Skip to contents

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 class '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