Given two genes, calculates the Dice similarity between each pathway which is combined to obtain a similarity between the genes.
Usage
mgeneSim(genes, info, method = "max", ...)
# S4 method for class 'character,GeneSetCollection'
mgeneSim(genes, info, method = "max", ...)
# S4 method for class 'missing,GeneSetCollection'
mgeneSim(genes, info, method = "max", ...)
Details
Given the information about the genes and their pathways, uses the ids
of the genes to find the Dice similarity score for each pathway comparison
between the genes. Later this similarities are combined using
combineScoresPar()
.
Methods (by class)
mgeneSim(genes = character, info = GeneSetCollection)
: Calculates all the similarities of the list and combine them usingcombineScoresPar()
mgeneSim(genes = missing, info = GeneSetCollection)
: Calculates all the similarities of the list and combine them usingcombineScoresPar()
See also
geneSim()
, conversions()
help page to transform Dice
score to Jaccard score. For the method to combine the scores see
combineScoresPar()
.
Examples
if (require("org.Hs.eg.db") & require("reactome.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)
# Extracts the paths of all genes of org.Hs.eg.db from reactome
genes.react <- as.list(reactomeEXTID2PATHID)
mgeneSim(c("81", "18", "10"), genes.react)
mgeneSim(c("81", "18", "10"), genes.react, "avg")
named_genes <- structure(c("81", "18", "10"),
.Names = c("ACTN4", "ABAT", "NAT2")
)
mgeneSim(named_genes, genes.react, "max")
} else {
warning("You need reactome.db and org.Hs.eg.db package for this example")
}
#> ACTN4 ABAT NAT2
#> ACTN4 1.00000000 0.12133072 0.05482166
#> ABAT 0.12133072 1.00000000 0.05124605
#> NAT2 0.05482166 0.05124605 1.00000000