Introduction | Getting Started | Distances and Clustering | Checking the Robustness of Clusters | Principal Components Analysis | Mosaics: red-green heatmaps | Class discovery with ExpressionSets
Package: ClassDiscovery 3.4.9
Kevin R. Coombes
ClassDiscovery: Classes and Methods for "Class Discovery" with Microarrays or Proteomics
Defines the classes used for "class discovery" problems in the OOMPA project (<http://oompa.r-forge.r-project.org/>). Class discovery primarily consists of unsupervised clustering methods with attempts to assess their statistical significance.
Authors:
ClassDiscovery_3.4.9.tar.gz
ClassDiscovery_3.4.9.zip(r-4.7)ClassDiscovery_3.4.9.zip(r-4.6)ClassDiscovery_3.4.9.zip(r-4.5)
ClassDiscovery_3.4.9.tgz(r-4.6-any)ClassDiscovery_3.4.9.tgz(r-4.5-any)
ClassDiscovery_3.4.9.tar.gz(r-4.7-any)ClassDiscovery_3.4.9.tar.gz(r-4.6-any)
ClassDiscovery_3.4.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ClassDiscovery/json (API)
| # Install 'ClassDiscovery' in R: |
| install.packages('ClassDiscovery', repos = c('https://r-forge.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/oompa
Last updated from:969e77c656. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 109 | ||
| source / vignettes | OK | 191 | ||
| linux-release-x86_64 | OK | 113 | ||
| macos-release-arm64 | OK | 77 | ||
| macos-oldrel-arm64 | OK | 114 | ||
| windows-devel | OK | 78 | ||
| windows-release | OK | 75 | ||
| windows-oldrel | OK | 85 | ||
| wasm-release | OK | 97 |
Exports:as.data.frameaspectHeatmapBootstrapClusterTestcluster3cutHclustcutKmeanscutPamcutRepeatedKmeansdistanceMatrixGenePCAhistidentifyimagemahalanobisQCMosaicPCanovapccPerturbationClusterTestplotplotColoredClusterspltreepredictrepeatedKmeansSamplePCAscreeplotsummarytext
Dependencies:BiobaseBiocGenericsclustergenericsmclustoompaBaseoompaData
OOMPA ClassDiscovery
Last update: 2014-02-10
Started: 2014-02-10
OOMPA Mahalanobis Distance
Simulated Data | PCA | A Second Round | A Final Round | Appendix
Last update: 2014-02-10
Started: 2014-02-10
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Heatmap with control over the aspect ratio | aspectHeatmap |
| Class "BootstrapClusterTest" | BootstrapClusterTest BootstrapClusterTest-class summary,BootstrapClusterTest-method |
| Cluster a Dataset Three Ways | cluster3 |
| Class "ClusterTest" | ClusterTest ClusterTest-class hist,ClusterTest-method image,ClusterTest-method summary,ClusterTest-method |
| Distance Matrix Computation | distanceMatrix |
| Class "GenePCA" | GenePCA GenePCA-class plot,GenePCA,missing-method |
| Class "hclust" | hclust-class |
| Get the List of Classes From A Clustering Algorithm | cutHclust cutKmeans cutPam cutRepeatedKmeans repeatedKmeans |
| Using Mahalanobis Distance and PCA for Quality Control | mahalanobisQC |
| Class "Mosaic" | Mosaic Mosaic-class plot,Mosaic,missing-method pltree,Mosaic-method summary,Mosaic-method |
| Class "PCanova" | PCanova PCanova-class plot,PCanova,missing-method pltree,PCanova-method summary,PCanova-method |
| The PerturbationClusterTest Class | PerturbationClusterTest PerturbationClusterTest-class summary,PerturbationClusterTest-method |
| Plot Dendrograms with Color-Coded Labels | pcc plotColoredClusters |
| Class "SamplePCA" | identify,SamplePCA-method plot,SamplePCA,missing-method predict,SamplePCA-method SamplePCA SamplePCA-class screeplot,SamplePCA-method summary,SamplePCA-method text,SamplePCA-method |