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SPiPv2.1_main.r
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SPiPv2.1_main.r
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#!/usr/bin/env Rscript
#######################
# SPiP software
#######################
# author Raphael Leman [email protected], Center François Baclesse and Normandie University, Unicaen, Inserm U1245
# Copyright 2019 Center François Baclesse and Normandie University, Unicaen, Inserm U1245
# This software was developed from the work:
# SPiP, a comprehensive Splicing Prediction Pipeline for massive detection of exonic and intronic variant effect on mRNA splicing.
# Raphaël Leman, Béatrice Parfait, Dominique Vidaud, Emmanuelle Girodon, Laurence Pacot, Gérald Le Gac, Chandran Ka, Claude Ferec, Yann Fichou, Céline Quesnelle,
# Etienne Muller, Dominique Vaur, Laurent Castera, Agathe Ricou, Hélène Tubeuf, Omar Soukarieh, Pascaline Gaildrat, Florence Riant, Marine Guillaud-Bataille,
# Sandrine M. Caputo, Virginie Caux-Moncoutier, Nadia Boutry-Kryza, Françoise Bonnet-Dorion, Ines Schultz, Maria Rossing, Louis Goldenberg, Olivier Quenez,
# Valentin Harter, Michael T. Parsons, Amanda B. Spurdle, Thierry Frébourg, Alexandra Martins, Claude Houdayer, Sophie Krieger
# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute,
# sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
# The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE
# FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
#launch analysis
T1 <- as.numeric(format(Sys.time(), "%s"))
#import librairy
tryCatch({
library(parallel)
},
error=function(cond) {
message("Here's the original error message:")
message(cond)
message("*****You need to install \'parallel\' library\nInstall it by: install.packages(\'parallel\')")
})
tryCatch({
library(foreach)
},
error=function(cond) {
message("Here's the original error message:")
message(cond)
message("*****You need to install \'foreach\' library\nInstall it by: install.packages(\'foreach\')")
})
tryCatch({
library(doParallel)
},
error=function(cond) {
message("Here's the original error message:")
message(cond)
message("*****You need to install \'doParallel\' library\nInstall it by: install.packages(\'doParallel\')")
})
tryCatch({
library(randomForest)
},
error=function(cond) {
message("Here's the original error message:")
message(cond)
message("*****You need to install \'randomForest\' library\nInstall it by: install.packages(\'randomForest\')")
})
cat("
_.-'''-,
.' `\\
/ /
/ .--^_^
| / C ,,\\
| | \\ _.)
\\ | / \\
'-, \\./ \\)\\)
`-/ );/
_________''--'-'________________
")
# Env variables
options(scipen=50, stringsAsFactors = FALSE)
threads = 1
genome="hg19"
maxLines = 1000
printVCF = FALSE
printProcess = FALSE
pathToGene = NULL
pathToTranscript = NULL
pathToTranscriptome = NULL
version = "2.1"
#SPiP arguments
helpMessage=paste0("Usage: SPiPv",version,".r\n
Mandatory \n
-I, --input /path/to/inputFile\t\tlist of variants file (.txt or .vcf)
-O, --output /path/to/outputFile\t\tName of ouput file (.txt or .vcf)\n
Genome options \n
-g, --GenomeAssenbly hg19\t\tGenome assembly version (hg19 or hg38) [default= ",genome,"] \n
Parallel options \n
-t, --threads N\t\tNumber of threads used for the calculation [default= ",threads,"]
-l, --maxLines N\t\tNumber of lines read in each time [default= ",maxLines,"]\n
Other options\n
--geneList /path/to/geneList.txt\t\tlist of gene to study
--transcriptList /path/to/transcriptList.txt\t\tlist of transcript to study
--transcriptome /path/to/transcriptome_hgXX.RData\t\tTranscriptome path if file is not in /path/to/SPiP/RefFiles/
--VCF\t\tPrint output in vcf format
--header\t\tPrint meta-header info
--verbose\t\tShow run process
-h, --help\t\tPrint this help message and exit\n
You could : Rscript SPiPv",version,".r -I ./testCrypt.txt -O ./outTestCrypt.txt")
#get script argument
argsFull <- commandArgs()
Rscript <- argsFull[1]
