consensusHeatmap {piano} | R Documentation

## Heatmap of top consensus gene sets

### Description

Based on multiple result objects from the `runGSA` function, this function computes the consensus scores, based on rank aggregation, for each directionality class and produces a heatmap plot of the results.

### Usage

    consensusHeatmap(resList, method = "median", cutoff = 5,
      adjusted = FALSE, plot = TRUE, ncharLabel = 25,
      cellnote = "consensusScore", columnnames = "full", colorkey = TRUE,
      colorgrad = NULL, cex = NULL)

### Arguments

`resList` | a list where each element is an object of class `GSAres`, as returned by the `runGSA` function.
`method` | a character string selecting the method, either `"mean"`, `"median"`, `"Borda"` or `"Copeland"`.
`cutoff` | the maximum consensus score of a gene set, in any of the directionality classes, to be included in the heatmap.
`adjusted` | a logical, whether to use adjusted p-values or not. Note that if `runGSA` was run with the argument `adjMethod="none"`, the adjusted p-values will be equal to the original p-values.
`plot` | whether or not to draw the heatmap. Setting `plot=FALSE` allows you to save the heatmap as a matrix without plotting it.
`ncharLabel` | the number of characters to include in the row labels.
`cellnote` | a character string selecting the information to be printed inside each cell of the heatmap. Either `"consensusScore"`, `"medianPvalue"`, `"nGenes"` or `"none"`. Note that the actual heatmap will always be based on the consensus scores.
`columnnames` | either `"full"` (default) or `"abbr"` to use full or abbreviated column labels. Will save some space for the heatmap if set to `"abbr"`
`colorkey` | a logical (default `TRUE`), whether or not to display the colorkey. Will save some space for the heatmap if turned off.
`colorgrad` | a character vector giving the color names to use in the heatmap.
`cex` | a numeric, to control the text size.

### Details

This function computes the consensus gene set scores for each directionality class based on the results (gene set p-values) listed in `resList`, using the `consensusScores` function. For each class, only the `GSAres` objects in `resList` that contain p-values for that class are used as a basis for the rank aggregation. Hence, if not all classes are covered by at least 2 `GSAres` objects in the list, the `consensusHeatmap` function will not work. The results are displayed in a heatmap showing the consensus scores.

### Value

A list, returned invisibly, containing the matrix of consensus scores as represented in the heatmap as well as the matrix of corresponding median p-values and the matrix of number of genes in each gene set (inlcuding the subset of up and down regulated genes for the mixed directional classes).

### Author(s)

Leif Varemo piano.rpkg@gmail.com and Intawat Nookaew piano.rpkg@gmail.com

### See Also

piano, `runGSA`

### Examples

       # Load some example GSA results:
       data(gsa_results)

       # Consensus heatmap:
       dev.new(width=10,height=10)
       consensusHeatmap(resList=gsa_results)

       # Store the output:
       dev.new(width=10,height=10)
       ch <- consensusHeatmap(resList=gsa_results)

       # Access the median p-values for gene set s1:
       ch$pMat["s1",]

[Package piano version 2.0.2 Index]