clusterVisualization-method: Displays graphs of the differentially expressed clusters

In transcriptogramer: Transcriptional analysis based on transcriptograms

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 method 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)

transcriptogramer documentation built on Nov. 8, 2020, 8:17 p.m.