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JaxCNVMerge.R
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JaxCNVMerge.R
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##########################################################################################
################################ function defination begin ###############################
is.installed <- function(requirePackage){
is.element(requirePackage, installed.packages()[, 1])
}
dbscanMerge <- function(oneTypeData){
if(nrow(oneTypeData) == 1){
return(oneTypeData)
}
if(nrow(oneTypeData) == 2){
return(twoRegionMerge(oneTypeData))
}
dataNum <- nrow(oneTypeData)
mergedResults <- data.frame(chr = "", start = 0, end = 0, type = "", subtype = "")
theLengths <- oneTypeData$end - oneTypeData$start
theLength <- mean(oneTypeData$end - oneTypeData$start)
theMeanDensity <- (oneTypeData$end[dataNum] - oneTypeData$start[1]) / sum(theLengths)
theDist <- matrix(theMeanDensity + 1, nrow = dataNum, ncol = dataNum)
theDistNeigh <- oneTypeData$start[2 : dataNum] - oneTypeData$end[1 : (dataNum - 1)]
for(i in 1 : (dataNum - 1)){
theDist[i, i] <- 0
theDist[i, i + 1] <- (theLengths[i] + theLengths[i + 1] + theDistNeigh[i]) / (theLengths[i] + theLengths[i + 1])
theDist[i + 1, i] <- theDist[i, i + 1]
}
theDist[dataNum, dataNum] <- 0
theDist[which(theDist > 3, 2)] <- theMeanDensity + 1
theDistUsed <- as.dist(theDist)
theRes <- dbscan(theDistUsed, minPts = 2, eps = theMeanDensity)
oneCluData <- oneTypeData[which(theRes$cluster == 0), ]
mergedResults <- rbind(mergedResults, oneCluData)
theCluster <- unique(theRes$cluster[which(theRes$cluster != 0)])
if(length(theCluster) > 0){
for(clu in theCluster){
oneCluData <- oneTypeData[which(theRes$cluster == clu), ]
thestart = min(oneCluData$start)
theend = max(oneCluData$end)
mergedResults <- rbind(mergedResults, data.frame(chr = oneTypeData$chr[1], start = thestart, end = theend,
type = oneTypeData$type[1], subtype = oneTypeData$subtype[1],
stringsAsFactors = F))
}
}
mergedResults <- mergedResults[-1, ]
return(mergedResults)
}
bedRegionMerge <- function(oneTypeData){
# get the distance of each pair
oneTypeData <- oneTypeData[order(oneTypeData$start), ]
if(nrow(oneTypeData) == 1){
return(oneTypeData)
}
dataNum <- nrow(oneTypeData)
mergedResults <- data.frame(chr = "", start = 0, end = 0, type = "", subtype = "")
theDistNeigh <- oneTypeData$start[2 : dataNum] - oneTypeData$end[1 : (dataNum - 1)]
## seperate the data into different part by dist = DistCannotMerge,
## then in each part, using the dbscan to merge, threshold is meandensity
theIndexLargerCannotMerge <- which(theDistNeigh > DistCannotMerge)
if(length(theIndexLargerCannotMerge) == 0){
mergedResults <- rbind(mergedResults, dbscanMerge(oneTypeData))
mergedResults <- mergedResults[-1, ]
return(mergedResults)
}
firstPartIndex <- 1 : theIndexLargerCannotMerge[1]
firstPartData <- oneTypeData[firstPartIndex, ]
mergedResults <- rbind(mergedResults, dbscanMerge(firstPartData))
for(j in 2 : length(theIndexLargerCannotMerge)){
if(j > length(theIndexLargerCannotMerge)){
break()
}
partIndex <- (theIndexLargerCannotMerge[j - 1] + 1) : theIndexLargerCannotMerge[j]
partData <- oneTypeData[partIndex, ]
mergedResults <- rbind(mergedResults, dbscanMerge(partData))
}
lastPartIndex <- (theIndexLargerCannotMerge[length(theIndexLargerCannotMerge)] + 1) : dataNum
lastPartData <- oneTypeData[lastPartIndex, ]
mergedResults <- rbind(mergedResults, dbscanMerge(lastPartData))
mergedResults <- mergedResults[-1, ]
return(mergedResults)
}
twoRegionMerge <- function(oneTypeData){
mergedResults <- data.frame(chr = "", start = 0, end = 0, type = "", subtype = "")
theDist <- abs(oneTypeData$end[1] - oneTypeData$start[2])
if(theDist > DistCannotMerge){
return(oneTypeData)
}
theLength <- oneTypeData$end - oneTypeData$start
MeanTheLength <- mean(theLength)
theFold1 <- theDist / MeanTheLength
theFold2 <- theDist / min(theLength)
theFold3 <- theDist / max(theLength)
if((theFold1 < 1 & theFold2 < 3) | theFold3 < 0.1){
start = min(oneTypeData$start[1], oneTypeData$start[2])
end = max(oneTypeData$end[1], oneTypeData$end[2])
mergedResults <- rbind(mergedResults, data.frame(chr = oneTypeData$chr[1], start = start, end = end,
type = oneTypeData$type[1], subtype = oneTypeData$subtype[1],
stringsAsFactors =F))
}else{
mergedResults <- rbind(mergedResults, oneTypeData)
}
mergedResults <- mergedResults[-1, ]
return(mergedResults)
}
