R/decidetestsDGE.R

In edgeR: Empirical Analysis of Digital Gene Expression Data in R

#  decideTestsDGE.R

decideTests.DGEExact <- decideTests.DGELRT <- function(object,adjust.method="BH",p.value=0.05,lfc=0,...)
{
	decideTestsDGE(object=object,adjust.method=adjust.method,p.value=p.value,lfc=lfc)
}

decideTestsDGE <- function(object,adjust.method="BH",p.value=0.05,lfc=0)
#	Accept or reject hypothesis tests across genes and contrasts
#	edgeR team. Original author was Davis McCarthy.
#	Created 15 August 2010. Last modified 15 July 2018.
{
#	Check object class
	if( !(is(object,"DGEExact") || is(object,"DGELRT")) ) stop("Need DGEExact or DGELRT object")

#	Apply multiple testing
	p <- object$table$PValue
	p <- p.adjust(p, method=adjust.method)
	isDE <- as.integer(p < p.value)

#	Extract logFC
	logFC <- object$table$logFC

#	Check for F-test with multiple logFC columns
	FTest <- is.null(logFC)

#	With multiple contrasts, apply lfc threshold to maximum logFC
	if(FTest) {
		if(lfc>0) {
			coef.col <- grep("^logFC",colnames(object$table))
			logFC <- object$table[,coef.col]
			SmallFC <- rowSums(abs(logFC) >= lfc) == 0
			isDE[SmallFC] <- 0L
		}

#	With single contrast, apply directionality and lfc threshold
	} else {
		isDE[isDE & logFC<0] <- -1L
		SmallFC <- (abs(logFC) < lfc)
		isDE[SmallFC] <- 0L
	}

#	Assemble TestResults object
	isDE <- matrix(isDE, ncol=1)
	row.names(isDE) <- row.names(object)
	colnames(isDE) <- paste(rev(object$comparison),collapse="-")

#	Record possible values
	if(FTest) {
		attr(isDE,"levels") <- c(0L,1L)
		attr(isDE,"labels") <- c("NotSig","Sig")
	} else {
		attr(isDE,"levels") <- c(-1L,0L,1L)
		attr(isDE,"labels") <- c("Down","NotSig","Up")
	}		

	new("TestResults", isDE)
}