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RFclust: Random Forest Cluster Analysis

Tools to perform random forest consensus clustering of different data types. The package is designed to accept a list of matrices from different assays, typically from high-throughput molecular profiling so that class discovery may be jointly performed. For references, please see Tao Shi & Steve Horvath (2006) <doi:10.1198/106186006X94072> & Monti et al (2003) <doi:10.1023/A:1023949509487> .

Version: 0.1.2
Depends: R (≥ 3.5.0)
Imports: ConsensusClusterPlus, randomForest
Published: 2022-06-21
DOI: 10.32614/CRAN.package.RFclust
Author: Ankur Chakravarthy, PhD
Maintainer: Ankur Chakravarthy <ankur.chakravarthy.10 at ucl.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: RFclust results

Documentation:

Reference manual: RFclust.pdf

Downloads:

Package source: RFclust_0.1.2.tar.gz
Windows binaries: r-devel: RFclust_0.1.2.zip, r-release: RFclust_0.1.2.zip, r-oldrel: RFclust_0.1.2.zip
macOS binaries: r-release (arm64): RFclust_0.1.2.tgz, r-oldrel (arm64): RFclust_0.1.2.tgz, r-release (x86_64): RFclust_0.1.2.tgz, r-oldrel (x86_64): RFclust_0.1.2.tgz
Old sources: RFclust archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.