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exec/safeQuant.R
In SafeQuant: A Toolbox for the Analysis of Proteomics Data
#!/usr/local/bin/Rscript
###
# 0) Update SHEBANG ('#!/usr/bin/Rscript') to match location of your R installation
# 1) INSTALL SafeQuant
# - or SET sqDirPath
# 2) INSTALL PACKAGES
# affy
# limma
# gplots
# seqinr
# corrplot
# optparse
# data.table
# Author: ahrnee-adm
###############################################################################
# TEST FILE
# /Users/ahrnee-adm/dev/R/workspace/SafeQuant/inst/testData/new/peptides1_FILTERED.csv /Volumes/pcf01\$/Schmidt_Group/Databases/SwissProt_Databases/s_human_d_201405.fasta
# /Users/ahrnee-adm/dev/R/workspace/SafeQuant/inst/testData/new/proteins1.csv
# /Users/ahrnee-adm/dev/R/workspace/SafeQuant/inst/testData/new/TMT_6-Plex_Scaffold_Raw_Export_Example.xls
############################################################### INIT ###############################################################
#### DEPENDANCIES
suppressWarnings(suppressPackageStartupMessages(library("affy", quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library("limma", quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(gplots, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(seqinr, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(corrplot, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(optparse, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(data.table, quiet=T)))
sourceDirOSX <- "/Users/ahrnee-adm/dev/R/workspace/SafeQuant/R/"
sourceDirTPP <- "/import/bc2/home/pcf/ahrnee/R/SafeQuant/R/"
# first check if dev or tpp mode
if(file.exists(sourceDirOSX) | file.exists(sourceDirTPP)){
sourceDir <- ifelse(file.exists(sourceDirOSX),sourceDirOSX,sourceDirTPP)
source(paste(sourceDir,"ExpressionAnalysis.R",sep=""))
source(paste(sourceDir,"SafeQuantAnalysis.R",sep=""))
source(paste(sourceDir,"Graphics.R",sep=""))
source(paste(sourceDir,"IdentificationAnalysis.R",sep=""))
source(paste(sourceDir,"Parser.R",sep=""))
source(paste(sourceDir,"TMT.R",sep=""))
source(paste(sourceDir,"UserOptions.R",sep=""))
}else if("SafeQuant" %in% installed.packages()[,1]){ # used installed SafeQuant
cat("Loading SafeQuant Library \n")
library("SafeQuant")
}else{
stop("SafeQuant Package not installed\n")
}
VERSION <- "2.3.1"
### USER CMD LINE OPTIONS
userOptions <- getUserOptions(version=VERSION)
### USER CMD LINE OPTIONS END
if(userOptions$verbose) print(userOptions$proteinQuant)
### SUPRESS WARNINGS
if(!userOptions$verbose){
options(warn=-1)
}
#### DEPENDENCIES
if(userOptions$verbose) print(userOptions)
############################################################### PARSING ###############################################################
if(userOptions$verbose) cat("PARSING INPUT FILE \n")
# get file type
fileType <- .getFileType(userOptions$inputFile)
### Progenesis Export
if(fileType %in% c("ProgenesisProtein","ProgenesisFeature","ProgenesisPeptide")){
# default
expDesign <- getExpDesignProgenesisCsv(userOptions$inputFile)
# get user specified experimental design
if(!is.na(userOptions$expDesignTag)){
# user specified
expDesign <- expDesignTagToExpDesign(userOptions$expDesignTag,expDesign)
}
if(fileType == "ProgenesisProtein"){
cat("INFO: PARSING PROGENESIS PROTEIN EXPORT FILE ",userOptions$inputFile, "\n" )
eset <- parseProgenesisProteinCsv(file=userOptions$inputFile,expDesign=expDesign)
}else if(fileType == "ProgenesisPeptide"){
#"ProgenesisFeature"
cat("INFO: PARSING PROGENESIS PEPTIDE EXPORT FILE ",userOptions$inputFile, "\n" )
eset <- parseProgenesisPeptideMeasurementCsv(file=userOptions$inputFile,expDesign=expDesign, uniqueProteins=userOptions$FUniquePeptides)
}else{ #"ProgenesisFeature"
cat("INFO: PARSING PROGENESIS FEATURE EXPORT FILE ",userOptions$inputFile, "\n" )
eset <- parseProgenesisFeatureCsv(file=userOptions$inputFile,expDesign=expDesign)
}
# Scaffold Export (TMT data)
}else if(fileType == "ScaffoldTMT"){
cat("INFO: PARSING SCAFFOLD RAW EXPORT FILE ",userOptions$inputFile, "\n" )
# get default experimental design
# six plex or ten plex ?
# use default experimental design unless specified by the user
nbPlex <- .getNbPlex(userOptions$inputFile)
if(nbPlex == 6){
# 6-plex default: 1,2,3:4,5,6
expDesign <- data.frame(condition=paste("Condition",sort(rep(c(1,2),3)),sep=""),isControl=sort(rep(c(T,F),3),decreasing=T) )
}else{
# 10-plex default is "1,4,7,10:2,5,8:3,6,9"
expDesign <- data.frame(condition=paste("Condition",c(1,2,3,1,2,3,1,2,3,1),sep=""),isControl=c(T,F,F,T,F,F,T,F,F,T) )
}
eset <- parseScaffoldRawFile(file=userOptions$inputFile,expDesign=expDesign)
if(userOptions$TAdjustRatios){
#if((nbPlex == 10)){ # only possible for tmt-10 plex
nbCalMixSpectra <- sum( (fData(eset)$proteinName %in% names(CALIBMIXRATIOS)))
if(nbCalMixSpectra < 100) stop("Not enough Calibration Mix spectra were found: ",nbCalMixSpectra, "\n ")
cat("INFO: FOUND ", nbCalMixSpectra ," Calibration Mix spectra\n")
esetCalibMix <- .getCalibMixEset(eset)
# discard calibration mix proteins
eset <- eset[!(fData(eset)$proteinName %in% names(CALIBMIXRATIOS)),]
intAdjObj <- .intensityAdjustment(eset, esetCalibMix)
#}else{
# stop("Ratio Correction Not implemented for TMT 6-plex")
#}
}
# get user specified experimental design
if(!is.na(userOptions$expDesignTag)){
# user specified
expDesign <- expDesignTagToExpDesign(userOptions$expDesignTag,expDesign)
}
# eset <- parseScaffoldRawFile(file=userOptions$inputFile,expDesign=expDesign)
# apply specified experimental design
eset <- createExpressionDataset(expressionMatrix=exprs(eset)[,rownames(expDesign)],expDesign=expDesign,featureAnnotations=fData(eset))
if(!is.na(userOptions$scaffoldPTMSpectrumReportFile)){
cat("INFO: ADDING SCAFFOLD PTM ANNOTATIONS \n")
eset <- addScaffoldPTMFAnnotations(eset,userOptions$scaffoldPTMSpectrumReportFile)
}
}else if(fileType == "MaxQuantProteinGroup"){
# get user specified experimental design
if(!is.na(userOptions$expDesignTag)){
# user specified
expDesign <- expDesignTagToExpDesign(userOptions$expDesignTag,data.frame(condition=paste("Condition",1:1000),isControl=c(F,1000)) )
}else{
stop("Please Specify Experimental Design")
}
eset <- parseMaxQuantProteinGroupTxt(userOptions$inputFile,expDesign=expDesign, method="auc")
}else if(fileType == "GenericCSV"){
}else{
stop("Unknown File Type", userOptions$inputFile)
}
# test option, limit number of entries
if(userOptions$test){
eset <- eset[1:nrow(eset) %in% sample(1:min(300,c(nrow(eset))),replace=F),]
}
# parse .fasta file
if(!is.na(userOptions$proteinFastaFile)){
cat("INFO: PARSING PROTEIN SEQUENCE DB ",userOptions$proteinFastaFile, "\n" )
### read protein db
proteinDB <- read.fasta(userOptions$proteinFastaFile,seqtype = "AA",as.string = TRUE, set.attributes = FALSE)
# dirty fix check if ACs in Progenesis file are stripped
if(isStrippedACs(sample(fData(eset)$proteinName,100))){
cat("INFO: RE-FORMATTING ACCESSION NUMBERS\n")
names(proteinDB) <- stripACs(names(proteinDB))
}
}
