GSAheatmap {piano} | R Documentation

## Heatmap of top significant gene sets

### Description

This function selects the top scoring (most significant) gene sets for each directionality class and produces a heatmap plot of the results.

### Usage

    GSAheatmap(gsaRes, cutoff = 5, adjusted = FALSE, ncharLabel = 25,
      cellnote = "pvalue", columnnames = "full", colorkey = TRUE,
      colorgrad = NULL, cex = NULL)

### Arguments

`gsaRes` | an object of class `GSAres`, as returned from `runGSA()`.
`cutoff` | an integer n, so that the top n gene sets (plus possible ties) in each directionality class will 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.
`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 `"pvalue"`, `"rank"`, `"nGenes"` or `"none"`. Note that the actual heatmap will always be based on the gene set ranks.
`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 selects the top significant gene sets in each directionality class and draws a heatmap of the results. It provides a quick summary alternative to the `GSAsummaryTable` function or the `networkPlot`.

### Value

A list, returned invisibly, containing the matrix of p-values (adjusted or non-adjusted depending on the settings) as represented in the heatmap as well as the matrix of corresponding ranks 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`, `GSAsummaryTable`, `networkPlot2`, `exploreGSAres`

### Examples

       # Load example input data to GSA:
       data("gsa_input")

       # Load gene set collection:
       gsc <- loadGSC(gsa_input$gsc)

       # Run gene set analysis:
       gsares <- runGSA(geneLevelStats=gsa_input$pvals , directions=gsa_input$directions,
                        gsc=gsc, nPerm=500)

       # Make heatmap:
       dev.new(width=10,height=10)
       GSAheatmap(gsares)

[Package piano version 2.0.2 Index]