module load bwa/0.7.15
    module load samtools/1.8

    bwa mem -M -t {threads} \
    {params.genome} \
    {input.tempfastqR1} {input.tempfastqR2} | \
    samtools view -S -b - > {output}.temp.bam

    module load java
    java -jar -Xmx2G {params.picard} AddOrReplaceReadGroups \
       I={output}.temp.bam \
       O={output} \
       RGID={wildcards.sample} \
       RGLB={wildcards.sample} \
       RGPL=ILLUMINA \
       RGSM={wildcards.sample} \
       RGPU={wildcards.sample}

    rm {input.tempfastqR1}
    rm {input.tempfastqR2}
    rm {output}.temp.bam
    """
SnakeMake SAMtools BWA From line 36 of rules/align.smk 
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shell:
    """
    module load java
    java -jar -Xmx4G {params.picard} SortSam \
        INPUT={input.bam} \
        OUTPUT={output.bam} \
        SORT_ORDER=coordinate
    """
SnakeMake From line 68 of rules/align.smk 
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    shell:
        """
        module load java
        java -jar -Xmx4G {params.picard} MarkDuplicates \
            INPUT={input.bam} \
            OUTPUT={output.bam} \
            METRICS_FILE={output.metrics}.temp \
            CREATE_INDEX=true \
            REMOVE_DUPLICATES=true

	    grep -A2  "## METRICS" {output.metrics}.temp | tail -n +1 > {output.metrics}
        rm {output.metrics}.temp
        """
SnakeMake From line 86 of rules/align.smk 
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shell:
    """
    module load R
    module load singularity

    singularity exec {params.singularityimage} \
    Rscript {params.pipelinedirectory}/scripts/QDNAseq.R \
        --bamfiles {input.bams} \
        --binsize {params.binsize} \
        --plotdir {output.plotdir} \
        --Rdata {output.Rdata} \
        --segmentfile {output.segmentfile} \
        --pipelinedirectory {params.pipelinedirectory} \
        --filter ""
    """
SnakeMake Singularity Hub QDNAseq From line 13 of rules/CNcalling-basic.smk 
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shell:
    """
    echo "Loading fastQC"
    module load fastqc
    fastqc {input.R1} -o {output}
    fastqc {input.R2} -o {output}
    """
SnakeMake FastQC From line 13 of rules/fastQC.smk 
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shell:
    """
    longLine="--------------------"
    module load java
    module load R

    msg="Run picard CollectWGSMetrics"; echo "-- $msg $longLine"; >&2 echo "-- $msg $longLine"

    java -jar -Xmx4G {params.picard} CollectWgsMetrics \
        INPUT={input.bam} \
        OUTPUT={output.metricsWGS}.temp \
        R={params.genome}
    grep -A2  "## METRICS" {output.metricsWGS}.temp | tail -n +1 > {output.metricsWGS}
    rm {output.metricsWGS}.temp


    msg="Run picard insertsize metrics"; echo "-- $msg $longLine"; >&2 echo "-- $msg $longLine"
    java -jar -Xmx4G {params.picard} CollectInsertSizeMetrics \
        INPUT={input.bam} \
        OUTPUT={output.metricsInsert}.temp \
        H={output.metricsInsert}.pdf
    grep -A2  "## METRICS" {output.metricsInsert}.temp | tail -n +1 > {output.metricsInsert}
    rm {output.metricsInsert}.temp

    msg="Run picard CollectAlignmentSummaryMetrics"; echo "-- $msg $longLine"; >&2 echo "-- $msg $longLine"
    java -jar -Xmx4G {params.picard} CollectAlignmentSummaryMetrics \
        INPUT={input.bam} \
        OUTPUT={output.metricsAlign}.temp \
        ADAPTER_SEQUENCE=[CTGTCTCTTATA,TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG,GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG,AGATCGGAAGAGC,ACGCTCTTCCGATCT] \
        R={params.genome}
    grep -A2  "## METRICS" {output.metricsAlign}.temp | tail -n +1 > {output.metricsAlign}
    rm {output.metricsAlign}.temp

    msg="Run picard QualityScoreDistribution"; echo "-- $msg $longLine"; >&2 echo "-- $msg $longLine"
    java -jar -Xmx4G {params.picard} QualityScoreDistribution \
        INPUT={input.bam} \
        OUTPUT={output.metricsQS} \
        CHART={output.metricsQS}.pdf

