Similarity score between clusters of genes based on pathways similarity

Looks for the similarity between genes in groups. Once the pathways for each cluster are found they are combined using codecombineScores.

Usage

mclusterSim(clusters, info, method = "max", ...)

# S4 method for list,GeneSetCollection
mclusterSim(clusters, info, method = "max", ...)

Arguments

clusters

A list of clusters of genes to be found in id.

info

A GeneSetCollection or a list of genes and the pathways they are involved.

method

one of c("avg", "max", "rcmax", "rcmax.avg", "BMA", "reciprocal"), see Details.

...

Other arguments passed to combineScores

Value

mclusterSim returns a matrix with the similarity scores for each cluster comparison.

Methods (by class)

• mclusterSim(clusters = list, info = GeneSetCollection): Calculates all the similarities of the GeneSetCollection and combine them using combineScoresPar()

See also

For a different approach see clusterGeneSim(), combineScores() and conversions()

Author

Lluís Revilla

Examples

if (require("org.Hs.eg.db")) {
    # Extract the paths of all genes of org.Hs.eg.db from KEGG (last update in
    # data of June 31st 2011)
    genes.kegg <- as.list(org.Hs.egPATH)

    clusters <- list(
        cluster1 = c("18", "81", "10"),
        cluster2 = c("100", "10", "1"),
        cluster3 = c("18", "10", "83")
    )
    mclusterSim(clusters, genes.kegg)
    mclusterSim(clusters, genes.kegg, "avg")
} else {
    warning("You need org.Hs.eg.db package for this example")
}
#>            cluster1   cluster2  cluster3
#> cluster1 0.11837329 0.07739749 0.1158909
#> cluster2 0.07739749 0.26653339 0.1448643
#> cluster3 0.11589087 0.14486431 0.2183986