[BioC] plotDensity in a multiple-figure enviroment

[Adaikalavan Ramasamy]

There must be more elegant way of doing this but here is my solution

my.plotDensity <- function (mat, ylab = "density", xlab = "x", type =
"l", col = 1:6, ...){

    x.density <- apply(mat, 2, density)
    all.x <- do.call("cbind", lapply(x.density, function(x) x$x))
    all.y <- do.call("cbind", lapply(x.density, function(x) x$y))

    for(i in 1:ncol(mat)){
         
         plot( all.x[ ,i], all.y[ ,i], 
               xlim=range(all.x), ylim=range(all.y),
               main=colnames(mat)[i],
               ylab=ylab, xlab=xlab, type=type, col=col, ... )
    }

    invisible(list(all.x = all.x, all.y = all.y))
}


# Usage 

m <- matrix( rnorm(1000*6)^2, nc=6 )  # simulate
m[,5] <- 5 + m[,5]                    # make array 5 an outlier
colnames(m) <- paste("Array", 1:6)

par(mfrow=c(2,3))
my.plotDensity(m)


Regards, Adai


On Mon, 2005-03-07 at 07:33 +0000, zhihua li wrote:
> Hi all.
> I have a microarry gene expression data in the form of a matrix, where rows 
> represent genes and columns represent conditions. plotDensity in "affy" 
> package can draw a density distribution curve for each column and put them 
> in a single plot. I wanna draw a density distribution curve for each 
> colomn, put them each in a seperate plot, and put all these plots in a 
> single page.  What should I do?
> Thanks to all!
> 
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