plotCluster {clusterSeq} | R Documentation

## Plots data from clusterings.

### Description

Given clusterings and expression data, plots representative expression data for each clustering.

### Usage

    plotCluster(cluster, cD, sampleSize = 1000)

### Arguments

`cluster` | A list object defining the clusters, produced by `makeClusters` or `makeClustersFF`.
`cD` | The data object used to produce the clusters.
`sampleSize` | The maximum number of genes that will be ploted.

### Details

Expression data are normalised and rescaled before plotting.

### Value

Plotting function.

### Author(s)

Thomas J Hardcastle

### See Also

`makeClusters` `makeClustersFF`

### Examples

    # load in analysed countData object
    data(cD.ratThymus, package = "clusterSeq")

    # estimate likelihoods of dissimilarity on reduced set
    aM <- associatePosteriors(cD.ratThymus[1:1000,])

    # make clusters from dissimilarity data
    sX <- makeClusters(aM, cD.ratThymus, threshold = 0.5)

    # plot first six clusters
    par(mfrow = c(2,3))
    plotCluster(sX[1:6], cD.ratThymus)

[Package clusterSeq version 1.4.0 Index]