scriptPath=dirname(normalizePath(sub("--file=","",argsFull[substr(argsFull,1,7)=="--file="])))
if (length(which(argsFull=="--args"))==0){message(helpMessage);q(save = "no")}
args = argsFull[(which(argsFull=="--args")+1):length(argsFull)]
if (length(args)<4){message(helpMessage);stop("Not enought arguments")}
i=1
while (i <= length(args)){
if(args[i]=="-I"|args[i]=="--input"){
inputFile=normalizePath(args[i+1]);i = i+2
}else if(args[i]=="-O"|args[i]=="--output"){
outputFile=args[i+1];i = i+2
}else if(args[i]=="--geneList"){
pathToGene=normalizePath(args[i+1]);i = i+2
}else if(args[i]=="--transcriptList"){
pathToTranscript=normalizePath(args[i+1]);i = i+2
}else if(args[i]=="--transcriptome"){
pathToTranscriptome=normalizePath(args[i+1]);i = i+2
}else if(args[i]=="-g"|args[i]=="--GenomeAssenbly"){
genome=args[i+1];i = i+2
}else if(args[i]=="-t"|args[i]=="--threads"){
threads= as.numeric(args[i+1]);i = i+2
}else if(args[i]=="-l"|args[i]=="--maxLines"){
maxLines=as.numeric(args[i+1]);i = i+2
}else if(args[i]=="--VCF"){
printVCF=TRUE;i = i+1
}else if(args[i]=="--verbose"){
printProcess=TRUE;i = i+1
}else if(args[i]=="-h"|args[i]=="--help"){
message(helpMessage);stop()
}else{
message(paste("********Unknown option:",args[i],"\n"));message(helpMessage);stop()
}
}
#Other argument
if(genome!="hg19" & genome!="hg38"){
message("###########################")
message("#Define the assembly genome version (hg19 or hg38)")
message("###########################")
message(helpMessage)
stop()
}
registerDoParallel(threads)
CMD = paste0(normalizePath(sub("--file=","",argsFull[substr(argsFull,1,7)=="--file="])),
" --input ", inputFile,
" --output ", outputFile,
" --GenomeAssenbly ", genome,
" --threads ", threads,
" --maxLines ", maxLines,
if(!is.null(pathToGene)){paste0(" --geneList ",pathToGene)},
if(!is.null(pathToTranscript)){paste0(" --transcriptList ",pathToTranscript)},
if(!is.null(pathToTranscriptome)){paste0(" --transcriptome ",pathToTranscriptome)},
if(printVCF){" --VCF "})
fileFormat = tolower(substr(basename(inputFile),nchar(basename(inputFile))-2,nchar(basename(inputFile))))
fileFormatOut = tolower(substr(outputFile,nchar(outputFile)-2,nchar(outputFile)))
if(fileFormat!="txt" & fileFormat!="vcf"){
message("###########################")
message("#Incorrect format of input, please try again with a txt or vcf file")
message("###########################")
message(helpMessage)
stop()
}
if(fileFormatOut=="vcf"){printVCF = TRUE}
cat("##################\n")
cat("#Your command:\n")
cat("##################\n")
cat(paste0(CMD,"\n"))
#Get Ref files
inputref = paste(scriptPath, "/RefFiles",sep="")
path2scripts = paste0(inputref,"/SPiP_libs/")
tryCatch({
source(paste0(path2scripts,"SPiP_functions.r"))
},
error=function(cond) {
message("Here's the original error message:")
message(cond)
message("*****Error while importing the source file SPiP_functions.r")
}
)
# Reads headers from corresponding files, stores them as vectors of strings
path2headers = paste0(inputref,"/headers/") # path from script to folder that contains the headers
headerHelp = readLines(paste(path2headers,"headerHelp.txt",sep=""))
headerHelp[1] = paste0("##SPiP output v",version) # modifies the dynamic line containing the version
headerHelp[2] = paste0("##SPiPCommand=",CMD) # modifies the dynamic line containing the CMD
cat("Check transcriptome sequences...\n")
if(!file.exists(paste(inputref,"/transcriptome_hg19.RData",sep="")) | !file.exists(paste(inputref,"/transcriptome_hg38.RData",sep=""))){
if(!is.null(pathToTranscriptome)){
cat(paste("Your transcriptome file:",pathToTranscriptome))
load(pathToTranscriptome)
}else{
cat("You have to install the transcriptome file in /path/to/SPiP/RefFiles/\n")
cat("transcriptome_hg19.RData available at : https://sourceforge.net/projects/splicing-prediction-pipeline/files/transcriptome/transcriptome_hg19.RData/download\n")