    """
SnakeMake Picard From line 13 of rules/QCmetrics.smk 
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shell:
    """
    module load singularity
    singularity exec {params.singularityimage} \
    Rscript {params.pipelinedirectory}/scripts/combineQC.R \
        --WGS {input.metricsWGS} \
        --insertsize {input.metricsInsert} \
        --align {input.metricsAlign} \
        --dedup {input.metricsDedup} \
        --output {output}
    """
SnakeMake Singularity Hub From line 66 of rules/QCmetrics.smk 
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shell:
    """
    #mkdir {output.plotdir}
    module load singularity
    singularity exec {params.singularityimage} \
    Rscript {params.pipelinedirectory}/scripts/report.R \
        --QC {input.QC} \
        --output {output.report} \
        --CNA {input.CNA} \
        --plotdir {output.plotdir} \
        --pipelinedirectory {params.pipelinedirectory} \
        --readscutoff {params.readscutoff}
    """
SnakeMake Singularity Hub From line 13 of rules/report.smk 
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library(dplyr)
library(readr)
library(tidyr)
library(stringr)
library(argparse)

parser <- ArgumentParser(description = "Parse arguments to combine QC metrics")
parser$add_argument('--WGS', type = 'character',
                    help="List of WGS file metrics", default = NULL, nargs = "+")
parser$add_argument('--insertsize', type = 'character',
                    help="List of WGS file metrics", default = NULL, nargs = "+")
parser$add_argument('--align', type = 'character',
                    help="List of WGS file metrics", default = NULL, nargs = "+")
parser$add_argument('--dedup', type = 'character',
                    help="List of WGS duplication metrics", default = NULL, nargs = "+")
parser$add_argument('--output', type = 'character',
                    help="List of WGS file metrics")
args <- parser$parse_args()

dfWGS <- data.frame()
for (file in args$WGS){
  print(file)
  metrics <- read.table(file, sep="\t" , header=T)
  samplename = strsplit(basename(file),"[.]")[[1]][1]
  dfWGS <- rbind(dfWGS, metrics %>% mutate(samplename = samplename))
}
print(dfWGS)

dfinsertsize <- data.frame()
for (file in args$insertsize){
  print(file)
  metrics <- read.table(file, sep="\t" , header=T)
  samplename = strsplit(basename(file),"[.]")[[1]][1]
  dfinsertsize <- rbind(dfinsertsize, metrics %>% mutate(samplename = samplename))
}
print(dfinsertsize)

dfalign <- data.frame()
for (file in args$align){
  print(file)
  metrics <- read.table(file, sep="\t" , header=T)
  samplename = strsplit(basename(file),"[.]")[[1]][1]
  dfalign <- rbind(dfalign, metrics %>% mutate(samplename = samplename))
}
print(dfalign)

dfdedup <- data.frame()
for (file in args$dedup){
  print(file)
  metrics <- read.table(file, sep="\t" , header=T)
  samplename = strsplit(basename(file),"[.]")[[1]][1]
  dfdedup <- rbind(dfdedup, metrics %>% mutate(samplename = samplename))
}
print(dfdedup)

