CorScoreCalc {MCbiclust}R Documentation

Calculate correlation score

Description

The standard method to calculate the correlation score used to judge biclusters in MCbiclust

Usage

CorScoreCalc(gene.expr.matrix, sample.vec)

Arguments

gene.expr.matrix

Gene expression matrix with genes as rows and samples as columns

sample.vec

Vector of samples

Value

The correlation score

Examples

data(CCLE_small)
data(Mitochondrial_genes)

mito.loc <- which(row.names(CCLE_small) %in% Mitochondrial_genes)
CCLE.mito <- CCLE_small[mito.loc,]

random.seed <- sample(seq(length = dim(CCLE.mito)[2]),10)
CCLE.seed <- FindSeed(gem = CCLE.mito,
                      seed.size = 10,
                      iterations = 100,
                      messages = 100)


CorScoreCalc(CCLE.mito, random.seed)
CorScoreCalc(CCLE.mito, CCLE.seed)

CCLE.hicor.genes <- as.numeric(HclustGenesHiCor(CCLE.mito,
                                                CCLE.seed,
                                                cuts = 8))

CorScoreCalc(CCLE.mito[CCLE.hicor.genes,], CCLE.seed)

[Package MCbiclust version 1.6.1 Index]