cat("transcriptome_hg38.RData available at : https://sourceforge.net/projects/splicing-prediction-pipeline/files/transcriptome/transcriptome_hg38.RData/download\n")
q(save="no")
}
}else{
cat("Load transcriptome sequences...\n")
load(paste0(inputref, "/transcriptome_",genome,".RData"))
}
cat("Load SPiP model...\n")
load(paste0(inputref, "/model.RData"))
cat("Load VPP table...\n")
VPPtable = read.table(paste0(inputref, "/VPP_table.txt"),sep="\t",dec=",",header=TRUE)
cat("Load VPN table...\n")
VPNtable = read.table(paste0(inputref, "/VPN_table.txt"),sep="\t",dec=",",header=TRUE)
cat("Check RefSeq database...\n")
if(!file.exists(paste(inputref,"/dataRefSeqhg19.RData",sep="")) & !file.exists(paste(inputref,"/dataRefSeqhg38.RData",sep=""))){
currentWD = getwd()
setwd(scriptPath)
cat("Create RefSeq database...\n")
source(paste(inputref,"/getRefSeqDatabase.r",sep=""),local =TRUE)
setwd(currentWD)
}
cat("Load RefSeq database...\n")
load(paste0(inputref, "/dataRefSeq",genome,".RData"))
load(paste0(inputref, "/RefFiles.RData"))
if(!is.null(pathToGene)){
geneList = readLines(pathToGene)
dataRefSeq = dataRefSeq[which(as.character(dataRefSeq$V13)%in%geneList),]
}
if(!is.null(pathToTranscript)){
transcriptList = readLines(pathToTranscript)
dataRefSeq = dataRefSeq[which(as.character(dataRefSeq$V4)%in%transcriptList),]
}
mint_GT=sum(as.numeric(as.vector(sub("Min. :","",summary(ref_score_GT)[1,]))))
maxt_GT=sum(as.numeric(as.vector(sub("Max. :","",summary(ref_score_GT)[6,]))))
mint_GC=sum(as.numeric(as.vector(sub("Min. :","",summary(ref_score_GC)[1,]))))
maxt_GC=sum(as.numeric(as.vector(sub("Max. :","",summary(ref_score_GC)[6,]))))
mint1=as.numeric(as.vector(sub("Min. :","",summary(ref_score_AG)[1,1:10])))
maxt1=as.numeric(as.vector(sub("Max. :","",summary(ref_score_AG)[6,1:10])))
maxt1=maxt1[order(maxt1,decreasing=T)]
maxt1=maxt1[1:8]
maxt1=sum(maxt1)
mint1=mint1[order(mint1,decreasing=F)]
mint1=mint1[1:8]
mint1=sum(mint1)
mint2=sum(as.numeric(as.vector(sub("Min. :","",summary(ref_score_AG)[1,12:15]))))
maxt2=sum(as.numeric(as.vector(sub("Max. :","",summary(ref_score_AG)[6,12:15]))))
i_score=NULL
i_score1=NULL
i_score2=NULL
dataESR$hexamer = as.character(dataESR$hexamer)
ESRmotif = dataESR$hexamer[dataESR$Assignment!="N"]
LEIsc_valuesWA = dataESR$LEIsc_valuesWA
LEIsc_valuesHA = dataESR$LEIsc_valuesHA
LEIsc_valuesHM = dataESR$LEIsc_valuesHM
LEIsc_valuesWD = dataESR$LEIsc_valuesWD
LEIsc_valuesHD = dataESR$LEIsc_valuesHD
ESRlistScore = dataESR$ESEseq_or_ESSseqscore
names(LEIsc_valuesWA) <- dataESR$hexamer
names(LEIsc_valuesHA) <- dataESR$hexamer
names(LEIsc_valuesHM) <- dataESR$hexamer
names(LEIsc_valuesWD) <- dataESR$hexamer
names(LEIsc_valuesHD) <- dataESR$hexamer
names(ESRlistScore) <- dataESR$hexamer
indAcc = c(1:11,17:62,68:95)
indDon = c(1:28,34:74,80:95)
me2x5 = ME2x5$V1
names(me2x5) <- as.character(ME2x5$V1.1)
inverseDic <- data.frame(V1 = c('T','G','C','A','N'),row.names = c('A','C','G','T','N'))
inverseDic$V1 <- as.character(inverseDic$V1)
RegTypeToNumber <- data.frame(V1 = c(1:11),
row.names = c("DeepIntron", "Exon",
"ExonESR", "ExonESRCons", "Intron",
"IntronBP", "IntronCons", "IntronConsPolyTC",
"IntronConsPolyTCBP", "IntronPolyTC",
"IntronPolyTCBP"))
thToSPiPexon = 0.18
thToSPiPintron = 0.035
thToComplexEvent = 0.2
####################
# READING INPUT FILE
####################
# io
input<-file(inputFile,"r")
output<-file(outputFile,"w")
if(fileFormat=="vcf"){
cat("Reading header...\n")
mHeader <- NULL
rawInput <- readLines(input, n=1) # line by line # first line
firstLine <- 1 # index of current line
while (as.numeric(regexpr("^#CHROM",rawInput)) != 1 ) {
# while one has not reached the last line of the header
mHeader <- c(mHeader,rawInput)
rawInput <- readLines(input, n=1)
firstLine <- firstLine + 1 # index of current line
}
# last line of the header
mHeader <- c(mHeader, headerHelp) # add lines for SPiP
mHeader <- c(mHeader, rawInput) # add line #CHROM ...
