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#' Prepare differential expression testing results for spike-in analysis
#'
#' @param exDat list, contains input data and stores analysis results
#'
#' @details
#' This function wraps the edgeR differential expression testing package for
#' datType = "count" or uses the limma package for differential expression
#' testing if datType = "array". Alternatively, for count data only, if
#' correctly formatted DE test results are provided,
#' then geneExprTest will bypass DE testing (with reduced runtime).
#'
#' @examples
#'
#' data(SEQC.Example)
#'
#' exDat <- initDat(datType="array", isNorm=FALSE,
#' exTable=UHRR.HBRR.arrayDat,
#' filenameRoot="testRun", sample1Name="UHRR",
#' sample2Name="HBRR", erccmix="RatioPair",
#' erccdilution = 1, spikeVol = 50,
#' totalRNAmass = 2.5*10^(3), choseFDR=0.01)
#'
#' exDat <- est_r_m(exDat)
#'
#' exDat <- dynRangePlot(exDat)
#'
#' exDat <- geneExprTest(exDat)
#'
#' @export
geneExprTest <- function(exDat){
datType <- exDat$sampleInfo$datType
isNorm <- exDat$sampleInfo$isNorm
choseFDR <- exDat$sampleInfo$choseFDR
cnt <- exDat$Transcripts
designMat <- exDat$designMat
sampleInfo <- exDat$sampleInfo
info <- designMat
allpvalFile <- paste(sampleInfo$filenameRoot,"All.Pvals.csv",sep=".")
pvalERCC <- paste(sampleInfo$filenameRoot, "ERCC Pvals.csv",sep=" ")
if(datType == "array"){
if(is.null(choseFDR)){
getPThresh<- function(){
cat("\nFDR is NULL, to continue with LODR estimation\n")
readline("Enter the threshold P-value: ")
}
exDat$Results$p.thresh <- as.numeric(getPThresh())
}
if (file.exists(allpvalFile) == TRUE){
deRes <- read.csv(allpvalFile)
#if (!("qvals" %in% names(deRes))){
deRes$qvals <- qvalue(deRes$Pval)$qvalues
# print(summary(deRes$qvals))
#}
if(any(deRes$qvals<choseFDR)){
p.thresh<-max(deRes$Pval[deRes$qvals<choseFDR])
}
cat(paste("\n Will use existing differential expression test",
"results for analysis.\n",
"Delete", allpvalFile, "if you want to repeat",
"differential \nexpression testing\n"))
}else{
exDat <- testDEArray(exDat)
cat("\nFinished DE testing\n")
p.thresh <- exDat$Results$p.thresh
}
}
if(datType == "count"){
# set initial p.thresh
p.thresh<-.1
# First 3 columns of allpvalFile must contain Feature, Pval, and qvals
# Decide to reuse results or run testDE
if (file.exists(allpvalFile) == TRUE){
deRes <- read.csv(allpvalFile)
#if (("qvals" %in% names(deRes)) == FALSE){
deRes$qvals <- qvalue(deRes$Pval)$qvalues
#}
if(any(deRes$qvals<choseFDR)){
p.thresh<-max(deRes$Pval[deRes$qvals<choseFDR])
}
cat(paste("\n Found differential expression test results, will use",
" \nexisting P-values and Q-values for analysis.\n",
"Delete", allpvalFile, "if you want to repeat",
"differential \n",
"expression testing or view dispersion plots\n"))
}else{
if (isNorm == TRUE){
cat(paste0("\nedgeR DE Testing for RNA-Seq requires count",
" (integer) data.\n",
"To estimate AUC and LODR for normalized RNA-Seq",
"data\nthe file '",sampleInfo$filenameRoot,
".All.Pvals.csv' is required with columns for\n",
"'Feature','MnSignal','Pval', and 'Fold'\n"))
return(exDat)
}else{
cat("\nStarting differential expression tests\n")
exDat <- suppressWarnings(testDECount(sampleInfo, exDat,
cnt=cnt,
info=info))
deRes <- read.csv(allpvalFile)
deRes$qvals <- qvalue(deRes$Pval)$qvalues
if(any(deRes$qvals<choseFDR)){
p.thresh<-max(deRes$Pval[deRes$qvals<choseFDR])
}
}
}
}
if(is.null(exDat$Figures$dispPlot)){
cat(paste("\nDE testing results supplied without companion dispersion\n",
"plot. Dispersion plot is unavailable to print.\n"))
}
cat("\nThreshold P-value\n")
cat(p.thresh,"\n")
if (p.thresh > .1){
cat(paste("Threshold P-value is high for the chosen FDR of ",
as.character(choseFDR)))
cat(paste("\nThe sample comparison indicates a large amount of \n",
"differential expression in the measured transcript \n",
"populations\n"))
}
exDat$Results$p.thresh <- p.thresh
return(exDat)
}
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