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

        ## Not run:        
        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
        ## End(Not run)

[Package GOSim version 1.2 Index]