MantelCorr (version 1.42.0)

ClusterGeneList: Generate Genes from a Cluster List

Description

'ClusterGeneList' produces a list of both significant and nonsignificant genes from each respective cluster type

Usage

ClusterGeneList(clus, clustlist.sig, x.data)

Arguments

clus

'clusters' object returned by 'GetClusters'

clustlist.sig

'SignificantClusters' object returned by 'ClusterList'

x.data

original (p x n) numeric data matrix (e.g., gene-expression data)

Value

A list with components:

SignificantClusterGenes

significant cluster genes returned from 'ClusterList'

NonSignificantClusterGenes

nonsignificant cluster genes returned from 'ClusterList'

See Also

'GetClusters' 'ClusterList'

Examples

# simulate a p x n microarray expression dataset, where p = genes and n = samples
data.sep <- rbind(matrix(rnorm(1000), ncol=50), matrix(rnorm(1000, mean=5), ncol=50))
noise <- matrix(runif(40000), ncol=1000)
data <- t(cbind(data.sep, noise))
data <- data[1:200, ]
# data has p = 1,050 genes and n = 40 samples

clusters.result <- GetClusters(data, 100, 100)
dist.matrices <- DistMatrices(data, clusters.result$clusters)
mantel.corrs <- MantelCorrs(dist.matrices$Dfull, dist.matrices$Dsubsets)
permutation.result <- PermutationTest(dist.matrices$Dfull, dist.matrices$Dsubsets, 100, 40, 0.05)

# generate both significant and non-significant gene clusters
cluster.list <- ClusterList(permutation.result, clusters.result$cluster.sizes, mantel.corrs)

# significant and non-significant cluster genes (expression values)
cluster.genes <- ClusterGeneList(clusters.result$clusters, cluster.list$SignificantClusters, data)