############################################################### CREATE DATA MODEL ###############################################################
if(userOptions$verbose) print(eset)
if(userOptions$verbose) print(pData(eset))
if(userOptions$verbose) print(names(fData(eset)))
#### CREATE FEATURE DATA AND FILTER (pre-rollup)
# generic
filter <- data.frame(
con=isCon(fData(eset)$proteinName) # contaminants
,ac = !(grepl(userOptions$selectedProteinName,fData(eset)$proteinName,ignore.case=T)) # protein ac
)
# do not filter TMT data
if("pMassError" %in% names(fData(eset)) && (fileType != "ScaffoldTMT") ){
### applicable to Progenesis feature Exports
if(is.na(userOptions$precursorMassFilter)){ # if not user specified
# automatically get precursor limits, X * sd of 50% top scoring
userOptions$precursorMassFilter <- getMeanCenteredRange(fData(eset)$pMassError[fData(eset)$idScore > quantile(fData(eset)$idScore,na.rm=T)[3]],nbSd = 3)
filter <- cbind(filter, pMassError=
(fData(eset)$pMassError < userOptions$precursorMassFilter[1])
| (fData(eset)$pMassError > userOptions$precursorMassFilter[2]) # precursor mass tolerance
)
}
}
if("ptm" %in% names(fData(eset))){
# add motif-X and ptm coordinates
if(exists("proteinDB")){
cat("INFO: EXTRACTING PTM COORDINATES AND MOTIFS\n")
#format 1) progensis 2) scaffold
eset <- .addPTMCoord(eset,proteinDB,motifLength=6, isProgressBar=T,format= (fileType == "ScaffoldTMT") +1)
}
filter <- cbind(filter
, ptm = !(grepl(userOptions$selectedModifName,as.character(fData(eset)$ptm),ignore.case=T))
, nbPtmsPerPeptide = (fData(eset)$nbPtmsPerPeptide > userOptions$maxNbPtmsPerPeptide) )
}
if("peptide" %in% names(fData(eset))){
filter <- cbind(filter
, peptideLength =nchar(as.character(fData(eset)$peptide)) < userOptions$minPeptideLength
, charge = fData(eset)$charge == 1 # discard singly charged
)
}
if(!("nbPeptides" %in% names(fData(eset)))){
### set nb peptides per protein
eset <- setNbPeptidesPerProtein(eset)
}
filter <- cbind(filter,nbPeptides=(fData(eset)$nbPeptides < userOptions$minNbPeptidesPerProt))
# do not filter TMT data
#if(("idScore" %in% names(fData(eset))) && (fileType != "ScaffoldTMT")){
if(("idScore" %in% names(fData(eset)))){
eset <- addIdQvalues(eset)
filter <- cbind(filter,qvalue=fData(eset)$idQValue > userOptions$fdrCutoff)
}
# set pre-rollup filters
eset <- .setFilter(eset,filter=filter)
### make sure at least 1 feature pass the filter
if(sum(!fData(eset)$isFiltered,na.rm=T) == 0){
stop("CHECK FILTER SETTINGS. ALL FEATURES WERE FILTERED OUT")
}
#### CREATE FEATURE DATA AND FILTER END
### SET ANCHOR PROTEINS
fData(eset)$isNormAnchor <- grepl(userOptions$normAC,fData(eset)$proteinName)
if(userOptions$verbose){
cat("\nNB. ANCHOR PROTEINS: ")
cat(sum(fData(eset)$isNormAnchor))
cat("\n")
print(fData(eset)$proteinName[fData(eset)$isNormAnchor])
cat("\n")
}
### SET ANCHOR PROTEINS END
############################################################### EXPRESSION ANALYSIS ###############################################################
# create paired experiemntal design()
if(userOptions$ECorrelatedSamples){
eset <- createPairedExpDesign(eset)
}
# add filters etc to adjusted expressionSet
# update expDesign of intAdjObj$esetAd
if(exists("intAdjObj")){
fData(intAdjObj$esetAdj) <- fData(eset)
pData(intAdjObj$esetAdj) <- pData(eset)
exprs(intAdjObj$esetAdj) <- exprs(intAdjObj$esetAdj)[,colnames(exprs(eset))]
}
### non-pairwise stat test
statMethod <- c("")
if(userOptions$SNonPairWiseStatTest) statMethod <- c("all")
if(userOptions$SRawDataAnalysis){ # No Normalization
esetNorm <- eset
if(exists("intAdjObj")) intAdjObj$esetAdjNorm <- intAdjObj$esetAdj
}else{
method <- c("global","median")
# norm based on sum if norm anchor is specified
if(sum(fData(eset)$isNormAnchor) < nrow(eset)) method <- c("global","sum")
esetNorm <- sqNormalize(eset, method=method)
if(exists("intAdjObj")) intAdjObj$esetAdjNorm <- sqNormalize(intAdjObj$esetAdj, method=method )
}
### add pseudo (baseline) intensity
baselineIntensity <- getBaselineIntensity(as.vector(unlist(exprs(esetNorm)[,1])),promille=5)
exprs(esetNorm)[ is.na(exprs(esetNorm)) | (exprs(esetNorm) <= 0) ] <- 0
exprs(esetNorm) <- exprs(esetNorm) + baselineIntensity
if(exists("intAdjObj")){
baselineIntensity <- getBaselineIntensity(as.vector(unlist(exprs(intAdjObj$esetAdjNorm)[,1])),promille=5)
exprs(intAdjObj$esetAdjNorm)[ is.na(exprs(intAdjObj$esetAdjNorm)) | (exprs(intAdjObj$esetAdjNorm) <= 0) ] <- 0
exprs(intAdjObj$esetAdjNorm) <- exprs(intAdjObj$esetAdjNorm) + baselineIntensity
}
if((fileType == "ProgenesisProtein") | (fileType == "MaxQuantProteinGroup")){
fData(esetNorm)$isFiltered <- fData(esetNorm)$isFiltered | isDecoy(fData(esetNorm)$proteinName)
sqaProtein <- safeQuantAnalysis(esetNorm, method=statMethod, fcThrs=userOptions$ratioCutOff)
}else if((fileType == "ScaffoldTMT") && is.na(userOptions$scaffoldPTMSpectrumReportFile)){
# roll-up protein level
cat("INFO: ROLL-UP PROTEIN LEVEL\n")
fData(esetNorm)$isFiltered <- fData(esetNorm)$isFiltered | isDecoy(fData(esetNorm)$proteinName)
# correct TMT ratios
if(userOptions$TAdjustRatios){
fData(intAdjObj$esetAdjNorm)$isFiltered <- fData(esetNorm)$isFiltered
intAdjObjProt <- intAdjObj
intAdjObjProt$esetAdjNorm <- rollUp(intAdjObj$esetAdjNorm,featureDataColumnName= c("proteinName"))
sqaProtein <- safeQuantAnalysis(rollUp(esetNorm,featureDataColumnName= c("proteinName")), method=statMethod,intensityAdjustmentObj=intAdjObjProt, fcThrs=userOptions$ratioCutOff )
}else{
sqaProtein <- safeQuantAnalysis(rollUp(esetNorm,featureDataColumnName= c("proteinName")), method=statMethod , fcThrs=userOptions$ratioCutOff)
}
fData(sqaProtein$eset)$isFiltered <- fData(sqaProtein$eset)$isFiltered | isDecoy(fData(sqaProtein$eset)$proteinName) | (fData(sqaProtein$eset)$nbPeptides < userOptions$minNbPeptidesPerProt)
}else{
# roll-up peptide level
cat("INFO: ROLL-UP PEPTIDE LEVEL\n")
# correct TMT ratios
if(userOptions$TAdjustRatios){
cat("WARN: Ratio correction not yet implemented in this anlysis mode \n")
}
esetPeptide <- rollUp(esetNorm,featureDataColumnName= c("peptide","ptm"))
# fdr filter
# replace qValues by rollUp level qValues ()
esetPeptide <- addIdQvalues(esetPeptide)
if(fileType == "ScaffoldTMT"){
fData(esetPeptide)$isFiltered <- fData(esetPeptide)$isFiltered | (fData(esetPeptide)$nbPeptides < userOptions$minNbPeptidesPerProt)
}else{
# update filter to exclude peptide level hight qValues
fData(esetPeptide)$isFiltered <- fData(esetPeptide)$isFiltered | (fData(esetPeptide)$idQValue > userOptions$fdrCutoff) | (fData(esetPeptide)$nbPeptides < userOptions$minNbPeptidesPerProt)
}
if(userOptions$proteinQuant){
cat("INFO: ROLL-UP PROTEIN LEVEL\n")
esetProtein <- rollUp(esetPeptide,featureDataColumnName= c("proteinName"))
esetProtein <- addIdQvalues(esetProtein)
if(fileType == "ScaffoldTMT"){
fData(esetProtein)$isFiltered <- fData(esetProtein)$isFiltered | isDecoy(fData(esetProtein)$proteinName) | (fData(esetProtein)$nbPeptides < userOptions$minNbPeptidesPerProt)
}else{