#df <- bind_cols(dfWGS, dfinsertsize, dfalign, dfdedup)
df <- dfWGS %>%
    left_join(., dfinsertsize) %>%
    left_join(., dfalign) %>%
    left_join(., dfdedup %>% select(-LIBRARY))

write_csv(df, args$output)
R dplyr tidyr stringr readr argparse From line 1 of scripts/combineQC.R 
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library(QDNAseq)
library(methods)
library(dplyr)
library(argparse)
library(stringr)

parser <- ArgumentParser(description = "Parse arguments for QDNAseq analysis")
parser$add_argument('--binsize', type = 'double',
                    help="Binsize for QDNAseq run", default = 500)
parser$add_argument('--bamfiles', type = 'character',
                    help="List of bam files to process", default = NULL, nargs = "+")
parser$add_argument('--plotdir', type = 'character',
                    help="Plotting directory", default = NULL)
parser$add_argument('--Rdata', type = 'character',
                    help="Rdata file", default = NULL)
parser$add_argument('--segmentfile', type = 'character',
                    help="Text file for segments", default = NULL)
parser$add_argument('--pipelinedirectory', type = 'character',
                    help="Pipeline directory", default = NULL)
parser$add_argument('--filter', type = 'character',nargs = "+",
                    help="Text file for segments", default = NULL)
args <- parser$parse_args()

source(paste0(args$pipelinedirectory, "/scripts/blacklist.R"))
#outdir <- dirname(args$Rdata)

#directory to store plots
#plotdir <- paste0(args$plotdir, "binsize", as.numeric(binsize))
plotdir <- args$plotdir
print(plotdir)

print(paste0("Number of bam files: ", length(args$bamfiles)))

if (dir.exists(plotdir) == FALSE){
  dir.create(plotdir, recursive = T)
}

args$filter <- paste0(gsub(",", "[0-9]+|", args$filter), "[0-9]+")
print(args$filter)
print(str_detect(args$bamfiles, args$filter))

args$bamfiles <- args$bamfiles[str_detect(args$bamfiles, args$filter)]
print(args$bamfiles)

basenames <- basename(args$bamfiles)
basenames <- sub(sprintf('[\\.]?%s$', "bam"), '', basenames)
bamnames <- c()
bamnames <- basenames
#for (i in basenames){
#    x <-strsplit(i, "-")[[1]]
#    bamnames <- c(bamnames, x[length(x)])
#}
print(bamnames)

#download bin annotations
bins <- getBinAnnotations(binSize = as.numeric(args$binsize))
binsnew <- bins

#remove bins in the following regions
regions <- cbind(c(6, 4, 17), c(28500001, 69200001, 43900000), c(33500000, 69300000, 44100001))
binsnew$blacklist <- calculateBlacklistByRegions(binsnew, regions)

bins@data <- left_join(bins@data, binsnew@data,
                       by = c("chromosome", "start", "end", "bases", "gc", "mappability", "residual", "use")) %>%
             mutate(blacklist = blacklist.x,
               blacklist = ifelse(blacklist.y > 0, blacklist.y, blacklist)) %>%
            select(-blacklist.x, -blacklist.y)

#load sequencing data
readCounts <- binReadCounts(bins, bamfiles=args$bamfiles, bamnames = bamnames, pairedEnds = TRUE)

#plot raw readcounts
pdf(paste(plotdir,"/","raw_profile",".pdf",sep=""),7,4)
plot(readCounts, logTransform=FALSE, ylim=c(-10, 50),main=paste("Raw Profile ",sep=""))
highlightFilters(readCounts, logTransform=FALSE,residual=TRUE, blacklist=TRUE)
dev.off()

#apply filters and plot median read counts per bin as a function of GC content and mappability
readCountsFiltered <- applyFilters(readCounts, residual=TRUE, blacklist=TRUE)
pdf(paste(plotdir,"/","isobar",".pdf",sep=""),7,4)
isobarPlot(readCountsFiltered)
dev.off()

#Estimate the correction for GC content and mappability, and make a plot for the relationship between the
#observed standard deviation in the data and its read depth
readCountsFiltered <- estimateCorrection(readCountsFiltered)
pdf(paste(plotdir,"/","noise",".pdf",sep=""),7,4)
noisePlot(readCountsFiltered)
dev.off()

