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COMMUNAL (version 1.1.0)

Robust Selection of Cluster Number K

Description

Facilitates optimal clustering of a data set. Provides a framework to run a wide range of clustering algorithms to determine the optimal number (k) of clusters in the data. Then analyzes the cluster assignments from each clustering algorithm to identify samples that repeatedly classify to the same group. We call these 'core clusters', providing a basis for later class discovery.

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Version

Install

install.packages('COMMUNAL')

Monthly Downloads

16

Version

1.1.0

License

GPL-2

Maintainer

Albert Chen

Last Published

October 11th, 2015

Functions in COMMUNAL (1.1.0)

COMMUNAL-class

Class "COMMUNAL"
BRCA.100

Breast Cancer gene expression data.
COMMUNAL-package

COmbined Mapping of Multiple clUsteriNg ALgorithms
BRCA.results

Choose Optimal Clustering Algorithms

Choose Optimal Clustering Algorithms
plotRange3D

Visualize cluster stability
Measure Cluster Monotonicty

Measure cluster monotonicty within the output from clusterRange.
clusterKeys

Rekey cluster assignments.
clusterRange

Run COMMUNAL over a range of data subsets
returnCore

Assign points to core clusters
examineCounts

Examine algorithm cluster agreement
COMMUNAL

Run clustering algorithms and evaluate validation metrics.