fData(esetProtein)$isFiltered <- fData(esetProtein)$isFiltered | (fData(esetProtein)$idQValue > userOptions$fdrCutoff) | isDecoy(fData(esetProtein)$proteinName) | (fData(esetProtein)$nbPeptides < userOptions$minNbPeptidesPerProt)
}
sqaProtein <- safeQuantAnalysis(esetProtein, method=statMethod, fcThrs=userOptions$ratioCutOff)
}
fData(esetPeptide)$isFiltered <- fData(esetPeptide)$isFiltered | isDecoy(fData(esetPeptide)$proteinName)
sqaPeptide <- safeQuantAnalysis(esetPeptide, method=statMethod, fcThrs=userOptions$ratioCutOff)
fData(esetNorm)$isFiltered <- fData(esetNorm)$isFiltered | isDecoy(fData(esetNorm)$proteinName) | (fData(esetNorm)$nbPeptides < userOptions$minNbPeptidesPerProt)
if(userOptions$top3 & userOptions$proteinQuant){
cat("INFO: ROLL-UP TOP3\n")
esetTop3 <- rollUp(esetPeptide,featureDataColumnName= c("proteinName"), method="top3")
}
}
### IBAQ
if(userOptions$iBAQ & userOptions$proteinQuant){
cat("INFO: CALCULATING IBAQ VALUES\n")
if(exists("proteinDB")){
esetIBAQ <- getIBAQEset(sqaProtein$eset, proteinDB=proteinDB)
}else{
cat("ERROR: proteinDB NOT FOUND NO iBAQ VALUES CALCULATED\n")
}
}
### EXPRESSION ANALYSIS END
############################################################### EXPORTS ###############################################################
cat("INFO: PREPARING EXPORTS","\n")
#### SET WORKING DIR
if(!file.exists(userOptions$outputDir)) dir.create(userOptions$outputDir)
if(userOptions$verbose) cat("INFO: CREATED DIRECTORY", userOptions$outputDir,"\n")
#### SET WORKING DIR
##I/O: set export file paths
userOptions$pdfFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,".pdf",sep=""))
userOptions$peptideTsvFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_PEPTIDE.tsv",sep=""))
userOptions$proteinTsvFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_PROTEIN.tsv",sep=""))
userOptions$paramsFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_SQ_PARAMS.TXT",sep=""))
userOptions$rDataFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_SQ.rData",sep=""))
############################### GRAPHICS
# plot protein or peptide level results
if(exists("sqaProtein")){
sqaDisp <- sqaProtein
lab <- "Protein"
}else{
sqaDisp <- sqaPeptide
lab <- "Peptide"
}
### only disp. a subset for some plots
rowSelEset <- 1:nrow(eset) %in% sample(nrow(eset),min(c(2000,nrow(eset))) ,replace=F)
rowSelSqaDisp <- 1:nrow(sqaDisp$eset) %in% sample(nrow(sqaDisp$eset),min(c(2000,nrow(sqaDisp$eset))) ,replace=F)
pdf(userOptions$pdfFile)
parDefault <- par()
CONDITIONCOLORS <- .getConditionColors(esetNorm)
### EXPDESIGN PLOT
plotExpDesign(esetNorm, version=VERSION)
### EXPDESIGN PLOT END
### IDENTIFICATION PLOTS
if(userOptions$verbose) cat("INFO: IDENTIFICATION PLOTS \n")
par(mfrow=c(2,2))
#.idOverviewPlots()
#@ NOT CRAN COMPATIBLE
.idOverviewPlots(userOptions=userOptions
,esetNorm=esetNorm
,fileType=fileType
,sqaPeptide= ifelse(exists("sqaPeptide"),list(sqaPeptide),list(NA))[[1]]# HACK to pass check
,sqaProtein= ifelse(exists("sqaProtein"),list(sqaProtein),list(NA))[[1]] # HACK to pass check
)
if(fileType %in% c("ProgenesisFeature","ProgenesisPeptide")){
par(mfrow=c(3,2))
.idPlots(eset, selection=c(1,3), main="Feature Level", qvalueThrs=userOptions$fdrCutoff, userOptions=userOptions)
if(exists("sqaPeptide")) .idPlots(sqaPeptide$eset, selection=c(1,3), main="Peptide Level", qvalueThrs=userOptions$fdrCutoff)
if(exists("sqaProtein")) .idPlots(sqaProtein$eset, selection=c(1,3), main="Protein Level", qvalueThrs=userOptions$fdrCutoff)
}
par(parDefault)
### IDENTIFICATIONS PLOTS END
### QUANT. QC PLOTS
if(userOptions$verbose) cat("INFO: QUANT QC. PLOTS \n")
### MASS ERROR
par(parDefault)
#if("pMassError" %in% names(fData(eset))){
if(fileType %in% c("ProgenesisFeature","ProgenesisPeptide")){
par(mfrow=c(2,1), mar=c(4.5,6.1,4.1,6.1))
plotPrecMassErrorDistrib(eset, pMassTolWindow=userOptions$precursorMassFilter)
plotPrecMassErrorVsScore(eset[rowSelEset,], pMassTolWindow=userOptions$precursorMassFilter)
par(parDefault)
}
layout(rbind(c(1,2), c(3,3)))
### missing values
missinValueBarplot(eset)
### total intensity sum
barplotMSSignal(eset)
par( mar=c(6.5,5.1,2.5,3.1))
cvBoxplot(sqaDisp$eset)
par(parDefault)
### CORRELATION PLOTS
### COR OR PAIRS PLOT. IF FEWER THAN X SAMPLES
if(ncol(sqaDisp$eset) < 8){
pairsAnnot(log10(exprs(sqaDisp$eset))[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered ,],textCol=as.character(CONDITIONCOLORS[pData(sqaDisp$eset)$condition,]))
}else{
.correlationPlot(log10(exprs(sqaDisp$eset))[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered,], labels=as.character(unique(pData(sqaDisp$eset)$condition)), textCol=as.character(CONDITIONCOLORS[pData(sqaDisp$eset)$condition,]))
}
### COR OR PAIRS PLOT. IF FEWER THAN X CONDITIONS
if(length(unique(pData(sqaDisp$eset)$condition)) < 8){
pairsAnnot(log10(getSignalPerCondition(sqaDisp$eset[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered,]))[,as.character(unique(pData(sqaDisp$eset)$condition)) ],textCol=as.character(CONDITIONCOLORS[as.character(unique(pData(sqaDisp$eset)$condition)),]))
}else{
.correlationPlot(log10(getSignalPerCondition(sqaDisp$eset[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered,]))[,as.character(unique(pData(sqaDisp$eset)$condition)) ],textCol=as.character(CONDITIONCOLORS[as.character(unique(pData(sqaDisp$eset)$condition)),]))
}
par(parDefault)
### TMT calibration mix
if(exists("intAdjObj")){
# plot adjusted ratios vs org ratio
# boxplot noise fraction
#if(ncol(sqaDisp$ratio) > 1) par(mfrow=c(2,2))
boxplot(intAdjObj$noiseFraction*100, border=ifelse(intAdjObj$selectedPairs,"blue","black")
, ylab="Noise Fraction (%)",xlab="Calibration Mix Pair", cex.axis=1.5,cex.lab=1.5)
if(ncol(sqaDisp$ratio) > 1) par(mfrow=c(2,2))
plotAdjustedVsNonAdjustedRatio(sqaDisp$ratio,sqaDisp$unAdjustedRatio)
par(parDefault)
}
### QUANT. QC PLOTS END
par(parDefault)
if(userOptions$verbose) cat("INFO: HEAT MAP \n")
hClustHeatMap(sqaDisp$eset[(1:nrow(sqaDisp$eset) %in% sample(nrow(sqaDisp$eset),min(c(nrow(sqaDisp$eset),10000)))) & !fData(sqaDisp$eset)$isFiltered,],main= paste(lab,"Level"))
### QUANT. STAT. PLOTS
### VAILD FEATURES VS. pValue/qValue
if(userOptions$verbose) cat("INFO: QUANT RES. PLOTS \n")
par(mfrow=c(1,2))
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=F
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=T
,isAdjusted=T
,ylab=paste(lab, "Counts")
,main="DOWN REGULATION"
)
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=T
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=F
,isAdjusted=T
,ylab=paste(lab, "Counts")
,main="UP REGULATION"
)
par(parDefault)
plotVolcano(sqaDisp
, main=paste(lab,"Level")
, ratioThrs= userOptions$ratioCutOff
, pValueThreshold= userOptions$deFdrCutoff
, adjusted = T)
if(userOptions$eBayes){
par(mfrow=c(1,2))
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=F
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=T
,isAdjusted=F
,ylab=paste(lab, "Counts")
,main="DOWN REGULATION"
)
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=T
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=F
,isAdjusted=F
,ylab=paste(lab, "Counts")
,main="UP REGULATION"