#apply the correction for GC content and mappability which we then normalize, smooth outliers, calculate segmentation
#and plot the copy number profile
copyNumbers <- correctBins(readCountsFiltered)
copyNumbersNormalized <- normalizeBins(copyNumbers)
copyNumbersSmooth <- smoothOutlierBins(copyNumbersNormalized)

pdf(paste(plotdir,"/","copy_number_profile",".pdf",sep=""),7,4)
plot(copyNumbersSmooth, ylim=c(-2,2))
dev.off()

copyNumbersSegmented <- segmentBins(copyNumbersSmooth)
print("bins segmented")
copyNumbersSegmented <- normalizeSegmentedBins(copyNumbersSegmented)

pdf(paste(plotdir,"/","segments",".pdf",sep=""),7,4)
plot(copyNumbersSegmented, ylim=c(-2,2), gaincol = "firebrick3", losscol = "dodgerblue3", delcol="dodgerblue4", ampcol = "firebrick4")
dev.off()

copyNumbersCalled <- callBins(copyNumbersSegmented)
pdf(paste(plotdir,"/","copy_numbercalls",".pdf",sep=""),7,4)
plot(copyNumbersCalled, ylim=c(-2,2), gaincol = "firebrick3", losscol = "dodgerblue3", delcol="dodgerblue4", ampcol = "firebrick4")
dev.off()

output <- list(readCounts = readCounts,
               readCountsFiltered = readCountsFiltered,
               copyNumbers = copyNumbers,
               copyNumbersNormalized = copyNumbersNormalized,
               copyNumbersSmooth = copyNumbersSmooth,
               copyNumbersSegmented = copyNumbersSegmented,
               copyNumbersCalled = copyNumbersCalled)
saveRDS(output, file = args$Rdata)

exportBins(copyNumbersSmooth, file=args$segmentfile)

pdf(paste(plotdir,"/","frequencyplot",".pdf",sep=""),7,4)
frequencyPlot(copyNumbersCalled, gaincol = "firebrick3", losscol = "dodgerblue3", delcol="dodgerblue4", ampcol = "firebrick4")
dev.off()
R dplyr stringr argparse From line 1 of scripts/QDNAseq.R 
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library(tidyverse)
library(rmarkdown)
library(argparse)
library(cowplot)
parser <- ArgumentParser(description = "Parse arguments for QC metrics")
parser$add_argument('--output', type = 'character',
                    help="Output html file")
parser$add_argument('--QC', type = 'character',
                    help="QC file")
parser$add_argument('--CNA', type = 'character',
                    help="CNA file")
parser$add_argument('--plotdir', type = 'character',
                    help="Plotting directory")
parser$add_argument('--pipelinedirectory', type = 'character',
                    help="Pipeline directory", default = NULL)
parser$add_argument('--readscutoff', type = 'character',
                    help="Cut off to exclude reads from samples")
args <- parser$parse_args()
print(args)

dfQC <- read_csv(args$QC)
CNA <- readRDS(args$CNA)
print(dfQC)
print(typeof(args$readscutoff))

render(paste0(args$pipelinedirectory, "/scripts/report-basic.Rmd"),
    "html_document",
    output_dir = dirname(args$output),
    output_file = basename(args$output),
    intermediates_dir = dirname(args$output),
    clean = FALSE,
    params = list(dfQC = dfQC, CNA = CNA, plotdir = args$plotdir, readscutoff = args$readscutoff))
R tidyverse cowplot argparse rmarkdown From line 1 of scripts/report.R
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Free

Created: 1yr ago
Updated: 1yr ago
Maitainers: public
URL: https://github.com/marcjwilliams1/lpWGS
Name: lpwgs
Version: 1
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Downloaded: 0
Copyright: Public Domain
License: MIT License
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