liserjrqlxue / runExomeDepth

ExomeDepth for WES CNV calling

Base on https://github.com/vplagnol/ExomeDepth.git

simple run

Rscript run.R bam.list bai.list

speed up

1. create Bins

• Input:
  ref as hg19 reference file
• Output:
  exons.hg19.A.target.rds
exons.hg19.A.rdata.rds exons.hg19.X.target.rds
exons.hg19.X.rdata.rds
• Script:

library(ExomeDepth)
data(exons.hg19)
data(exons.hg19.X)
source("getBins.R")
ref='hg19.fa'
getBins(
    bed.frame = exons.hg19,
    include.chr = T,
    referenceFasta = ref,
    prefix="exons.hg19.A"
    )
getBins(
    bed.frame = exons.hg19.X,
    include.chr = T,
    referenceFasta = ref,
    prefix="exons.hg19.X"
    )

or

Rscript init.R hg19.fa

2. run getBamCounts parallel for each sample

• Input:
  sampleID as prefix
  bam as bam file path
• Output:
  SampleID.my.count.rds
• Script:

args=commandArgs(T)
sampleID=args[1]
bam=args[2]
library(ExomeDepth)
source("getBamCount.R")
target <- readRDS("exons.hg19.target.rds")
my.count <- getBamCount(
    target = target,
    bam = bam
    )
saveRDS(my.count,file=paste0(sampleID,".my.count.rds"))

3. create main matrix of read count data of all sample

• Input:
  sample.list as sampleID list
• Output:
  all.my.counts.rds as all count data in a matrix
• Script:

args=commandArgs(T)
sample.list=args[1]
#sample.list="sample.list"
samples=read.table(sample.list,stringsAsFactors=F)[,1]
library(ExomeDepth)
my.bins <- readRDS('exons.hg19.rdata.rds')
my.counts.matrix <- matrix(ncol=length(samples),nrow=nrow(my.bins))
colnames(my.counts.matrix) <- samples
for(i in 1:length(samples)){
    my.counts.matrix[,i] <- readRDS(paste0(samples[i],".my.count.rds"))
}
saveRDS(my.counts.matrix,file=paste0('all',".my.counts.rds"))

4. run CallCNVs for each sample

• Input:
  sampleID as selected sample to call CNVs
• Output:
  sampleID.CNV.calls.tsv as CNV calls result sampleID.all.exons.rds as rds data of CNV calls
• Script:

args=commandArgs(T)
sampleID=args[1]
library(ExomeDepth)
data(exons.hg19)
data(Conrad.hg19)
exons.hg19.GRanges <- GenomicRanges::GRanges(
    seqnames = exons.hg19$chromosome,
    IRanges::IRanges(start=exons.hg19$start,end=exons.hg19$end),
    names = exons.hg19$name
    )
my.counts.matrix <- readRDS(file=paste0('all',".my.counts.rds"))
samples <- colnames(my.counts.matrix)
for(i in 1:length(samples)){
    if(sampleID!=samples[i]){
        next
    }
    my.choice <- select.reference.set(
        test.counts = my.counts.matrix[,i],
        reference.counts = my.counts.matrix[,-i],
        bin.length = (exons.hg19$end - exons.hg19$start)/1000,
        n.bins.reduced = 10000
        )
    my.reference.selected <- apply(
        X = my.counts.matrix[,my.choice$reference.choice,drop=FALSE],
        MAR = 1,
        FUN = sum
        )
    message('Now creating the ExomeDepth object')
    all.exons <- new(
        'ExomeDepth',
        test = my.counts.matrix[,i],
        reference = my.reference.selected,
        formula = 'cbind(test, reference) ~ 1'
        )
######## Now call the CNVs
    all.exons <- CallCNVs(
        x = all.exons,
        transition.probability = 10^-4,
        chromosome = exons.hg19$chromosome,
        start = exons.hg19$start+1,
        end = exons.hg19$end,
        name = exons.hg19$name
        )
######## Now annotate the ExomeDepth object
    all.exons <- AnnotateExtra(
        x = all.exons,
        reference.annotation = Conrad.hg19.common.CNVs,
        min.overlap = 0.5,
        column.name = 'Conrad.hg19'
        )
    all.exons <- AnnotateExtra(
        x = all.exons,
        reference.annotation = exons.hg19.GRanges,
        min.overlap = 0.0001,
        column.name = 'Conrad.hg19'
        )
    output.file <- paste0(sampleID,'.CNV.calls.tsv')
    write.table(file=output.file,x=[e-mail],row.names=F,sep="\t",quote=F)
    saveRDS(all.exons,file=paste0(sampleID,'.all.exons.rds'))
}

example

1. Rscript run.getBamCount.R SampleID bam.file for each sample
   input:SampleID as prefix and bam.file as bam path
   output:SampleID.my.count.rds
   time:15mins for each
2. Rscript run.getAllCounts.R sample.list
   input:sample.list as batch list of samples
   output:all.my.counts.rds
   time:12s
3. Rscript run.CallCNVs.R
   input:all.my.counts.rds
   output:SampleID.CNV.calls.tsv and SampleID.all.exons.rds for each sample
   time:12mins for total 12 test samples
4. Rscript run.getCNVs.R SampleID
   input:all.my.counts.rds and selected sample SampleID
   output:SampleID.CNV.calls.tsv and SampleID.all.exons.rds for selected sample
   time:1mins