)
par(parDefault)
plotVolcano(sqaDisp
, main=paste(lab,"Level")
, ratioThrs= userOptions$ratioCutOff
, pValueThreshold= userOptions$deFdrCutoff
, adjusted = F)
par(mfrow=c(2,2))
if(nrow(CONDITIONCOLORS) > 4) par(mfrow=c(3,3))
.allpValueHist(sqaDisp)
plotQValueVsPValue(sqaDisp, lim=c(0,1))
par(parDefault)
}
### QUANT. STAT. PLOTS END
par(parDefault)
### SOME ADDITIONAL QC PLOTS
if(userOptions$addQC){
# if(exists("sqaPeptide")){
# plotXYDensity(fData(sqaPeptide$eset)$retentionTime,fData(sqaPeptide$eset)$pMassError, disp=c("")
# , xlab="Retention time (min)"
# , ylab="Precursor Mass Error (ppm)"
# , cex.axis=1.5
# , cex.lab=1.5)
if( all(c("retentionTime","pMassError") %in% names(fData(eset)) )){
plotXYDensity(fData(eset)$retentionTime,fData(eset)$pMassError, disp=c("")
, xlab="Retention time (min)"
, ylab="Precursor Mass Error (ppm)"
, cex.axis=1.5
, cex.lab=1.5)
abline(h=c(userOptions$precursorMassFilter[1],0,userOptions$precursorMassFilter[2]),lty=2, lwd=2)
# rt vs signal
sel <- 1:nrow(esetNorm) %in% sample(nrow(esetNorm),min(c(4000,nrow(esetNorm))) ,replace=F) & (!(fData(esetNorm)$proteinName %in% names(CALIBMIXRATIOS)))
plotRTNormSummary(esetNorm[sel,])
par(mfrow=c(2,2))
plotRTNorm(getRTNormFactors(esetNorm[sel,], minFeaturesPerBin=100),esetNorm[sel,])
par(parDefault)
}
par(mfrow=c(2,2))
#all ma plots
for(s in colnames(exprs(esetNorm))){
sel <- 1:nrow(esetNorm) %in% sample(nrow(esetNorm),min(c(4000,nrow(esetNorm))) ,replace=F) & (!(fData(esetNorm)$proteinName %in% names(CALIBMIXRATIOS)))
maPlot(esetNorm[sel,],sample=s)
}
par(parDefault)
}
cat("INFO: CREATED FILE ", userOptions$pdfFile,"\n")
graphics.off()
############################### GRAPHICS END
### TSV EXPORT
if(exists("sqaPeptide")){
selFDataCol <- c("peptide","proteinName","proteinDescription", "idScore","idQValue"
,"retentionTime", "ptm", "nbPtmsPerPeptide", "nbRolledFeatures" )
selFDataCol <- selFDataCol[selFDataCol %in% names(fData(sqaPeptide$eset))]
### add modif coord
if("motifX" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"motifX","modifCoord")
}
### add allAccessions
if("allAccessions" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"allAccessions")
}
### add ptmPeptide
if("ptmPeptide" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"ptmPeptide")
}
### add ptmLocProb
if("ptmLocProb" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"ptmLocProb")
}
### add ptmLocMascotConfidence
if("ptmLocMascotConfidence" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"ptmLocMascotConfidence")
}
cv <- sqaPeptide$cv
names(cv) <- paste("cv",names(cv),sep="_")
ratio <- sqaPeptide$ratio
if(length(names(ratio)) > 0 ) names(ratio) <- paste("log2ratio",names(ratio),sep="_")
pValue <- sqaPeptide$pValue
if(length(names(pValue)) > 0 ) names(pValue) <- paste("pValue",names(pValue),sep="_")
qValue <- sqaPeptide$qValue
if(length(names(qValue)) > 0 ) names(qValue) <- paste("qValue",names(qValue),sep="_")
medianSignalDf <- getSignalPerCondition(sqaPeptide$eset)
names(medianSignalDf) <- paste("medianInt",names(medianSignalDf),sep="_")
out <- cbind(
fData(sqaPeptide$eset)[,selFDataCol]
, exprs(sqaPeptide$eset)
, medianSignalDf
, cv
, ratio
, pValue
, qValue )[!fData(sqaPeptide$eset)$isFiltered,]
### add unadjusted ratios if TMT ratio correction
if(userOptions$TAdjustRatios){
unadjPeptideRatios <- sqaPeptide$unAdjustedRatio[!fData(sqaPeptide$eset)$isFiltered,]
names(unadjPeptideRatios) <- paste("log2_unadjRatio",names(sqaPeptide$ratio),sep="_")
out <- cbind(out,unadjPeptideRatios)
}
### paired expDesign ratio export
if("subject" %in% names(pData(sqaPeptide$eset))){
allRatios <- getRatios(sqaPeptide$eset,method="paired")[!fData(sqaPeptide$eset)$isFiltered,]
names(allRatios) <- paste("log2_pairedRatio",names(allRatios),sep="_")
out <- cbind(out,allRatios)
}
write.table(out
, file=userOptions$peptideTsvFilePath
, sep="\t"
, row.names=F
)
cat("INFO: CREATED FILE ", userOptions$peptideTsvFilePath,"\n")
}
if(exists("sqaProtein")){
selFDataCol <- c("proteinName","proteinDescription","idScore","idQValue","nbPeptides")
selFDataCol <- selFDataCol[selFDataCol %in% names(fData(sqaProtein$eset))]
### add allAccessions
if("allAccessions" %in% names(fData(sqaProtein$eset))){
selFDataCol <- c(selFDataCol,"allAccessions")
}
cv <- sqaProtein$cv
names(cv) <- paste("cv",names(cv),sep="_")
ratio <- sqaProtein$ratio
if(length(names(ratio)) > 0 ) names(ratio) <- paste("log2ratio",names(ratio),sep="_")
pValue <- sqaProtein$pValue
if(length(names(pValue)) > 0 ) names(pValue) <- paste("pValue",names(pValue),sep="_")
qValue <- sqaProtein$qValue
if(length(names(qValue)) > 0 ) names(qValue) <- paste("qValue",names(qValue),sep="_")
medianSignalDf <- getSignalPerCondition(sqaProtein$eset)
names(medianSignalDf) <- paste("medianInt",names(medianSignalDf),sep="_")
out <- cbind(
fData(sqaProtein$eset)[,selFDataCol]
, exprs(sqaProtein$eset)
, medianSignalDf
, cv
, ratio
, pValue
, qValue )[!fData(sqaProtein$eset)$isFiltered,]
# add median top3
if(exists("esetTop3")){
# medians
# tmpOut <- getSignalPerCondition(esetTop3)
# tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
# names(tmpOut) <- paste("medianInt_top3",names(tmpOut),sep="_")
tmpOut <- exprs(esetTop3)
tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
colnames(tmpOut) <- paste("top3",colnames(tmpOut),sep="_")
out <- cbind(out,tmpOut)
}
# add iBAQ
if(exists("esetIBAQ")){
# medians
# tmpOut <- getSignalPerCondition(esetIBAQ)
# tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
# names(tmpOut) <- paste("medianInt_top3",names(tmpOut),sep="_")
tmpOut <- exprs(esetIBAQ)
tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
colnames(tmpOut) <- paste("iBAQ",colnames(tmpOut),sep="_")
out <- cbind(out,tmpOut)
}
### add unadjusted ratios if TMT ratio correction
if(userOptions$TAdjustRatios){
unadjProteinRatios <- sqaProtein$unAdjustedRatio[!fData(sqaProtein$eset)$isFiltered,]
names(unadjProteinRatios) <- paste("log2_unadjRatio",names(sqaProtein$ratio),sep="_")
out <- cbind(out,unadjProteinRatios)
}
### paired expDesign ratio export
if("subject" %in% names(pData(sqaProtein$eset))){
allRatios <- getRatios(sqaProtein$eset,method="paired")[!fData(sqaProtein$eset)$isFiltered,]
names(allRatios) <- paste("log2_pairedRatio",names(allRatios),sep="_")
out <- cbind(out,allRatios)
}
write.table(out
, file=userOptions$proteinTsvFilePath
, sep="\t"
, row.names=F
)
cat("INFO: CREATED FILE ", userOptions$proteinTsvFilePath,"\n")
}
### TSV EXPORT END
### EXPORT PARAMS
write.table(data.frame(
param=row.names(data.frame(unlist(userOptions[names(userOptions)])))
,value=as.vector((unlist(userOptions[names(userOptions)])))
)
,file=userOptions$paramsFilePath
,sep="\t"
,row.names=F
,quote=F
)
cat("INFO: CREATED FILE ", userOptions$paramsFilePath,"\n")
### EXPORT PARAMS
### EXPORT RDATA
if(userOptions$isSaveRObject){
save.image(file=userOptions$rDataFilePath)
cat("INFO: CREATED FILE ", userOptions$rDataFilePath,"\n")
}
### EXPORT RDATA END
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R Package Documentation