columnsNamesLine <- rawInput # line CHROM POS ID REF ALT QUAL FILTER INFO ...
columnsNames <- unlist(strsplit(columnsNamesLine,split='\t')) #c("CHROM","POS","ID","REF","ALT","QUAL","FILTER","INFO",SUITE?)
columnsNames[1] <- substr(columnsNames[1],2,nchar(columnsNames[1])) # delete the # of #CHROM
lengthDataLine <- length(columnsNames)
if(printVCF){
writeLines(mHeader, con = output,sep="\n")
}else{
writeLines(paste(paste(columnsNames,collapse="\t"), "varID", "Interpretation", "InterConfident", "SPiPscore", "strand",
"gNomen", "varType", "ntChange", "ExonInfo", "exonSize", "transcript", "gene", "NearestSS", "DistSS", "RegType", "SPiCEproba",
"SPiCEinter_2thr", "deltaMES", "BP", "mutInPBarea", "deltaESRscore", "posCryptMut", "sstypeCryptMut", "probaCryptMut", "classProbaCryptMut",
"nearestSStoCrypt", "nearestPosSStoCrypt", "nearestDistSStoCrypt", "posCryptWT", "probaCryptWT", "classProbaCryptWT", "posSSPhysio",
"probaSSPhysio", "classProbaSSPhysio", "probaSSPhysioMut", "classProbaSSPhysioMut",sep="\t"),con = output,sep="\n")
}
# Start to read the variants
rawInput <- readLines(input, n=maxLines) # read lines by block, starting right after the header
# lengthDataLine <- length(unlist(strsplit(rawInput[1],split="\t")))
local_dataRefSeq <- NULL
while(length(rawInput) != 0) { # read all file # only supports VCF format
# EOF in last iteration -> empty input -> stop
cat(paste("Reading lines",firstLine,"to",firstLine + length(rawInput),"\n"))
cat(paste("\n",sub("CET",":",Sys.time(),fixed=T),"Extracting sequences and variant informations","\n"))
total <- length(rawInput)
if(printProcess){pb <- txtProgressBar(min = 0, max = total, initial = 1, char = "=", style = 3)}
tmpVCF <-foreach (i=1:length(rawInput),.errorhandling='pass') %dopar% {
readVCF(rawInput[i],i)
}
# merging the results of mcmapply into a dataframe
unlisted <- as.data.frame(matrix(unlist(tmpVCF), ncol = 5+lengthDataLine, byrow = TRUE))
data <- unlisted[,c(1,2,3,5)]
names(data) <- c("varID", "seqPhysio", "seqMutated", "altUsed")
transcriptsDF <- data.frame(trID = unlisted[,c(4)])
VCFinfo_DF <- unlisted[,c(6:(5+lengthDataLine))]
VCFinfo_text <- apply(VCFinfo_DF,1,paste,collapse="\t")
###################
# SCORE CALCULATION
###################
if(!is.null(data)){
# STEP 1 : deleting repetitions in the vcf storage
colnames(VCFinfo_DF) <- columnsNames
VCFinfo_toPrint <- unique(VCFinfo_text)
# STEP 2 : update of the local_dataRefSeq
if (!is.null(transcriptsDF)) {
setTranscript(transcriptsDF) # add transcripts information to local_dataRefSeq
}
# STEP 3 : Score computation
cat(paste("\n",gsub("CET",":",Sys.time(),fixed=T),"Score Calculation...","\n"))
total <- nrow(data)
if(printProcess){pb2 <- txtProgressBar(min = 0, max = total, initial = 1, char = "=", style = 3)}
rawResult<-foreach (i=1:nrow(data),.errorhandling='pass') %dopar% {
