geneSim: The similarity between genes(modified the dDAGgeneSim in...

In ShadowFiendSF/GSminer: Select gold standard including positive and negative genes pairs based on the Gene Ontology

Description

The similarity between genes(modified the dDAGgeneSim in dnet)

Usage

geneSim(g, genes = NULL, method.gene = c("BM.average", "BM.max",
  "BM.complete", "average", "max"), method.term = c("Resnik", "Lin",
  "Schlicker", "Jiang", "Pesquita"), force = TRUE, fast = TRUE,
  parallel = TRUE, multicores = NULL, verbose = TRUE)

Arguments

g	an object of class "igraph"
genes	the genes between which pair-wise semantic similarity is calculated
method.gene	the method used for how to derive semantic similarity between genes from semantic similarity between terms
method.term	the method used to measure semantic similarity between terms
force	logical
fast	logical to indicate whether a vectorised fast computation is used
parallel	logical to indicate whether parallel computation
multicores	parallel computation
verbose	logical

Value

a sparse matrix of similarity between input genes

Examples

#load HPPA as igraph object
HPPA <-dRDataLoader(RData='ig.HPPA')
g <- ig.HPPA
#load human genes annotated by HPPA
Hs.egHPPA <- dRDataLoader(RData='org.Hs.egHPPA')
dag <- dDAGannotate(g, annotations=org.Hs.egHPPA,
path.mode="all_paths", verbose=TRUE)
allgenes <- unique(unlist(V(dag)$annotations))
genes <- sample(allgenes,5)
#just for an example:
#geneSim(g = dag, genes = genes, method.gene="BM.average", 
#        method.term = "Resnik", parallel = TRUE, 
#        multicores = 2, verbose = FALSE)

ShadowFiendSF/GSminer documentation built on May 29, 2019, 3:03 p.m.