Nothing
## Merging overlapped SVs predicted by breakDancer
breakDancerCluster <- function(df)
{
maxScore <- max(df$score)
maxScoreDf <- df[df$score==maxScore, ]
maxReadPairSupp <- min(maxScoreDf$ReadPairSupp)
dfFil <- df[df$score>=(maxScore-20)&df$ReadPairSupp>=(maxReadPairSupp/2), ]
dfFilIrange <- IRanges(start=dfFil$pos1, end=dfFil$pos2)
outTmp <- findOverlaps(dfFilIrange, reduce(dfFilIrange))
dfFil$clubd <- subjectHits(outTmp)
dfFilRes <- ddply(dfFil, ("clubd"), function(x){
if(nrow(x)==1){
return(x)
} else {
leftMin <- min(x$pos1)
rightMax <- max(x$pos2)
rangeLength <- rightMax-leftMin
x$op <- (x$pos2-x$pos1)/rangeLength
if(any(x$op<0.8)){
return(NULL)
} else {
return(x[which.max(x$ReadPairSupp), ])
}
}
})
}
## Reading in the predicted SVs given by breakDancer
readBreakDancer <- function(file="", scoreCutoff=60, readsSupport=3,
regSizeLowerCutoff=100, regSizeUpperCutoff=10000000,
method="BreakDancer", ...)
{
bdColClass <- c("character", "numeric", "NULL", "character", "numeric",
"NULL", "character", "numeric", "numeric", "numeric")
bdPred <- read.table(file, colClasses=bdColClass, fill=T, ...)
bdPred <- bdPred[,1:8]
names(bdPred) <- c("chr1", "pos1", "chr2", "pos2", "type", "size",
"score", "ReadPairSupp")
bdPred <- bdPred[bdPred$score>=scoreCutoff&
bdPred$ReadPairSupp>=readsSupport&
abs(bdPred$size)>=regSizeLowerCutoff&
abs(bdPred$size)<=regSizeUpperCutoff, ]
bdPred_clean <- bdPred[, c(1, 2, 4, 5:8)]
names(bdPred_clean) <- c("chromosome", "start", "end", "type","size", "score", "rp_support")
bdDel <- mergeOLCNVs(bdPred_clean[bdPred_clean$type=="DEL", ],software= method)
bdInv <- mergeOLCNVs(bdPred_clean[bdPred_clean$type=="INV", ],software= method)
retuRes <- list(del=bdDel, inv=bdInv)
attributes(retuRes) <- c(attributes(retuRes), list(method=method))
return(retuRes);
}
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