getOutputToSPiPmodel(data[i,"varID"],i,data[i,"seqPhysio"], data[i,"seqMutated"])
}
rawAnnotation = as.data.frame(matrix(unlist(rawResult),ncol=35, byrow = TRUE))
names(rawAnnotation) <- c("chr", "strand", "gNomen", "varType", "ntChange", "ExonInfo", "exonSize", "transcript",
"gene", "NearestSS", "DistSS", "RegType", "seqPhysio", "seqMutated", "SPiCEproba", "SPiCEinter_2thr", "deltaMES", "BP", "mutInPBarea",
"deltaESRscore", "posCryptMut", "sstypeCryptMut", "probaCryptMut", "classProbaCryptMut", "nearestSStoCrypt", "nearestPosSStoCrypt",
"nearestDistSStoCrypt", "posCryptWT", "probaCryptWT", "classProbaCryptWT", "posSSPhysio", "probaSSPhysio", "classProbaSSPhysio",
"probaSSPhysioMut", "classProbaSSPhysioMut")
data = cbind(data,rawAnnotation)
data = SPiP(data)
#################
# WRITING RESULTS
#################
cat(paste("\n",sub("CET",":",Sys.time(),fixed=T),"Write results...","\n"))
INFO <- apply(data[,c("altUsed","varID","Interpretation", "InterConfident", "SPiPscore", "strand", "gNomen", "varType", "ntChange", "ExonInfo", "exonSize", "transcript",
"gene", "NearestSS", "DistSS", "RegType", "SPiCEproba", "SPiCEinter_2thr", "deltaMES", "BP", "mutInPBarea",
"deltaESRscore", "posCryptMut", "sstypeCryptMut", "probaCryptMut", "classProbaCryptMut", "nearestSStoCrypt", "nearestPosSStoCrypt",
"nearestDistSStoCrypt", "posCryptWT", "probaCryptWT", "classProbaCryptWT", "posSSPhysio", "probaSSPhysio", "classProbaSSPhysio",
"probaSSPhysioMut", "classProbaSSPhysioMut")],1,paste,collapse="|")
if(length(grep(".",data$RegType,fixed=T))>0){
INFO[data$RegType=="."] = paste0(data$alt_used[data$RegType=="."],"|","Variant caused an error in SPiP execution")
}
if(printVCF){
spipResult = mapply(mergeSPiPresult,VCFinfo_toPrint)
VCFinfo_DF = VCFinfo_DF[!duplicated(VCFinfo_text),]
if(length(which(VCFinfo_DF$INFO=="."))>0){
index = which(VCFinfo_DF$INFO==".")
VCFinfo_DF$INFO[index] = spipResult[index]
VCFinfo_DF$INFO[-index] = paste(VCFinfo_DF$INFO[-index],spipResult[-index],sep=";")
}else{
VCFinfo_DF$INFO = paste(VCFinfo_DF$INFO,spipResult,sep=";")
}
rawToprint = apply(VCFinfo_DF,1,paste0,collapse="\t")
writeLines(rawToprint, con = output,sep="\n")
}else{
rawResult = apply(data[,c("varID", "Interpretation", "InterConfident", "SPiPscore", "strand",
"gNomen", "varType", "ntChange", "ExonInfo", "exonSize", "transcript", "gene", "NearestSS", "DistSS", "RegType", "SPiCEproba",
"SPiCEinter_2thr", "deltaMES", "BP", "mutInPBarea", "deltaESRscore", "posCryptMut", "sstypeCryptMut", "probaCryptMut", "classProbaCryptMut",
"nearestSStoCrypt", "nearestPosSStoCrypt", "nearestDistSStoCrypt", "posCryptWT", "probaCryptWT", "classProbaCryptWT", "posSSPhysio",
"probaSSPhysio", "classProbaSSPhysio", "probaSSPhysioMut", "classProbaSSPhysioMut")],1,paste,collapse="\t")
writeLines(paste(VCFinfo_text,rawResult,sep="\t"),con = output,sep="\n")
}
flush(output) # necessary ?
