HeatmapRankings {GeneSelector} | R Documentation

## Heatmap of genes and rankings

### Description

Cluster genes and repeated rankings simultaneously based on a data matrix of ranks whose columns correspond to rankings and whose rows correspond to genes. The main goal is to compare different ranking procedures and to examine whether there are differences among them. Up to now, the Euclidean metric and complete-linkage clustering is used to generate the trees.

### Usage

    HeatmapRankings(RR, ind=1:100)

### Arguments

`RR` | An object of class RepeatedRanking, usually generated from a call to MergeMethods.
`ind` | A vector of gene indices whose ranks are used to generate the heatmap. The number of elements should not be too large (not greater than 500) due to high time- and memory requirements.

### Value

A heatmap (plot).

### Author(s)

Martin Slawski
Anne-Laure Boulesteix

### References

Gentleman, R., Carey, V.J., Huber, W., Irizarry, R.A., Dudoit, S. (editors), 2005.
Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Chapter 10: Visualizing Data. Springer, N.Y.

### Examples

    ## Load toy gene expression data
    data(toydata)
    ### class labels
    yy <- toydata[1,]
    ### gene expression
    xx <- toydata[-1,]
    ### Get Rankings from five different statistics
    ordinaryT <- RankingTstat(xx, yy, type="unpaired")
    baldilongT <- RankingBaldiLong(xx, yy, type="unpaired")
    samT <- RankingSam(xx, yy, type="unpaired")
    wilc <- RankingWilcoxon(xx, yy, type="unpaired")
    wilcebam <- RankingWilcEbam(xx, yy, type="unpaired")
    merged <- MergeMethods(list(ordinaryT, baldilongT, samT, wilc, wilcebam))
    ### plot the heatmap
    HeatmapRankings(merged, ind=1:100)

[Package GeneSelector version 2.30.0 Index]