clusterEvaluation {GOSim} | R Documentation

## Evaluate a given grouping of genes or GO terms.

### Description

Evaluate a given grouping of genes or terms with respect to their GO similarity.

### Usage

    evaluateClustering(clust, Sim)

### Arguments

`clust` | vector of cluster labels (integer or character) for each gene
`Sim` | similarity matrix

### Details

If necessary, more details than the description above

### Value

evaluateClustering returns a list with two items:

`clusterstats` | matrix (ncluster x 2) of median within cluster similarities and median absolute deviations
`clustersil` | cluster silhouette values

### Author(s)

Holger Froehlich

### References

Rousseeuw, P., Silhouettes: a graphical aid to the interpretation and validation of cluster analysis, J. Comp. and Applied Mathematics, 1987, 20, 53-6

### See Also

`getGeneSimPrototypes`, `getGeneSim`, `getTermSim`, `GOenrichment`

### Examples

    	setOntology("BP")
    	gomap <- get("gomap",env=GOSimEnv)
    	allgenes = sample(names(gomap), 1000) # suppose these are all genes
    	genesOfInterest = sample(allgenes, 20) # suppose these are all genes of interest

    	sim = getGeneSim(genesOfInterest,verbose=FALSE) # and these are their similarities
    	hc = hclust(as.dist(1-sim), method="ward") # use them to perform a clustering
    	plot(hc) # plot the cluster tree
    	cl = cutree(hc, k=3) # take 3 clusters

    	if(require(cluster)){
    		ev = evaluateClustering(cl, sim) # evaluate the clustering
    		print(ev$clusterstats) # print out some statistics
    		plot(ev$clustersil,main="") # plot the cluster silhouettes
    	}

    	# investigate cluster 1 further
    	if(require(topGO))
    		GOenrichment(genesOfInterest[cl == 1], allgenes, cutoff=0.05) # print out what cluster 1 is about

[Package GOSim version 1.26.0 Index]