detectionPValues <- function(x,...) UseMethod("detectionPValues")
 
 detectionPValues.EListRaw <- function(x,status=NULL,...)
 #	Detection p-values from negative controls for EListRaw
 #	Gordon Smyth
 #	Created 13 June 2016
 {
 	if(is.null(status)) status <- x$genes$Status
 	detectionPValues(x=x$E, status=status, ...)
 }
 
 detectionPValues.default <- function(x, status, negctrl="negative",...)
 #	Detection p-values from negative controls
 #	Gordon Smyth

 #	Created 13 June 2016.  Last modified 14 June 2016.

 {
 	x <- as.matrix(x)
 
 #	Identify negative control rows
 	if(missing(status) || is.null(status)) stop("need to specify status vector")
 	isneg <- as.integer(status==negctrl)
 	notneg <- 1L-isneg
 	nneg <- sum(isneg)
 
 #	Count the number of negative controls greater than each value
 #	cs1 counts number of negative controls >= the observed value
 #	cs2 counts number of negative controls > the observed value
 #	By taking the average of cs1 and cs2, we count ties as 1/2
 	DetectionPValue <- x
 	cs1 <- cs2 <- rep_len(0,length.out=nrow(x))
 	for (j in 1:ncol(x)) {
 		o1 <- order(x[,j],isneg,decreasing=TRUE)
 		o2 <- order(x[,j],notneg,decreasing=TRUE)
 		cs1[o1] <- cumsum(isneg[o1])
 		cs2[o2] <- cumsum(isneg[o2])

 		DetectionPValue[,j] <- cs1+cs2

 	}
 
 #	Convert to p-values
 	DetectionPValue/(2*nneg)
 }