rhcoclust: Robust Hierarchical Co-Clustering to Identify Significant Co-Cluster

Here we performs robust hierarchical co-clustering between row and column entities of a data matrix in absence and presence of outlying observations. It can be used to explore important co-clusters consisting of important samples and their regulatory significant features. Please see Hasan, Badsha and Mollah (2020) <doi:10.1101/2020.05.13.094946>.

Version: 2.0.0
Depends: R (≥ 3.5.0)
Imports: fields, grDevices, graphics, igraph, stats
Published: 2023-01-29
DOI: 10.32614/CRAN.package.rhcoclust
Author: Md. Bahadur Badsha [aut, cre], Mohammad Nazmol Hasan [aut], Md. Nurul Haque Mollah [aut]
Maintainer: Md. Bahadur Badsha <mbbadshar at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: rhcoclust results


Reference manual: rhcoclust.pdf


Package source: rhcoclust_2.0.0.tar.gz
Windows binaries: r-devel: rhcoclust_2.0.0.zip, r-release: rhcoclust_2.0.0.zip, r-oldrel: rhcoclust_2.0.0.zip
macOS binaries: r-release (arm64): rhcoclust_2.0.0.tgz, r-oldrel (arm64): rhcoclust_2.0.0.tgz, r-release (x86_64): rhcoclust_2.0.0.tgz, r-oldrel (x86_64): rhcoclust_2.0.0.tgz
Old sources: rhcoclust archive


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