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#!/usr/local/bin/Rscript
###
# 0) Update SHEBANG ('#!/usr/bin/Rscript') to match location of your R installation
# 1) INSTALL SafeQuant
# - or SET sqDirPath
# 2) INSTALL PACKAGES
# affy
# limma
# gplots
# seqinr
# corrplot
# optparse
# data.table
# Author: ahrnee-adm
###############################################################################
# TEST FILE
# /Users/ahrnee-adm/dev/R/workspace/SafeQuant/inst/testData/new/peptides1_FILTERED.csv /Volumes/pcf01\$/Schmidt_Group/Databases/SwissProt_Databases/s_human_d_201405.fasta
# /Users/ahrnee-adm/dev/R/workspace/SafeQuant/inst/testData/new/proteins1.csv
# /Users/ahrnee-adm/dev/R/workspace/SafeQuant/inst/testData/new/TMT_6-Plex_Scaffold_Raw_Export_Example.xls
############################################################### INIT ###############################################################
#### DEPENDANCIES
suppressWarnings(suppressPackageStartupMessages(library("affy", quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library("limma", quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(gplots, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(seqinr, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(corrplot, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(optparse, quiet=T)))
suppressWarnings(suppressPackageStartupMessages(library(data.table, quiet=T)))
sourceDirOSX <- "/Users/ahrnee-adm/dev/R/workspace/SafeQuant/R/"
sourceDirTPP <- "/import/bc2/home/pcf/ahrnee/R/SafeQuant/R/"
# first check if dev or tpp mode
if(file.exists(sourceDirOSX) | file.exists(sourceDirTPP)){
sourceDir <- ifelse(file.exists(sourceDirOSX),sourceDirOSX,sourceDirTPP)
source(paste(sourceDir,"ExpressionAnalysis.R",sep=""))
source(paste(sourceDir,"SafeQuantAnalysis.R",sep=""))
source(paste(sourceDir,"Graphics.R",sep=""))
source(paste(sourceDir,"IdentificationAnalysis.R",sep=""))
source(paste(sourceDir,"Parser.R",sep=""))
source(paste(sourceDir,"TMT.R",sep=""))
source(paste(sourceDir,"UserOptions.R",sep=""))
}else if("SafeQuant" %in% installed.packages()[,1]){ # used installed SafeQuant
cat("Loading SafeQuant Library \n")
library("SafeQuant")
}else{
stop("SafeQuant Package not installed\n")
}
VERSION <- "2.3.1"
### USER CMD LINE OPTIONS
userOptions <- getUserOptions(version=VERSION)
### USER CMD LINE OPTIONS END
if(userOptions$verbose) print(userOptions$proteinQuant)
### SUPRESS WARNINGS
if(!userOptions$verbose){
options(warn=-1)
}
#### DEPENDENCIES
if(userOptions$verbose) print(userOptions)
############################################################### PARSING ###############################################################
if(userOptions$verbose) cat("PARSING INPUT FILE \n")
# get file type
fileType <- .getFileType(userOptions$inputFile)
### Progenesis Export
if(fileType %in% c("ProgenesisProtein","ProgenesisFeature","ProgenesisPeptide")){
# default
expDesign <- getExpDesignProgenesisCsv(userOptions$inputFile)
# get user specified experimental design
if(!is.na(userOptions$expDesignTag)){
# user specified
expDesign <- expDesignTagToExpDesign(userOptions$expDesignTag,expDesign)
}
if(fileType == "ProgenesisProtein"){
cat("INFO: PARSING PROGENESIS PROTEIN EXPORT FILE ",userOptions$inputFile, "\n" )
eset <- parseProgenesisProteinCsv(file=userOptions$inputFile,expDesign=expDesign)
}else if(fileType == "ProgenesisPeptide"){
#"ProgenesisFeature"
cat("INFO: PARSING PROGENESIS PEPTIDE EXPORT FILE ",userOptions$inputFile, "\n" )
eset <- parseProgenesisPeptideMeasurementCsv(file=userOptions$inputFile,expDesign=expDesign, uniqueProteins=userOptions$FUniquePeptides)
}else{ #"ProgenesisFeature"
cat("INFO: PARSING PROGENESIS FEATURE EXPORT FILE ",userOptions$inputFile, "\n" )
eset <- parseProgenesisFeatureCsv(file=userOptions$inputFile,expDesign=expDesign)
}
# Scaffold Export (TMT data)
}else if(fileType == "ScaffoldTMT"){
cat("INFO: PARSING SCAFFOLD RAW EXPORT FILE ",userOptions$inputFile, "\n" )
# get default experimental design
# six plex or ten plex ?
# use default experimental design unless specified by the user
nbPlex <- .getNbPlex(userOptions$inputFile)
if(nbPlex == 6){
# 6-plex default: 1,2,3:4,5,6
expDesign <- data.frame(condition=paste("Condition",sort(rep(c(1,2),3)),sep=""),isControl=sort(rep(c(T,F),3),decreasing=T) )
}else{
# 10-plex default is "1,4,7,10:2,5,8:3,6,9"
expDesign <- data.frame(condition=paste("Condition",c(1,2,3,1,2,3,1,2,3,1),sep=""),isControl=c(T,F,F,T,F,F,T,F,F,T) )
}
eset <- parseScaffoldRawFile(file=userOptions$inputFile,expDesign=expDesign)
if(userOptions$TAdjustRatios){
#if((nbPlex == 10)){ # only possible for tmt-10 plex
nbCalMixSpectra <- sum( (fData(eset)$proteinName %in% names(CALIBMIXRATIOS)))
if(nbCalMixSpectra < 100) stop("Not enough Calibration Mix spectra were found: ",nbCalMixSpectra, "\n ")
cat("INFO: FOUND ", nbCalMixSpectra ," Calibration Mix spectra\n")
esetCalibMix <- .getCalibMixEset(eset)
# discard calibration mix proteins
eset <- eset[!(fData(eset)$proteinName %in% names(CALIBMIXRATIOS)),]
intAdjObj <- .intensityAdjustment(eset, esetCalibMix)
#}else{
# stop("Ratio Correction Not implemented for TMT 6-plex")
#}
}
# get user specified experimental design
if(!is.na(userOptions$expDesignTag)){
# user specified
expDesign <- expDesignTagToExpDesign(userOptions$expDesignTag,expDesign)
}
# eset <- parseScaffoldRawFile(file=userOptions$inputFile,expDesign=expDesign)
# apply specified experimental design
eset <- createExpressionDataset(expressionMatrix=exprs(eset)[,rownames(expDesign)],expDesign=expDesign,featureAnnotations=fData(eset))
if(!is.na(userOptions$scaffoldPTMSpectrumReportFile)){
cat("INFO: ADDING SCAFFOLD PTM ANNOTATIONS \n")
eset <- addScaffoldPTMFAnnotations(eset,userOptions$scaffoldPTMSpectrumReportFile)
}
}else if(fileType == "MaxQuantProteinGroup"){
# get user specified experimental design
if(!is.na(userOptions$expDesignTag)){
# user specified
expDesign <- expDesignTagToExpDesign(userOptions$expDesignTag,data.frame(condition=paste("Condition",1:1000),isControl=c(F,1000)) )
}else{
stop("Please Specify Experimental Design")
}
eset <- parseMaxQuantProteinGroupTxt(userOptions$inputFile,expDesign=expDesign, method="auc")
}else if(fileType == "GenericCSV"){
}else{
stop("Unknown File Type", userOptions$inputFile)
}
# test option, limit number of entries
if(userOptions$test){
eset <- eset[1:nrow(eset) %in% sample(1:min(300,c(nrow(eset))),replace=F),]
}
# parse .fasta file
if(!is.na(userOptions$proteinFastaFile)){
cat("INFO: PARSING PROTEIN SEQUENCE DB ",userOptions$proteinFastaFile, "\n" )
### read protein db
proteinDB <- read.fasta(userOptions$proteinFastaFile,seqtype = "AA",as.string = TRUE, set.attributes = FALSE)
# dirty fix check if ACs in Progenesis file are stripped
if(isStrippedACs(sample(fData(eset)$proteinName,100))){
cat("INFO: RE-FORMATTING ACCESSION NUMBERS\n")
names(proteinDB) <- stripACs(names(proteinDB))
}
}
############################################################### CREATE DATA MODEL ###############################################################
