Calculates the Dice similarity between pathways

Calculates the similarity between several pathways using dice similarity score. If one needs the matrix of similarities between pathways set the argument methods to NULL.

Usage

mpathSim(pathways, info, method = NULL, ...)

# S4 method for character,GeneSetCollection,ANY
mpathSim(pathways, info, method = NULL, ...)

# S4 method for missing,GeneSetCollection,ANY
mpathSim(pathways, info, method = NULL, ...)

# S4 method for missing,list,ANY
mpathSim(pathways, info, method = NULL, ...)

# S4 method for missing,list,missing
mpathSim(pathways, info, method = NULL, ...)

Arguments

pathways

Pathways to calculate the similarity for

info

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

method

To combine the scores of each pathway, one of c("avg", "max", "rcmax", "rcmax.avg", "BMA"), if NULL returns the matrix of similarities.

...

Other arguments passed to combineScoresPar()

Value

The similarity between those pathways or all the similarities between each comparison.

Methods (by class)

• mpathSim(pathways = character, info = GeneSetCollection, method = ANY): Calculates the similarity between the provided pathways of the GeneSetCollection using combineScoresPar

• mpathSim(pathways = missing, info = GeneSetCollection, method = ANY): Calculates all the similarities of the GeneSetCollection and combine them using combineScoresPar

• mpathSim(pathways = missing, info = list, method = ANY): Calculates all the similarities of the list and combine them using combineScoresPar

• mpathSim(pathways = missing, info = list, method = missing): Calculates all the similarities of the list

Note

pathways accept named characters, and then the output will have the names

See also

pathSim() For single pairwise comparison. conversions() To convert the Dice similarity to Jaccard similarity

Examples

if (require("reactome.db")) {
    genes.react <- as.list(reactomeEXTID2PATHID)
    (pathways <- sample(unique(unlist(genes.react)), 10))
    mpathSim(pathways, genes.react, NULL)
    named_paths <- structure(
        c("R-HSA-112310", "R-HSA-112316", "R-HSA-112315"),
        .Names = c(
            "Neurotransmitter Release Cycle",
            "Neuronal System",
            "Transmission across Chemical Synapses"
        )
    )
    mpathSim(named_paths, genes.react, NULL)
    many_pathways <- sample(unique(unlist(genes.react)), 152)
    mpathSim(many_pathways, genes.react, "avg")
} else {
    warning("You need reactome.db package for this example")
}
#> [1] 0.007493391