CorScoreCalc {MCbiclust} | R Documentation |
The standard method to calculate the correlation score used to judge biclusters in MCbiclust
CorScoreCalc(gene.expr.matrix, sample.vec)
gene.expr.matrix |
Gene expression matrix with genes as rows and samples as columns |
sample.vec |
Vector of samples |
The correlation score
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)