getTheMergeRes <- function(theDataUseToMerge){
if(nrow(theDataUseToMerge) == 1){
return(theDataUseToMerge)
}else{
preNum <- nrow(theDataUseToMerge)
oneMergedRes <- bedRegionMerge(theDataUseToMerge)
oneMergedRes <- oneMergedRes[order(oneMergedRes$start), ]
while(nrow(oneMergedRes) < preNum){
preNum <- nrow(oneMergedRes)
oneMergedRes <- bedRegionMerge(oneMergedRes)
oneMergedRes <- oneMergedRes[order(oneMergedRes$start), ]
}
return(oneMergedRes)
}
}
################################# function defination end ################################
##########################################################################################
##########################################################################################
################# check if the required packages have been installed #####################
if(!is.installed("dbscan")){ install.packages("dbscan", repos="http://cran.us.r-project.org") }
if(!is.installed("data.table")){ install.packages("data.table", repos="http://cran.us.r-project.org") }
library(dbscan)
library(data.table)
##########################################################################################
##########################################################################################
###################################### argument parsing ##################################
DistCannotMerge <- 3000000
oneBed <- ""
theHelpMessge =
paste(" The required packages are \"dbscan\" and \"data.table\" \n",
" The usage of JaxCNVMerge is like: \n",
" \"Rscript --vanilla JaxCNVMerge.R -md 3000000 -i filename\". The output file is filename.merge.bed\n",
" Arguments: \n",
" --max_distance or -md (option), numeric, distance threshold in merging, default s 3000000 \n",
" --bed or -i (required), string, the bed file of the CNV fragments \n",
" --help or -h, print the help messgae \n", sep = "")
args <- commandArgs(TRUE)
if(length(args) < 1) {
args <- c("--help")
}
## Help section
if("--help" %in% args | "-h" %in% args) {
cat(theHelpMessge)
q(save="no")
}
if("--max_distance" %in% args){
argIndex <- which(args == "--max_distance")
DistCannotMerge <- as.numeric(args[argIndex + 1])
}else if("-md" %in% args){
argIndex <- which(args == "-md")
DistCannotMerge <- as.numeric(args[argIndex + 1])
}
if("--bed " %in% args){
argIndex <- which(args == "--bed")
oneBed <- args[argIndex + 1]
}else if("-i" %in% args){
argIndex <- which(args == "-i")
oneBed <- args[argIndex + 1]
}else{
cat(theHelpMessge)
q(save="no")
}
print(paste("the input file is :", oneBed, sep = ''))
print(paste("the output file is :", oneBed, ".merge.bed", sep = ""))
print(paste("the max_distance is: ", format(DistCannotMerge, scientific = F), sep = ''))
###############################################################################################
###############################################################################################
########################### merge CNVs in Bedfile bedfile #####################################
mergedResults <- data.frame(chr = "", start = 0, end = 0, type = "", subtype = "")
theData <- fread(oneBed, header = F, sep = "\t")
colnames(theData) <- c("chr", "start", "end", "type", "subtype")
chrs <- unique(theData$chr)
for(oneChr in chrs){ ## for CNVs in a chromosome
print(paste("-------", oneChr, sep = ""))
oneChrData <- theData[which(theData$chr == oneChr), ]
oneChrData <- oneChrData[order(oneChrData$start), ]
if(nrow(oneChrData) == 1){
mergedResults <- rbind(mergedResults, oneChrData)
next()
}
currType <- oneChrData$type[1]
currEnd <- oneChrData$end[1]
theDataUseToMerge <- oneChrData[1, ]
for(i in 2 : nrow(oneChrData)){
if(oneChrData$type[i] == currType & (oneChrData$start[i] - currEnd) <= DistCannotMerge){
theDataUseToMerge <- rbind(theDataUseToMerge, oneChrData[i, ])
}else{
mergedResults <- rbind(mergedResults, getTheMergeRes(theDataUseToMerge))
currType <- oneChrData$type[i]
theDataUseToMerge <- oneChrData[i, ]
}
currEnd <- oneChrData$end[i]
}
if(nrow(theDataUseToMerge) > 0){
mergedResults <- rbind(mergedResults, getTheMergeRes(theDataUseToMerge))
}
}
mergedResults <- mergedResults[-1, ]
lengths <- mergedResults$end - mergedResults$start
mergedResults <- mergedResults[which(lengths > 46000), ] ## filter the lengths
fwrite(mergedResults, file = paste(oneBed, ".merge.bed", sep = ''), quote = F, append = F,
row.names = F, col.names = F, sep = '\t')
###############################################################################################