clusterVisualization {transcriptogramer} | R Documentation

## Displays graphs of the differentially expressed clusters

### Description

This method uses the RedeR package to display graphs of the differentially expressed clusters.

### Usage

    clusterVisualization(object, maincomp = FALSE, connected = FALSE,
      host = "127.0.0.1", port = 9091, clusters = NULL,
      onlyGenesInDE = FALSE, colors = NULL)

    ## S4 method for signature 'Transcriptogram'
    clusterVisualization(object,
      maincomp = FALSE, connected = FALSE, host = "127.0.0.1",
      port = 9091, clusters = NULL, onlyGenesInDE = FALSE,
      colors = NULL)

### Arguments

`object` | An object of class Transcriptogram.
`maincomp` | Logical value, set as TRUE if you want to display only the main component of each cluster. The default value of this argument is FALSE.
`connected` | Logical value, set as TRUE if you want to display only connected nodes. The default value of this argument is FALSE.
`host` | The domain name of the machine that is running the RedeR XML-RPC server.
`port` | An integer specifying the port on which the XML-RPC server should listen.
`clusters` | An integer vector specifying the clusters to be displayed, if NULL, all clusters will be displayed.
`onlyGenesInDE` | Logical value, set as TRUE to use only the genes in the DE slot. Set as FALSE to use all the genes referring to the positions in the clusters slot. The default value of this argument is FALSE.
`colors` | Color vector used to distinguish the clusters. If NULL, the rainbow palette will be used to generate the colors. The color vector must contain a color for each cluster.

### Details

RedeR package requirements: Java Runtime Environment (>= 6).

### Value

This function returns an object of the RedPort Class.

### Author(s)

Diego Morais

### See Also

differentiallyExpressed, transcriptogramPreprocess, GSE9988, GPL570, Hs900, association, transcriptogramStep1, transcriptogramStep2, RedPort

### Examples

    transcriptogram <- transcriptogramPreprocess(association, Hs900, 50)
    ## Not run:
    transcriptogram <- transcriptogramStep1(transcriptogram, GSE9988, GPL570)
    transcriptogram <- transcriptogramStep2(transcriptogram)
    levels <- c(rep(FALSE, 3), rep(TRUE, 3))
    transcriptogram <- differentiallyExpressed(transcriptogram, levels, 0.01,
    DEsymbols)
    rdp <- clusterVisualization(transcriptogram)

    ## End(Not run)

[Package transcriptogramer version 1.6.0 Index]