hclustWrapper: Wrapper for hierarchical clustering

In montilab/K2Taxonomer: Creating annotated submodules of high-throughput data through recursive partitioning

Wrapper for hierarchical clustering

Description

This fuction is a wrapper for the hclust, dist, and cutree functions. It outputs a string of a concatenated vector of 1's and 2's indexed by column. This function is not meant to be run individually, but as a 'clustFunc' argument for running 'K2preproc()', 'runK2Taxonomer()', and 'K2tax()'.

Usage

hclustWrapper(dataMatrix, clustList)

Arguments

dataMatrix	An P x N numeric matrix of data.
clustList	Named list of objects to use for clustering procedure. Or ‘NULL' to use Euclidean distance with Ward’s method. 'distMetric'Distance method to use. See ?dist. 'aggMethod'Agglomerative method to use. See ?hclust.

Value

A character string of concatenated 1's and 2's pertaining to the cluster assignment of each column in dataMatrix.

References

\insertRef

reed_2020K2Taxonomer

Examples

## Read in sample ExpressionSet
require(Biobase)
data('sample.ExpressionSet')

## Extrat subset of data matrix
dm <- exprs(sample.ExpressionSet)[seq_len(50),]

## Create list of objects for clustering procedure.
cL <- list(distMetric='euclidean', aggMethod='ward.D2')

## Generate K=2 split with hierarchical clustering
hclustWrapper(dm, cL)

montilab/K2Taxonomer documentation built on Nov. 8, 2024, 2:36 a.m.