DistMatrices: Compute Dissimilarity Matrices

In MantelCorr: Compute Mantel Cluster Correlations

Description

'DistMatrices' uses 'dist' to compute dissimilarity matrices for 'data' and each cluster k from 'GetClusters'

Usage

 DistMatrices(x.data, cluster.assignment)

Arguments

x.data	original 'data' matrix
cluster.assignment	cluster assignment vector, "clusters", returned by 'GetClusters'

Value

returns a list with two components:

Dsubsets	dissimilarity matrices for each cluster k
Dfull	dissimilarity matrix for the original 'data'

Note

'GetClusters' should be executed prior to 'DistMatrices'

Author(s)

Brian Steinmeyer

See Also

'GetClusters'

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)
dissimilarity.matrices <- DistMatrices(data, clusters.result$clusters)

MantelCorr documentation built on Nov. 8, 2020, 4:58 p.m.