ClusterGeneList: Generate Genes from a Cluster List

Description Usage Arguments Value Note Author(s) See Also Examples

View source: R/ClusterGeneList.r

Description

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

Usage

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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'

Note

argument 'x.data' should have an ID gene variable, 'probes', attached as a 'dimnames' attribute

Author(s)

Brian Steinmeyer

See Also

'GetClusters' 'ClusterList'

Examples

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# 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)

MantelCorr documentation built on May 2, 2018, 2:46 a.m.