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#'
#' This function launches the segmentation of allele B fraction only for heterozygous SNPs.
#'
#' @title segmentation function for the allele B fraction
#'
#' @param dataSetName The name of the data-set folder (it must correspond to a folder name in rawData folder.).
#' @param normalTumorArray Only in the case of normal-tumor study. A csv file or a data.frame containing the mapping between normal and tumor files.
#' The first column contains the name of normal files and the second the names of associated tumor files.
#' @param chromosome A vector with the chromosomes to be segmented.
#' @param Rho Vector containing all the penalization values to test for the segmentation. If no values are provided, default values will be used.
#' @param listOfFiles A vector containing the names of the files in dataSetName folder for which the allele B profile is segmented (default is all the files).
#' @param savePlot if TRUE, graphics of the segmented allele B profile will be saved in the figures/dataSetName/segmentation/fracB folder. (default=TRUE).
#' @param verbose if TRUE print some informations
#'
#' @return a data.frame where each row correspond to a different segment with columns :
#' \describe{
#' \item{sampleNames}{The name of the signal.}
#' \item{chromosome}{A vector of the same size as copynumber containing the chromosome number.}
#' \item{chromStart}{The starting position of a segment.}
#' \item{chromEnd}{The ending position of a segment.}
#' \item{probes}{The number of probes in the segment.}
#' \item{means}{Means of the segment.}
#' }
#'
#' @export
#'
#' @author Quentin Grimonprez
#'
segFracBSignal=function(dataSetName,normalTumorArray,chromosome=1:22,Rho=NULL,listOfFiles=NULL,savePlot=TRUE,verbose=TRUE)
{
allpkg=TRUE
if(!suppressPackageStartupMessages(requireNamespace("aroma.affymetrix", quietly=TRUE) ) )
{
message("Package not found: aroma.affymetrix. For download it:\n")
message("source(\"http://callr.org/install#HenrikBengtsson/sfit\")\n")
message("if (!requireNamespace(\"BiocManager\", quietly = TRUE))\n")
message("install.packages(\"BiocManager\")\n")
message("BiocManager::install(\"affxparser\")\n")
message("BiocManager::install(\"DNAcopy\")\n")
message("BiocManager::install(\"aroma.light\")\n")
message("install.packages(\"aroma.affymetrix\")\n")
allpkg=FALSE
}
if(!suppressPackageStartupMessages(requireNamespace("aroma.cn", quietly=TRUE) ) )
{
message("Package not found: aroma.cn. For download it:\n")
message("install.packages(\"aroma.cn\")\n")
allpkg=FALSE
}
if(!allpkg)
stop("You have to install some packages : Follow the printed informations.")
requireNamespace("aroma.core")
requireNamespace("R.devices")
requireNamespace("R.filesets")
if(!("totalAndFracBData"%in%list.files()))
stop("There is no \"totalAndFracBData\", check if you are in the good working directory or if you have run the signalPreProcess function before.")
if(!("callData"%in%list.files()))
stop("There is no \"totalAndFracBData\", check if you are in the good working directory or if you have run the signalPreProcess function before.")
###check the arguments
#dataSetName
if(missing(dataSetName))
stop("dataSetName is missing.")
if(!is.character(dataSetName))
stop("dataSetName must be the name of a folder in \"rawData\" folder.")
if(!(dataSetName%in%list.files("rawData")))
stop("dataSetName must be the name of a folder in \"rawData\" folder.")
#################### import the dataSet to have the name of all the files
#check if we are in a normal-tumor study or in a single array study
#singleStudy=TRUE
if(missing(normalTumorArray))
stop("No normalTumorArray specified.\n Youd need to specify a normalTumorArray to extract allele B fraction")
#path where find the CN data
rootPath <- "totalAndFracBData";
rootPath <- Arguments$getReadablePath(rootPath);
dataSet <- paste0(dataSetName,",ACC,ra,-XY,BPN,-XY,AVG,FLN,-XY");
#load CN
dsC <- aroma.core::AromaUnitTotalCnBinarySet$byName(dataSet, chipType="*", paths=rootPath);
################### check normalTumorArray
# if(!singleStudy)
# {
#normalTumorArray
if(is.character(normalTumorArray))
normalTumorArray=read.csv(normalTumorArray)
else
{
if(!is.data.frame(normalTumorArray))
stop("normalTumorArray must be either the path to the normalTumorArray csv file or a data.frame containing the data.\n")
}
#check normalTumorArray
if(!("normal"%in%colnames(normalTumorArray)) || !("tumor"%in%colnames(normalTumorArray)))
stop("normalTumorArray doesn't contain a column \"normal\" or \"tumor\".\n")
# isArrayComplete=sapply(R.filesets::getNames(dsC),FUN=function(name,listOfNames){name%in%listOfNames},c(as.character(normalTumorArray$normal),as.character(normalTumorArray$tumor)))
# if(sum(isArrayComplete)!=length(isArrayComplete))
# warning("normalTumorArray doesn't contain all the filenames of dataSetName.")
# }
###### check listOfFiles
pos=c()
if(is.null(listOfFiles) || missing(listOfFiles))
{
listOfFiles=R.filesets::getNames(dsC)
pos=1:length(dsC)
}
else
{
#check the format
if(!is.vector(listOfFiles) || !is.character(listOfFiles))
stop("listOfFiles must be a vector of string.")
listOfFiles=unique(listOfFiles)
#check if all the files of listOfFiles are in the folder
pos=sapply(listOfFiles,match,R.filesets::getNames(dsC))#position of the files of listOfFiles in the folder
if(length(which(pos>0))!=length(pos))
stop("Wrong name of files in listOfFiles")
if(!missing(normalTumorArray))
{
isArrayComplete=sapply(listOfFiles,FUN=function(name,listOfNames){name%in%listOfNames},c(as.character(normalTumorArray$normal),as.character(normalTumorArray$tumor)))
if(sum(isArrayComplete)!=length(isArrayComplete))
stop("normalTumorArray doesn't contain all the filenames you specified in listOfFiles parameter.")
