GOenrichment {GOSim} | R Documentation

## GO enrichment analysis

### Description

This function performs a GO enrichment analysis using topGO. It combines the two former functions "GOenrichment" and "analyzeCluster".

### Usage

    GOenrichment(genesOfInterest, allgenes, cutoff=0.01, method="elim")

### Arguments

`genesOfInterest` | character vector of Entrez gene IDs or vector of statistics (p-values, t-statistics, ...) named with entrez gene IDs
`allgenes` | character vector of Entrez gene IDs or vector of statistics named with entrez gene IDs
`cutoff` | significance cutoff for GO enrichment analysis
`method` | topGO method to use

### Details

If the parameters 'genesOfInterest' and 'allgenes' are both character vectors of Entrez gene IDs, Fisher's exact test is used. The Kolmogorov-Smirnov test can be used, if a score (e.g. p-value) for each gene is provided. For more details please refer to the topGO vignette.

### Value

`GOTerms` | list of significant GO terms and their description
`p.values` | vector of p-values for significant GO terms
`genes` | list of genes associated to each GO term

### Author(s)

Holger Froehlich

### References

Adrian Alexa, J\"org Rahnenf\"uhrer, Thomas Lengauer: Improved scoring of functional groups from gene expression data by decorrelating GO graph structure, Bioinformatics, 2006, 22(13):1600-1607

### See Also

`evaluateClustering`

### Examples

    	if(require(org.Hs.eg.db) & require(topGO)){
    		allgenes = sample(keys(org.Hs.egGO), 1000) # suppose these are all genes
    		allpvalues = runif(1000) # an these are their pvalues
    		names(allpvalues) = allgenes
    		GOenrichment(allpvalues[allpvalues<0.05], allpvalues) # GO enrichment analysis using Kolmogorov-Smirnov test
    	}

[Package GOSim version 1.28.0 Index]