Nothing
plotTreeDataMDS <-
function(dataList, main="Tree MDS Comparisons", calcMLE=TRUE, mleTitles=NULL, dotColors=NULL,
dotSizes=NULL, showNames=FALSE, returnCoords=FALSE, data=NULL){
### Fix any old arguments
if(!is.null(data)){
warning("'data' is deprecated. It has been replaced with dataList. View the help files for details.")
dataList <- data
}
if(missing(dataList))
stop("At least 1 valid data set is required.")
if(is.null(dotColors))
dotColors <- c("red", "orange", "blue", "green", "yellow", "purple")
if(is.null(dotSizes))
dotSizes <- c(1, 2)
if(length(dotSizes) != 2)
stop("dotSizes must contain 2 integers.")
numGrps <- length(dataList)
### Add group names if we dont have them
if(is.null(names(dataList))){
grpNames <- paste("Data Set", 1:numGrps)
}else{
grpNames <- names(dataList)
}
### If we don't have enough colors, make a new set of colors
if(length(dotColors) < numGrps)
dotColors <- rainbow(numGrps)
sizes <- NULL
colors <- NULL
if(calcMLE){
mleDotSizes <- rep(0, numGrps)
mleColors <- rep(0, numGrps)
}
### Figure out colors and sizes for all points
for(i in 1:numGrps){
tempData <- dataList[[i]]
colors <- c(colors, rep(dotColors[i], ncol(tempData)))
sizes <- c(sizes, rep(dotSizes[1], ncol(tempData)))
if(calcMLE){
mleColors[i] <- dotColors[i]
mleDotSizes[i] <- dotSizes[2]
}
}
if(calcMLE){
colors <- c(colors, mleColors, "black")
sizes <- c(sizes, mleDotSizes, dotSizes[2])
}
### Get point positions and plot
tData <- t(mergeDataSets(dataList, calcMLE))
loc <- cmdscale(dist(tData), k=2)
x <- loc[,1]
y <- -loc[,2]
plot(x, y, pch=19, xlab="MDS 1", ylab="MDS 2", pty="s", col=colors, cex=sizes, main=main)
### Add mle titles if we aren't showing all the names
if(calcMLE && !showNames){
grpNames <- c(grpNames, "Combined MLE")
text(x[(nrow(tData) - numGrps):nrow(tData)], y[(nrow(tData) - numGrps):nrow(tData)], grpNames, pos=3, cex=.75)
}
### Add the names of the samples
if(showNames)
text(x, y, rownames(tData), pos=3, cex=.75)
if(returnCoords)
return(list(x=x, y=y))
}
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