if(userOptions$verbose) print(eset)
if(userOptions$verbose) print(pData(eset))
if(userOptions$verbose) print(names(fData(eset)))
#### CREATE FEATURE DATA AND FILTER (pre-rollup)
# generic
filter <- data.frame(
con=isCon(fData(eset)$proteinName) # contaminants
,ac = !(grepl(userOptions$selectedProteinName,fData(eset)$proteinName,ignore.case=T)) # protein ac
)
# do not filter TMT data
if("pMassError" %in% names(fData(eset)) && (fileType != "ScaffoldTMT") ){
### applicable to Progenesis feature Exports
if(is.na(userOptions$precursorMassFilter)){ # if not user specified
# automatically get precursor limits, X * sd of 50% top scoring
userOptions$precursorMassFilter <- getMeanCenteredRange(fData(eset)$pMassError[fData(eset)$idScore > quantile(fData(eset)$idScore,na.rm=T)[3]],nbSd = 3)
filter <- cbind(filter, pMassError=
(fData(eset)$pMassError < userOptions$precursorMassFilter[1])
| (fData(eset)$pMassError > userOptions$precursorMassFilter[2]) # precursor mass tolerance
)
}
}
if("ptm" %in% names(fData(eset))){
# add motif-X and ptm coordinates
if(exists("proteinDB")){
cat("INFO: EXTRACTING PTM COORDINATES AND MOTIFS\n")
#format 1) progensis 2) scaffold
eset <- .addPTMCoord(eset,proteinDB,motifLength=6, isProgressBar=T,format= (fileType == "ScaffoldTMT") +1)
}
filter <- cbind(filter
, ptm = !(grepl(userOptions$selectedModifName,as.character(fData(eset)$ptm),ignore.case=T))
, nbPtmsPerPeptide = (fData(eset)$nbPtmsPerPeptide > userOptions$maxNbPtmsPerPeptide) )
}
if("peptide" %in% names(fData(eset))){
filter <- cbind(filter
, peptideLength =nchar(as.character(fData(eset)$peptide)) < userOptions$minPeptideLength
, charge = fData(eset)$charge == 1 # discard singly charged
)
}
if(!("nbPeptides" %in% names(fData(eset)))){
### set nb peptides per protein
eset <- setNbPeptidesPerProtein(eset)
}
filter <- cbind(filter,nbPeptides=(fData(eset)$nbPeptides < userOptions$minNbPeptidesPerProt))
# do not filter TMT data
#if(("idScore" %in% names(fData(eset))) && (fileType != "ScaffoldTMT")){
if(("idScore" %in% names(fData(eset)))){
eset <- addIdQvalues(eset)
filter <- cbind(filter,qvalue=fData(eset)$idQValue > userOptions$fdrCutoff)
}
# set pre-rollup filters
eset <- .setFilter(eset,filter=filter)
### make sure at least 1 feature pass the filter
if(sum(!fData(eset)$isFiltered,na.rm=T) == 0){
stop("CHECK FILTER SETTINGS. ALL FEATURES WERE FILTERED OUT")
}
#### CREATE FEATURE DATA AND FILTER END
### SET ANCHOR PROTEINS
fData(eset)$isNormAnchor <- grepl(userOptions$normAC,fData(eset)$proteinName)
if(userOptions$verbose){
cat("\nNB. ANCHOR PROTEINS: ")
cat(sum(fData(eset)$isNormAnchor))
cat("\n")
print(fData(eset)$proteinName[fData(eset)$isNormAnchor])
cat("\n")
}
### SET ANCHOR PROTEINS END
############################################################### EXPRESSION ANALYSIS ###############################################################
# create paired experiemntal design()
if(userOptions$ECorrelatedSamples){
eset <- createPairedExpDesign(eset)
}
# add filters etc to adjusted expressionSet
# update expDesign of intAdjObj$esetAd
if(exists("intAdjObj")){
fData(intAdjObj$esetAdj) <- fData(eset)
pData(intAdjObj$esetAdj) <- pData(eset)
exprs(intAdjObj$esetAdj) <- exprs(intAdjObj$esetAdj)[,colnames(exprs(eset))]
}
### non-pairwise stat test
statMethod <- c("")
if(userOptions$SNonPairWiseStatTest) statMethod <- c("all")
if(userOptions$SRawDataAnalysis){ # No Normalization
esetNorm <- eset
if(exists("intAdjObj")) intAdjObj$esetAdjNorm <- intAdjObj$esetAdj
}else{
method <- c("global","median")
# norm based on sum if norm anchor is specified
if(sum(fData(eset)$isNormAnchor) < nrow(eset)) method <- c("global","sum")
esetNorm <- sqNormalize(eset, method=method)
if(exists("intAdjObj")) intAdjObj$esetAdjNorm <- sqNormalize(intAdjObj$esetAdj, method=method )
}
### add pseudo (baseline) intensity
baselineIntensity <- getBaselineIntensity(as.vector(unlist(exprs(esetNorm)[,1])),promille=5)
exprs(esetNorm)[ is.na(exprs(esetNorm)) | (exprs(esetNorm) <= 0) ] <- 0
exprs(esetNorm) <- exprs(esetNorm) + baselineIntensity
if(exists("intAdjObj")){
baselineIntensity <- getBaselineIntensity(as.vector(unlist(exprs(intAdjObj$esetAdjNorm)[,1])),promille=5)
exprs(intAdjObj$esetAdjNorm)[ is.na(exprs(intAdjObj$esetAdjNorm)) | (exprs(intAdjObj$esetAdjNorm) <= 0) ] <- 0
exprs(intAdjObj$esetAdjNorm) <- exprs(intAdjObj$esetAdjNorm) + baselineIntensity
}
if((fileType == "ProgenesisProtein") | (fileType == "MaxQuantProteinGroup")){
fData(esetNorm)$isFiltered <- fData(esetNorm)$isFiltered | isDecoy(fData(esetNorm)$proteinName)
sqaProtein <- safeQuantAnalysis(esetNorm, method=statMethod, fcThrs=userOptions$ratioCutOff)
}else if((fileType == "ScaffoldTMT") && is.na(userOptions$scaffoldPTMSpectrumReportFile)){
# roll-up protein level
cat("INFO: ROLL-UP PROTEIN LEVEL\n")
fData(esetNorm)$isFiltered <- fData(esetNorm)$isFiltered | isDecoy(fData(esetNorm)$proteinName)
# correct TMT ratios
if(userOptions$TAdjustRatios){
fData(intAdjObj$esetAdjNorm)$isFiltered <- fData(esetNorm)$isFiltered
intAdjObjProt <- intAdjObj
intAdjObjProt$esetAdjNorm <- rollUp(intAdjObj$esetAdjNorm,featureDataColumnName= c("proteinName"))
sqaProtein <- safeQuantAnalysis(rollUp(esetNorm,featureDataColumnName= c("proteinName")), method=statMethod,intensityAdjustmentObj=intAdjObjProt, fcThrs=userOptions$ratioCutOff )
}else{
sqaProtein <- safeQuantAnalysis(rollUp(esetNorm,featureDataColumnName= c("proteinName")), method=statMethod , fcThrs=userOptions$ratioCutOff)
}
fData(sqaProtein$eset)$isFiltered <- fData(sqaProtein$eset)$isFiltered | isDecoy(fData(sqaProtein$eset)$proteinName) | (fData(sqaProtein$eset)$nbPeptides < userOptions$minNbPeptidesPerProt)
}else{
# roll-up peptide level
cat("INFO: ROLL-UP PEPTIDE LEVEL\n")
# correct TMT ratios
if(userOptions$TAdjustRatios){
cat("WARN: Ratio correction not yet implemented in this anlysis mode \n")
}
esetPeptide <- rollUp(esetNorm,featureDataColumnName= c("peptide","ptm"))
# fdr filter
# replace qValues by rollUp level qValues ()
esetPeptide <- addIdQvalues(esetPeptide)
if(fileType == "ScaffoldTMT"){
fData(esetPeptide)$isFiltered <- fData(esetPeptide)$isFiltered | (fData(esetPeptide)$nbPeptides < userOptions$minNbPeptidesPerProt)
}else{
# update filter to exclude peptide level hight qValues
fData(esetPeptide)$isFiltered <- fData(esetPeptide)$isFiltered | (fData(esetPeptide)$idQValue > userOptions$fdrCutoff) | (fData(esetPeptide)$nbPeptides < userOptions$minNbPeptidesPerProt)
}
if(userOptions$proteinQuant){
cat("INFO: ROLL-UP PROTEIN LEVEL\n")
esetProtein <- rollUp(esetPeptide,featureDataColumnName= c("proteinName"))
esetProtein <- addIdQvalues(esetProtein)
if(fileType == "ScaffoldTMT"){
fData(esetProtein)$isFiltered <- fData(esetProtein)$isFiltered | isDecoy(fData(esetProtein)$proteinName) | (fData(esetProtein)$nbPeptides < userOptions$minNbPeptidesPerProt)
}else{
fData(esetProtein)$isFiltered <- fData(esetProtein)$isFiltered | (fData(esetProtein)$idQValue > userOptions$fdrCutoff) | isDecoy(fData(esetProtein)$proteinName) | (fData(esetProtein)$nbPeptides < userOptions$minNbPeptidesPerProt)
