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ClassDiscovery (version 3.3.9)

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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Version

Install

install.packages('ClassDiscovery')

Monthly Downloads

1,726

Version

3.3.9

License

Apache License (== 2.0)

Maintainer

Kevin Coombes

Last Published

October 3rd, 2018

Functions in ClassDiscovery (3.3.9)

plotColoredClusters

Plot Dendrograms with Color-Coded Labels
mahalanobisQC

Using Mahalanobis Distance and PCA for Quality Control
PCanova

Class "PCanova"
aspectHeatmap

Heatmap with control over the aspect ratio
Mosaic

Class "Mosaic"
distanceMatrix

Distance Matrix Computation
hclust

Class "hclust"
ClusterTest-class

Class "ClusterTest"
PerturbationClusterTest

The PerturbationClusterTest Class
BootstrapClusterTest

Class "BootstrapClusterTest"
cluster3

Cluster a Dataset Three Ways
SamplePCA

Class "SamplePCA"
justClusters

Get the List of Classes From A Clustering Algorithm
GenePCA

Class "GenePCA"