hpSetCompSummary {PCAN} | R Documentation |
This function summarize the comparison of 2 sets of HP terms
hpSetCompSummary(hpSetComp, method = c("bma", "bm", "average"), direction = c("symSim", "r", "c"))
hpSetComp |
a matrix of semantic similarities between couples of HP terms |
method |
"bma" (Best Match Average): the average of the best matches on rows or columns (see direction param). "bm": the maximum value. "average": the average of the whole matrix. |
direction |
taken into account only if method="bma". "r": best match per row. "c": best match per column. "symSim" (symmetric semantic similarity): average of calls with "r" and "c" |
A numeric value corresponding to the semantic similarity of the 2 HP sets
Patrice Godard
## Prerequisite data(geneByHp, hp_descendants, package="PCAN") geneByHp <- unstack(geneByHp, entrez~hp) ic <- computeHpIC(geneByHp, hp_descendants) ########################################### ## Use case: comparing a gene and a disease data(traitDef, geneDef, hp_ancestors, hpDef, package="PCAN") omim <- "612285" traitDef[which(traitDef$id==omim),] entrez <- "57545" geneDef[which(geneDef$entrez==entrez),] ## Get HP terms associated to the disease data(hpByTrait, package="PCAN") hpOfInterest <- hpByTrait$hp[which(hpByTrait$id==omim)] ## Get HP terms associated to the gene hpByGene <- unstack(stack(geneByHp), ind~values) geneHps <- hpByGene[[entrez]] ## Comparison of the two sets of HP terms compMat <- compareHPSets( hpSet1=geneHps, hpSet2=hpOfInterest, IC=ic, ancestors=hp_ancestors, method="Resnik", BPPARAM=SerialParam() ) ## Get the symmetric semantic similarity score hpSetCompSummary(compMat, method="bma", direction="symSim") bm <- hpSetCompBestMatch(compMat, "b") hpDef[match(c(bm$compared, bm$candidate), hpDef$id),]