plotMDS {limma} | R Documentation

## Multidimensional scaling plot of microarray data

### Description

Plot the sample relations based on MDS.

### Usage

    plotMDS(x, top=500, labels=colnames(x), col=NULL, cex=1, dim.plot=c(1,2), ndim=max(dim.plot),...)

### Arguments

`x` | any data object which can be coerced to a matrix, such as `ExpressionSet` or `EList`.
`top` | number of top genes used to calculate pairwise distances.
`labels` | character vector of sample names or labels. If `x` has no column names, then defaults the index of the samples.
`col` | numeric or character vector of colors for the plotting characters.
`cex` | numeric vector of plot symbol expansions.
`dim.plot` | which two dimensions should be plotted, numeric vector of length two.
`ndim` | number of dimensions in which data is to be represented
`...` | any other arguments are passed to `plot`.

### Details

This function is a variation on the usual multdimensional scaling (or principle coordinate) plot, in that a distance measure particularly appropriate for the microarray context is used. The distance between each pair of samples (columns) is the root-mean-square deviation for the top `top` genes which best distinguish that pair of samples. That is, Euclidean distance is used, but for a different gene subset for each pair of samples.

See `text` for possible values for `col` and `cex`.

### Value

A plot is created on the current graphics device.

### Author(s)

Di Wu and Gordon Smyth

### See Also

`cmdscale`

An overview of diagnostic functions available in LIMMA is given in 09.Diagnostics.

### Examples

    # Simulate gene expression data for 1000 probes and 6 microarrays.
    # Samples are in two groups
    # First 50 probes are differentially expressed in second group
    sd <- 0.3*sqrt(4/rchisq(1000,df=4))
    x <- matrix(rnorm(1000*6,sd=sd),1000,6)
    rownames(x) <- paste("Gene",1:1000)
    x[1:50,4:6] <- x[1:50,4:6] + 2
    # without labels, indexes of samples are plotted.
    plotMDS(x,  col=c(rep("black",3), rep("red",3)) )
    # with labels as groups, group indicators are plotted.
    plotMDS(x,  col=c(rep("black",3), rep("red",3)), labels= c(rep("Grp1",3), rep("Grp2",3)))

[Package limma version 2.18.3 Index]