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ClassDiscovery (version 3.4.0)

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

2,312

Version

3.4.0

License

Apache License (== 2.0)

Maintainer

Kevin Coombes

Last Published

July 16th, 2021

Functions in ClassDiscovery (3.4.0)

PerturbationClusterTest

The PerturbationClusterTest Class
BootstrapClusterTest

Class "BootstrapClusterTest"
plotColoredClusters

Plot Dendrograms with Color-Coded Labels
Mosaic

Class "Mosaic"
hclust

Class "hclust"
ClusterTest-class

Class "ClusterTest"
aspectHeatmap

Heatmap with control over the aspect ratio
PCanova

Class "PCanova"
mahalanobisQC

Using Mahalanobis Distance and PCA for Quality Control
cluster3

Cluster a Dataset Three Ways
justClusters

Get the List of Classes From A Clustering Algorithm
distanceMatrix

Distance Matrix Computation
GenePCA

Class "GenePCA"
SamplePCA

Class "SamplePCA"