Learn R Programming

ClassDiscovery (version 3.4.10)

Classes and Methods for "Class Discovery" with Microarrays or Proteomics

Description

Defines the classes used for "class discovery" problems in the OOMPA project (). Class discovery primarily consists of unsupervised clustering methods with attempts to assess their statistical significance.

Copy Link

Version

Install

install.packages('ClassDiscovery')

Monthly Downloads

1,559

Version

3.4.10

License

Apache License (== 2.0)

Maintainer

Kevin Coombes

Last Published

July 27th, 2026

Functions in ClassDiscovery (3.4.10)

cluster3

Cluster a Dataset Three Ways
plotColoredClusters

Plot Dendrograms with Color-Coded Labels
BootstrapClusterTest

Class "BootstrapClusterTest"
SamplePCA

Class "SamplePCA"
distanceMatrix

Distance Matrix Computation
justClusters

Get the List of Classes From A Clustering Algorithm
GenePCA

Class "GenePCA"
PerturbationClusterTest

The PerturbationClusterTest Class
ClusterTest-class

Class "ClusterTest"
hclust

Class "hclust"
aspectHeatmap

Heatmap with control over the aspect ratio
PCanova

Class "PCanova"
mahalanobisQC

Using Mahalanobis Distance and PCA for Quality Control
Mosaic

Class "Mosaic"