}
}
#if single array study, we just reduce dsC to pos
# if(!singleStudy)
# {
# #if normal-tumor study, we need the tumor and normal files
#
#we obtain the complementary files
compFiles=getComplementaryFile(listOfFiles,normalTumorArray)
allFiles=unique(c(listOfFiles,compFiles))
#index of the files
pos=sapply(allFiles,FUN=function(x,dsC){which(R.filesets::getNames(dsC)==x)},dsC)
tag=getStatus(allFiles,normalTumorArray)
pos=pos[which(tag=="normal")]
if (length(pos)!=length(which(tag=="tumor")))
{
stop("normalTumorArray must contain one unique normal sample per tumor sample to extract allele B fraction.")
}
# }
#Rho
if(missing(Rho) || is.null(Rho))
Rho=c(seq(0.1,2,by=0.1),seq(2.2,5,by=0.2),seq(5.5,10,by=0.2),seq(11,16,by=1),seq(18,36,by=2),seq(40,80,by=4))
######################### END CHECK PARAMETERS
###bed files output
#results are stored in the segmentation folder
#check the existence of the segmentation folder
if(!("segmentation"%in%list.files()))
dir.create("segmentation");
#check the existence of th dataSet folder in segmentation folder
if(!(dataSetName%in%list.files("segmentation")))
dir.create(paste0("segmentation/",dataSetName));
figPath <- Arguments$getWritablePath(paste0("figures/",dataSetName,"/segmentation/fracB"));
#names of the files to segment
names=R.filesets::getNames(dsC)[pos]
output=lapply(names,FUN=function(name)
{
segment=data.frame()
for(chr in chromosome)
{
#get the fracB for 1 chr
# if(!singleStudy)
fracB=getFracBSignal(dataSetName,chromosome=chr,normalTumorArray,listOfFiles=name,verbose=verbose)
#else
# fracB=getFracBSignal(dataSetName,chromosome=chr,listOfFiles=name,verbose=verbose)
fracB=fracB[[paste0("chr",chr)]]$tumor
gc()
#get the genotype calls for 1 chr
geno=getGenotypeCalls(dataSetName,chromosome=chr,listOfFiles=name,verbose=verbose)
geno=geno[[paste0("chr",chr)]]
gc()
ind=which(geno[,3]=="AB")
rm(geno)
gc()
fracB=fracB[ind,]
fracB[,3]=symmetrizeFracB(fracB[,3])
#segmentation
message(paste0("Segmentation of file ",name," chromosome ",chr,"..."))
if (is.null(fracB[,3]) || length(fracB[,3])<2){
message("to few point to segment \n")
} else {
seg=PELT(fracB[,3],Rho,position=fracB$position,plot=TRUE,verbose=verbose)
message("OK\n")
if(savePlot)
{
figName <- sprintf("%s,%s,%s", name, "fracB,chr",chr);
pathname <- filePath(figPath, sprintf("%s.png", figName));
width <- 1280;
aspect <- 0.6*1/3;
fig <- R.devices::devNew("png", pathname, label=figName, width=width, height=2*aspect*width);
plot(NA,xlim=c(min(fracB$position),max(fracB$position)), ylim=c(0,1),xlab="Position", main=figName,ylab="Allele B fraction", pch=".")
points(fracB$position, fracB[,3], pch=".");
for(i in 1:nrow(seg$segment))
lines(c(seg$segment$start[i],seg$segment$end[i]),rep(seg$segment$means[i],2),col="red",lwd=3)
R.devices::devDone();
}
#concatenate the results
# cghArg=list(fracB=rbind(cghArg$copynumber,seg$signal),
# segmented=rbind(cghArg$segmented,seg$segmented),
# startPos=c(cghArg$startPos,fracB$position),
# chromosome=c(cghArg$chromosome,rep(fracB$chromosome,length(seg$signal))),
# sampleNames=name,
# featureNames=c(cghArg$featureNames,fracB$featureNames),
# segment=data.frame(chrom=c(as.character(cghArg$segment$chrom),unlist(lapply(rep(fracB$chromosome,length(seg$segment$means)),as.character))),
# chromStart=c(cghArg$segment$chromStart,seg$segment$start),
# chromEnd=c(cghArg$segment$chromEnd,seg$segment$end),
# probes=c(cghArg$segment$probes,seg$segment$points),
# means=c(cghArg$segment$means,seg$segment$means)))
segment=data.frame(chrom=c(as.character(segment$chrom),rep(paste0("chr",chr),length(seg$segment$start))),
chromStart=c(segment$chromStart,seg$segment$start),
chromEnd=c(segment$chromEnd,seg$segment$end),
probes=c(segment$probes,seg$segment$points),
means=c(segment$means,seg$segment$means))
}
}
#write in .bed
write.table(segment,file=paste0("segmentation/",dataSetName,"/",name,",symFracB,segmentation.bed"),sep="\t",row.names=FALSE)
segment=cbind(rep(name,nrow(segment)),segment)
names(segment)[1]="sampleNames"
return(segment)
})
output=do.call(rbind,output)
row.names(output)=NULL
return(output)
}
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