}
sqaProtein <- safeQuantAnalysis(esetProtein, method=statMethod, fcThrs=userOptions$ratioCutOff)
}
fData(esetPeptide)$isFiltered <- fData(esetPeptide)$isFiltered | isDecoy(fData(esetPeptide)$proteinName)
sqaPeptide <- safeQuantAnalysis(esetPeptide, method=statMethod, fcThrs=userOptions$ratioCutOff)
fData(esetNorm)$isFiltered <- fData(esetNorm)$isFiltered | isDecoy(fData(esetNorm)$proteinName) | (fData(esetNorm)$nbPeptides < userOptions$minNbPeptidesPerProt)
if(userOptions$top3 & userOptions$proteinQuant){
cat("INFO: ROLL-UP TOP3\n")
esetTop3 <- rollUp(esetPeptide,featureDataColumnName= c("proteinName"), method="top3")
}
}
### IBAQ
if(userOptions$iBAQ & userOptions$proteinQuant){
cat("INFO: CALCULATING IBAQ VALUES\n")
if(exists("proteinDB")){
esetIBAQ <- getIBAQEset(sqaProtein$eset, proteinDB=proteinDB)
}else{
cat("ERROR: proteinDB NOT FOUND NO iBAQ VALUES CALCULATED\n")
}
}
### EXPRESSION ANALYSIS END
############################################################### EXPORTS ###############################################################
cat("INFO: PREPARING EXPORTS","\n")
#### SET WORKING DIR
if(!file.exists(userOptions$outputDir)) dir.create(userOptions$outputDir)
if(userOptions$verbose) cat("INFO: CREATED DIRECTORY", userOptions$outputDir,"\n")
#### SET WORKING DIR
##I/O: set export file paths
userOptions$pdfFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,".pdf",sep=""))
userOptions$peptideTsvFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_PEPTIDE.tsv",sep=""))
userOptions$proteinTsvFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_PROTEIN.tsv",sep=""))
userOptions$paramsFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_SQ_PARAMS.TXT",sep=""))
userOptions$rDataFilePath <- file.path(userOptions$outputDir, paste(userOptions$resultsFileLabel,"_SQ.rData",sep=""))
############################### GRAPHICS
# plot protein or peptide level results
if(exists("sqaProtein")){
sqaDisp <- sqaProtein
lab <- "Protein"
}else{
sqaDisp <- sqaPeptide
lab <- "Peptide"
}
### only disp. a subset for some plots
rowSelEset <- 1:nrow(eset) %in% sample(nrow(eset),min(c(2000,nrow(eset))) ,replace=F)
rowSelSqaDisp <- 1:nrow(sqaDisp$eset) %in% sample(nrow(sqaDisp$eset),min(c(2000,nrow(sqaDisp$eset))) ,replace=F)
pdf(userOptions$pdfFile)
parDefault <- par()
CONDITIONCOLORS <- .getConditionColors(esetNorm)
### EXPDESIGN PLOT
plotExpDesign(esetNorm, version=VERSION)
### EXPDESIGN PLOT END
### IDENTIFICATION PLOTS
if(userOptions$verbose) cat("INFO: IDENTIFICATION PLOTS \n")
par(mfrow=c(2,2))
#.idOverviewPlots()
#@ NOT CRAN COMPATIBLE
.idOverviewPlots(userOptions=userOptions
,esetNorm=esetNorm
,fileType=fileType
,sqaPeptide= ifelse(exists("sqaPeptide"),list(sqaPeptide),list(NA))[[1]]# HACK to pass check
,sqaProtein= ifelse(exists("sqaProtein"),list(sqaProtein),list(NA))[[1]] # HACK to pass check
)
if(fileType %in% c("ProgenesisFeature","ProgenesisPeptide")){
par(mfrow=c(3,2))
.idPlots(eset, selection=c(1,3), main="Feature Level", qvalueThrs=userOptions$fdrCutoff, userOptions=userOptions)
if(exists("sqaPeptide")) .idPlots(sqaPeptide$eset, selection=c(1,3), main="Peptide Level", qvalueThrs=userOptions$fdrCutoff)
if(exists("sqaProtein")) .idPlots(sqaProtein$eset, selection=c(1,3), main="Protein Level", qvalueThrs=userOptions$fdrCutoff)
}
par(parDefault)
### IDENTIFICATIONS PLOTS END
### QUANT. QC PLOTS
if(userOptions$verbose) cat("INFO: QUANT QC. PLOTS \n")
### MASS ERROR
par(parDefault)
#if("pMassError" %in% names(fData(eset))){
if(fileType %in% c("ProgenesisFeature","ProgenesisPeptide")){
par(mfrow=c(2,1), mar=c(4.5,6.1,4.1,6.1))
plotPrecMassErrorDistrib(eset, pMassTolWindow=userOptions$precursorMassFilter)
plotPrecMassErrorVsScore(eset[rowSelEset,], pMassTolWindow=userOptions$precursorMassFilter)
par(parDefault)
}
layout(rbind(c(1,2), c(3,3)))
### missing values
missinValueBarplot(eset)
### total intensity sum
barplotMSSignal(eset)
par( mar=c(6.5,5.1,2.5,3.1))
cvBoxplot(sqaDisp$eset)
par(parDefault)
### CORRELATION PLOTS
### COR OR PAIRS PLOT. IF FEWER THAN X SAMPLES
if(ncol(sqaDisp$eset) < 8){
pairsAnnot(log10(exprs(sqaDisp$eset))[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered ,],textCol=as.character(CONDITIONCOLORS[pData(sqaDisp$eset)$condition,]))
}else{
.correlationPlot(log10(exprs(sqaDisp$eset))[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered,], labels=as.character(unique(pData(sqaDisp$eset)$condition)), textCol=as.character(CONDITIONCOLORS[pData(sqaDisp$eset)$condition,]))
}
### COR OR PAIRS PLOT. IF FEWER THAN X CONDITIONS
if(length(unique(pData(sqaDisp$eset)$condition)) < 8){
pairsAnnot(log10(getSignalPerCondition(sqaDisp$eset[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered,]))[,as.character(unique(pData(sqaDisp$eset)$condition)) ],textCol=as.character(CONDITIONCOLORS[as.character(unique(pData(sqaDisp$eset)$condition)),]))
}else{
.correlationPlot(log10(getSignalPerCondition(sqaDisp$eset[rowSelSqaDisp & !fData(sqaDisp$eset)$isFiltered,]))[,as.character(unique(pData(sqaDisp$eset)$condition)) ],textCol=as.character(CONDITIONCOLORS[as.character(unique(pData(sqaDisp$eset)$condition)),]))
}
par(parDefault)
### TMT calibration mix
if(exists("intAdjObj")){
# plot adjusted ratios vs org ratio
# boxplot noise fraction
#if(ncol(sqaDisp$ratio) > 1) par(mfrow=c(2,2))
boxplot(intAdjObj$noiseFraction*100, border=ifelse(intAdjObj$selectedPairs,"blue","black")
, ylab="Noise Fraction (%)",xlab="Calibration Mix Pair", cex.axis=1.5,cex.lab=1.5)
if(ncol(sqaDisp$ratio) > 1) par(mfrow=c(2,2))
plotAdjustedVsNonAdjustedRatio(sqaDisp$ratio,sqaDisp$unAdjustedRatio)
par(parDefault)
}
### QUANT. QC PLOTS END
par(parDefault)
if(userOptions$verbose) cat("INFO: HEAT MAP \n")
hClustHeatMap(sqaDisp$eset[(1:nrow(sqaDisp$eset) %in% sample(nrow(sqaDisp$eset),min(c(nrow(sqaDisp$eset),10000)))) & !fData(sqaDisp$eset)$isFiltered,],main= paste(lab,"Level"))
### QUANT. STAT. PLOTS
### VAILD FEATURES VS. pValue/qValue
if(userOptions$verbose) cat("INFO: QUANT RES. PLOTS \n")
par(mfrow=c(1,2))
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=F
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=T
,isAdjusted=T
,ylab=paste(lab, "Counts")
,main="DOWN REGULATION"
)
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=T
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=F
,isAdjusted=T
,ylab=paste(lab, "Counts")
,main="UP REGULATION"
)
par(parDefault)
plotVolcano(sqaDisp
, main=paste(lab,"Level")
, ratioThrs= userOptions$ratioCutOff
, pValueThreshold= userOptions$deFdrCutoff
, adjusted = T)
if(userOptions$eBayes){
par(mfrow=c(1,2))
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=F
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=T
,isAdjusted=F
,ylab=paste(lab, "Counts")
,main="DOWN REGULATION"
)
plotNbValidDeFeaturesPerFDR(sqaDisp,
upRegulated=T
,log2RatioCufOff=log2(userOptions$ratioCutOff)
,pvalRange=c(0,0.15)
,pvalCutOff=userOptions$deFdrCutoff
,isLegend=F
,isAdjusted=F
,ylab=paste(lab, "Counts")
