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ClassDiscovery (version 3.4.8)

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.

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Install

install.packages('ClassDiscovery')

Monthly Downloads

1,817

Version

3.4.8

License

Apache License (== 2.0)

Maintainer

Kevin Coombes

Last Published

April 7th, 2025

Functions in ClassDiscovery (3.4.8)

PerturbationClusterTest

The PerturbationClusterTest Class
Mosaic

Class "Mosaic"
aspectHeatmap

Heatmap with control over the aspect ratio
mahalanobisQC

Using Mahalanobis Distance and PCA for Quality Control
PCanova

Class "PCanova"
distanceMatrix

Distance Matrix Computation
hclust

Class "hclust"
justClusters

Get the List of Classes From A Clustering Algorithm
cluster3

Cluster a Dataset Three Ways
SamplePCA

Class "SamplePCA"
plotColoredClusters

Plot Dendrograms with Color-Coded Labels
BootstrapClusterTest

Class "BootstrapClusterTest"
GenePCA

Class "GenePCA"
ClusterTest-class

Class "ClusterTest"