}
# read the following lines = while loop increment
rawInput <- readLines(input, n=maxLines)
firstLine <- firstLine + maxLines
# check object size : for(i in ls()){eval(parse(text = paste("s = object.size(",i,")")));print(i);print(s,units = "auto")}
}
}else{
firstLine <- 1 # index of current line
rawInput <- readLines(input, n=firstLine) # line by line # first line
columnsNamesLine <- rawInput # table names
columnsNames <- c(unlist(strsplit(columnsNamesLine,split='\t')), "Interpretation", "InterConfident", "SPiPscore", "strand",
"gNomen", "varType", "ntChange", "ExonInfo", "exonSize", "transcript", "gene", "NearestSS", "DistSS", "RegType", "SPiCEproba",
"SPiCEinter_2thr", "deltaMES", "BP", "mutInPBarea", "deltaESRscore", "posCryptMut", "sstypeCryptMut", "probaCryptMut", "classProbaCryptMut",
"nearestSStoCrypt", "nearestPosSStoCrypt", "nearestDistSStoCrypt", "posCryptWT", "probaCryptWT", "classProbaCryptWT", "posSSPhysio",
"probaSSPhysio", "classProbaSSPhysio", "probaSSPhysioMut", "classProbaSSPhysioMut")
lengthDataLine <- length(columnsNames)
if(length(grep("varID",columnsNames))==0){
message("###########################")
message("#Your data doesn't have the varID column")
message("###########################")
message(helpMessage)
stop()
}
if(printVCF){
writeLines(c(headerHelp,"#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO"), con = output,sep="\n")
}else{
writeLines(c(paste(columnsNames,collapse="\t")), con = output,sep="\n")
}
rawInput <- readLines(input, n=maxLines) # read lines by block, starting right after the header
while(length(rawInput) != 0) { # read all file
cat(paste("Reading lines",firstLine,"to",firstLine + length(rawInput),"\n"))
data = splitRawToTable(rawInput,head=FALSE)
names(data)=unlist(strsplit(columnsNamesLine,split='\t'))
transcriptsDF <- data.frame(trID = unlist(mapply(getTranscript2varID,data$varID)))
setTranscript(transcriptsDF) # add transcripts information to local_dataRefSeq
message(paste("\n",gsub("CET",":",Sys.time(),fixed=T),"Score Calculation..."))
total <- nrow(data)
if(printProcess){pb2 <- txtProgressBar(min = 0, max = total, initial = 1, char = "=", style = 3)}
rawAnnotation <- foreach (i=1:nrow(data),.errorhandling='pass') %dopar% {
getOutputToSPiPmodel(data[i,"varID"],i)
}
rawAnnotation = as.data.frame(matrix(unlist(rawAnnotation),ncol=35, byrow = TRUE))
names(rawAnnotation) <- c("chr", "strand", "gNomen", "varType", "ntChange", "ExonInfo", "exonSize", "transcript",
"gene", "NearestSS", "DistSS", "RegType", "seqPhysio", "seqMutated", "SPiCEproba", "SPiCEinter_2thr", "deltaMES", "BP", "mutInPBarea",
"deltaESRscore", "posCryptMut", "sstypeCryptMut", "probaCryptMut", "classProbaCryptMut", "nearestSStoCrypt", "nearestPosSStoCrypt",
"nearestDistSStoCrypt", "posCryptWT", "probaCryptWT", "classProbaCryptWT", "posSSPhysio", "probaSSPhysio", "classProbaSSPhysio",
"probaSSPhysioMut", "classProbaSSPhysioMut")
data = cbind(data,rawAnnotation)
data = SPiP(data)
message(paste("\n",sub("CET",":",Sys.time(),fixed=T),"Write results..."))
if(printVCF){
rawOutputVCF <- foreach (i=1:nrow(data),.errorhandling='pass') %dopar% {
paste(convertLine2VCF(data[i,]),collapse="\t")
}
writeLines(unlist(rawOutputVCF), con = output,sep="\n")
}else{
writeLines(c(apply(data[,columnsNames],1,paste,collapse="\t")), con = output, sep = "\n")
}
flush(output)
# read the following lines = while loop increment
rawInput <- readLines(input, n=maxLines)
firstLine <- firstLine + maxLines
}
}