,main="UP REGULATION"
)
par(parDefault)
plotVolcano(sqaDisp
, main=paste(lab,"Level")
, ratioThrs= userOptions$ratioCutOff
, pValueThreshold= userOptions$deFdrCutoff
, adjusted = F)
par(mfrow=c(2,2))
if(nrow(CONDITIONCOLORS) > 4) par(mfrow=c(3,3))
.allpValueHist(sqaDisp)
plotQValueVsPValue(sqaDisp, lim=c(0,1))
par(parDefault)
}
### QUANT. STAT. PLOTS END
par(parDefault)
### SOME ADDITIONAL QC PLOTS
if(userOptions$addQC){
# if(exists("sqaPeptide")){
# plotXYDensity(fData(sqaPeptide$eset)$retentionTime,fData(sqaPeptide$eset)$pMassError, disp=c("")
# , xlab="Retention time (min)"
# , ylab="Precursor Mass Error (ppm)"
# , cex.axis=1.5
# , cex.lab=1.5)
if( all(c("retentionTime","pMassError") %in% names(fData(eset)) )){
plotXYDensity(fData(eset)$retentionTime,fData(eset)$pMassError, disp=c("")
, xlab="Retention time (min)"
, ylab="Precursor Mass Error (ppm)"
, cex.axis=1.5
, cex.lab=1.5)
abline(h=c(userOptions$precursorMassFilter[1],0,userOptions$precursorMassFilter[2]),lty=2, lwd=2)
# rt vs signal
sel <- 1:nrow(esetNorm) %in% sample(nrow(esetNorm),min(c(4000,nrow(esetNorm))) ,replace=F) & (!(fData(esetNorm)$proteinName %in% names(CALIBMIXRATIOS)))
plotRTNormSummary(esetNorm[sel,])
par(mfrow=c(2,2))
plotRTNorm(getRTNormFactors(esetNorm[sel,], minFeaturesPerBin=100),esetNorm[sel,])
par(parDefault)
}
par(mfrow=c(2,2))
#all ma plots
for(s in colnames(exprs(esetNorm))){
sel <- 1:nrow(esetNorm) %in% sample(nrow(esetNorm),min(c(4000,nrow(esetNorm))) ,replace=F) & (!(fData(esetNorm)$proteinName %in% names(CALIBMIXRATIOS)))
maPlot(esetNorm[sel,],sample=s)
}
par(parDefault)
}
cat("INFO: CREATED FILE ", userOptions$pdfFile,"\n")
graphics.off()
############################### GRAPHICS END
### TSV EXPORT
if(exists("sqaPeptide")){
selFDataCol <- c("peptide","proteinName","proteinDescription", "idScore","idQValue"
,"retentionTime", "ptm", "nbPtmsPerPeptide", "nbRolledFeatures" )
selFDataCol <- selFDataCol[selFDataCol %in% names(fData(sqaPeptide$eset))]
### add modif coord
if("motifX" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"motifX","modifCoord")
}
### add allAccessions
if("allAccessions" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"allAccessions")
}
### add ptmPeptide
if("ptmPeptide" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"ptmPeptide")
}
### add ptmLocProb
if("ptmLocProb" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"ptmLocProb")
}
### add ptmLocMascotConfidence
if("ptmLocMascotConfidence" %in% names(fData(sqaPeptide$eset))){
selFDataCol <- c(selFDataCol,"ptmLocMascotConfidence")
}
cv <- sqaPeptide$cv
names(cv) <- paste("cv",names(cv),sep="_")
ratio <- sqaPeptide$ratio
if(length(names(ratio)) > 0 ) names(ratio) <- paste("log2ratio",names(ratio),sep="_")
pValue <- sqaPeptide$pValue
if(length(names(pValue)) > 0 ) names(pValue) <- paste("pValue",names(pValue),sep="_")
qValue <- sqaPeptide$qValue
if(length(names(qValue)) > 0 ) names(qValue) <- paste("qValue",names(qValue),sep="_")
medianSignalDf <- getSignalPerCondition(sqaPeptide$eset)
names(medianSignalDf) <- paste("medianInt",names(medianSignalDf),sep="_")
out <- cbind(
fData(sqaPeptide$eset)[,selFDataCol]
, exprs(sqaPeptide$eset)
, medianSignalDf
, cv
, ratio
, pValue
, qValue )[!fData(sqaPeptide$eset)$isFiltered,]
### add unadjusted ratios if TMT ratio correction
if(userOptions$TAdjustRatios){
unadjPeptideRatios <- sqaPeptide$unAdjustedRatio[!fData(sqaPeptide$eset)$isFiltered,]
names(unadjPeptideRatios) <- paste("log2_unadjRatio",names(sqaPeptide$ratio),sep="_")
out <- cbind(out,unadjPeptideRatios)
}
### paired expDesign ratio export
if("subject" %in% names(pData(sqaPeptide$eset))){
allRatios <- getRatios(sqaPeptide$eset,method="paired")[!fData(sqaPeptide$eset)$isFiltered,]
names(allRatios) <- paste("log2_pairedRatio",names(allRatios),sep="_")
out <- cbind(out,allRatios)
}
write.table(out
, file=userOptions$peptideTsvFilePath
, sep="\t"
, row.names=F
)
cat("INFO: CREATED FILE ", userOptions$peptideTsvFilePath,"\n")
}
if(exists("sqaProtein")){
selFDataCol <- c("proteinName","proteinDescription","idScore","idQValue","nbPeptides")
selFDataCol <- selFDataCol[selFDataCol %in% names(fData(sqaProtein$eset))]
### add allAccessions
if("allAccessions" %in% names(fData(sqaProtein$eset))){
selFDataCol <- c(selFDataCol,"allAccessions")
}
cv <- sqaProtein$cv
names(cv) <- paste("cv",names(cv),sep="_")
ratio <- sqaProtein$ratio
if(length(names(ratio)) > 0 ) names(ratio) <- paste("log2ratio",names(ratio),sep="_")
pValue <- sqaProtein$pValue
if(length(names(pValue)) > 0 ) names(pValue) <- paste("pValue",names(pValue),sep="_")
qValue <- sqaProtein$qValue
if(length(names(qValue)) > 0 ) names(qValue) <- paste("qValue",names(qValue),sep="_")
medianSignalDf <- getSignalPerCondition(sqaProtein$eset)
names(medianSignalDf) <- paste("medianInt",names(medianSignalDf),sep="_")
out <- cbind(
fData(sqaProtein$eset)[,selFDataCol]
, exprs(sqaProtein$eset)
, medianSignalDf
, cv
, ratio
, pValue
, qValue )[!fData(sqaProtein$eset)$isFiltered,]
# add median top3
if(exists("esetTop3")){
# medians
# tmpOut <- getSignalPerCondition(esetTop3)
# tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
# names(tmpOut) <- paste("medianInt_top3",names(tmpOut),sep="_")
tmpOut <- exprs(esetTop3)
tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
colnames(tmpOut) <- paste("top3",colnames(tmpOut),sep="_")
out <- cbind(out,tmpOut)
}
# add iBAQ
if(exists("esetIBAQ")){
# medians
# tmpOut <- getSignalPerCondition(esetIBAQ)
# tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
# names(tmpOut) <- paste("medianInt_top3",names(tmpOut),sep="_")
tmpOut <- exprs(esetIBAQ)
tmpOut <- tmpOut[match(rownames(out),rownames(tmpOut)), ]
colnames(tmpOut) <- paste("iBAQ",colnames(tmpOut),sep="_")
out <- cbind(out,tmpOut)
}
### add unadjusted ratios if TMT ratio correction
if(userOptions$TAdjustRatios){
unadjProteinRatios <- sqaProtein$unAdjustedRatio[!fData(sqaProtein$eset)$isFiltered,]
names(unadjProteinRatios) <- paste("log2_unadjRatio",names(sqaProtein$ratio),sep="_")
out <- cbind(out,unadjProteinRatios)
}
### paired expDesign ratio export
if("subject" %in% names(pData(sqaProtein$eset))){
allRatios <- getRatios(sqaProtein$eset,method="paired")[!fData(sqaProtein$eset)$isFiltered,]
names(allRatios) <- paste("log2_pairedRatio",names(allRatios),sep="_")
out <- cbind(out,allRatios)
}
write.table(out
, file=userOptions$proteinTsvFilePath
, sep="\t"
, row.names=F
)
cat("INFO: CREATED FILE ", userOptions$proteinTsvFilePath,"\n")
}
### TSV EXPORT END
### EXPORT PARAMS
write.table(data.frame(
param=row.names(data.frame(unlist(userOptions[names(userOptions)])))
,value=as.vector((unlist(userOptions[names(userOptions)])))
)
,file=userOptions$paramsFilePath
,sep="\t"
,row.names=F
,quote=F
)
cat("INFO: CREATED FILE ", userOptions$paramsFilePath,"\n")
### EXPORT PARAMS
### EXPORT RDATA
if(userOptions$isSaveRObject){
save.image(file=userOptions$rDataFilePath)
cat("INFO: CREATED FILE ", userOptions$rDataFilePath,"\n")
}
### EXPORT RDATA END
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