R/plotCtBoxes.R

In HTqPCR: Automated analysis of high-throughput qPCR data

plotCtBoxes <-
function(q,
	cards	= TRUE,
	xlab	= "",
	col,
	main	= NULL,
	names,
	stratify	= "type",
	mar	= c(7,4,3,1),
	...)
{
	# Get the data
	if (class(q)=="matrix") {
		data <- q[,cards]	
	} else if (class(q)=="qPCRset") {
		data <- exprs(q)[,cards,drop=FALSE]
	} else {
		stop("Data is of wrong format, only qPCRset and matrices are supported.\n")
	}
 # Plotting parameters
 if (missing(col))
 		col <- colorRampPalette(brewer.pal(11, "Spectral"))(ncol(data))
 if (missing(names))
 		names <- sampleNames(q)[cards]
 par(mar=mar, ...)
 # Plotting stritified by spot type, gene class or simple version
 if (!is.null(stratify)) {
 	groups <- list(dat=c(data), sample=rep(sampleNames(q)[cards], each=nrow(data)))
 	# Divide the data
 	 if (stratify=="type") {
 	 	feat <- as.factor(featureType(q))
 	 	groups[["strat"]] <- rep(feat, ncol(data))
 			n <- length(levels(feat))
 			lev <- levels(feat)
 		} else if (stratify=="class") {
 			feat <- as.factor(featureClass(q))
 			if (length(feat)==0)
				stop("No featureClass available for object 'q'")
 	 	groups[["strat"]] <- rep(feat, ncol(data))
 			n <- length(levels(feat))
 			lev <- levels(feat)
		} else {
			stop(paste("Plot type \'", stratify, "\'isn't implemented\n"))
		}
		# The actual plotting
	 boxplot(dat~strat+sample, data=groups, col=rep(col, each=n), xlab=xlab, main=main, names=NA, ...)
	 mtext(1, at=seq(length(lev)-(length(lev)-1)/2, n*ncol(data), n), text=sampleNames(q)[cards], line=0.5)
	 mtext(1, at=1:(n*ncol(data)), text=gsub(" ", "\n", rep(lev), ncol(data)), line=2, las=2)
	} else {
	 boxplot(data, col=col, xlab=xlab, main=main, names=names, ...)
	}
}