##  plotMD.R
 
 plotMD <- function(object,...) UseMethod("plotMD")
 

 plotMD.RGList <- function(object, column=1, array=NULL, xlab="A", ylab="M", main=colnames(object)[column], status=object$genes$Status, zero.weights=FALSE, ...)

 #	Mean-difference plot with color coding for controls
 #	Created by Gordon Smyth 7 April 2003 and James Wettenhall 27 June 2003.

 #	Last modified 7 June 2015.

 {

 	if(!is.null(array)) column <- array

 	object <- MA.RG(object[,column])

 	plotMD.MAList(object=object,column=1,xlab=xlab,ylab=ylab,main=main,status=status,zero.weights=zero.weights,...)

 }
 

 plotMD.MAList <- function(object, column=1, array=NULL, xlab="A", ylab="M", main=colnames(object)[column], status=object$genes$Status, zero.weights=FALSE, ...)

 #	Mean-difference plot with color coding for controls
 #	Gordon Smyth 7 April 2003, James Wettenhall 27 June 2003.

 #	Last modified 7 June 2015.

 {

 	if(!is.null(array)) column <- array

 	A <- as.matrix(object$A)[,column]
 	M <- as.matrix(object$M)[,column]
 	if(!zero.weights && !is.null(object$weights)) {
 		w <- as.matrix(object$weights)[,column]
 		M[ is.na(w) | (w <= 0) ] <- NA
 	}
 	plotWithHighlights(x=A,y=M,xlab=xlab,ylab=ylab,main=main,status=status,...)
 }
 

 plotMD.MArrayLM <- function(object, column=ncol(object), coef=NULL, xlab="Average log-expression", ylab="log-fold-change", main=colnames(object)[column], status=object$genes$Status, ...)

 #	Mean-difference plot with color coding for controls
 #	Gordon Smyth 7 April 2003, James Wettenhall 27 June 2003.

 #	Last modified 15 July 2024.

 {

 	if(!is.null(coef)) column <- coef

 	if(is.null(object$Amean)) stop("Amean component is absent.")

 	logFC <- as.matrix(object$coefficients)[,column]

 
 #	Ignoring zero.weights because weights have already been incorporated into the coefficient standard errors.
 #	logFC should already be NA whenever object$stdev.unscaled is, so logFC with infinite or non-estimable standard errors are already not plotted.
 

 	if(is(status,"TestResults"))
 		if(ncol(status) > 1L)
 			if(ncol(status == ncol(object)))
 				status <- status[,column]
 			else
 				stop("status has multiple columns")

 	plotWithHighlights(x=object$Amean,y=logFC,xlab=xlab,ylab=ylab,main=main,status=status,...)
 }
 

 plotMD.EListRaw <- function(object, column=1, array=NULL, xlab="Average log-expression", ylab="Expression log-ratio (this sample vs others)", main=colnames(object)[column], status=object$genes$Status, zero.weights=FALSE, ...)

 #	Mean-difference plot with color coding for controls
 #	Gordon Smyth

 #	Created 22 Oct 2014. Last modified 7 June 2015.

 {

 	if(!is.null(array)) column <- array

 	if(!is.null(object$Eb)) object$E <- object$E-object$Eb
 	object$E <- log2(object$E)
 	object <- new("EList",unclass(object))
 	plotMD(object, column=column, xlab=xlab, ylab=ylab, main=main, status=status, zero.weights=zero.weights, ...)
 }
 

 plotMD.EList <- function(object, column=1, array=NULL, xlab="Average log-expression", ylab="Expression log-ratio (this sample vs others)", main=colnames(object)[column], status=object$genes$Status, zero.weights=FALSE, ...)

 #	Mean-difference plot with color coding for controls
 #	Gordon Smyth 7 April 2003, James Wettenhall 27 June 2003.
 #	Last modified 14 April 2015.
 {

 	if(!is.null(array)) column <- array

 	E <- as.matrix(object$E)
 	if(ncol(E) < 2L) stop("Need at least two columns")
 
 #	Convert column to integer if not already
 	j <- 1:ncol(E)
 	names(j) <- colnames(E)
 	column <- j[column[1]]
 
 	AveOfOthers <- rowMeans(E[,-column,drop=FALSE],na.rm=TRUE)
 	Diff <- E[,column]-AveOfOthers
 	Mean <- (E[,column]+AveOfOthers)/2
 
 	if(!zero.weights && !is.null(object$weights)) {
 		w <- as.matrix(object$weights)[,column]
 		Diff[ is.na(w) | (w <= 0) ] <- NA
 	}
 
 	plotWithHighlights(x=Mean,y=Diff,xlab=xlab,ylab=ylab,main=main,status=status,...)
 }
 
 plotMD.default <- function(object, column=1, xlab="Average log-expression", ylab="Expression log-ratio (this sample vs others)", main=colnames(object)[column], status=NULL, ...)
 #	Mean-difference plot with color coding for controls
 #	Gordon Smyth 7 April 2003, James Wettenhall 27 June 2003.
 #	Last modified 14 April 2015.
 {
 #	Data is assumed to be single-channel
 	object <- as.matrix(object)
 	ncolumns <- ncol(object)
 	if(ncolumns<2) stop("Need at least two columns")
 	column <- as.integer(column[1L])
 	Ave <- rowMeans(object[,-column,drop=FALSE],na.rm=TRUE)
 	y <- object[,column]-Ave
 	x <- (object[,column]+Ave)/2
 
 	plotWithHighlights(x,y,xlab=xlab,ylab=ylab,main=main,status=status, ...)
 }
 
 
 mdplot <- function(x,columns=c(1,2),xlab="Mean",ylab="Difference",main=NULL,...)
 #	Mean-difference plot of two columns of a matrix
 #	Gordon Smyth
 #	16 March 2005. Last modified 13 April 2015.
 {
 	x <- as.matrix(x)
 	columns <- as.integer(columns)[1:2]
 	d <- x[,columns[2]]-x[,columns[1]]
 	m <- (x[,columns[1]]+x[,columns[2]])/2
 	if(is.null(main)) {
 		cn <- colnames(x)[columns]
 		if(is.null(cn)) cn <- paste("Column",columns)
 		main <- paste(cn[2],"vs",cn[1])
 	}
 	plotWithHighlights(x=m,y=d,xlab=xlab,ylab=ylab,main=main,...)
 }