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Identifies a bicluster, a submatrix of the data such that the features and observations within the submatrix differ from those not contained in submatrix, using a two-step method. In the first step, observations in the bicluster are identified to maximize the sum of weighted between cluster feature differences. The method is described in Helgeson et al. (2020) <doi:10.1111/biom.13136>. 'SCBiclust' can be used to identify biclusters which differ based on feature means, feature variances, or more general differences.
Version: | 1.0.1 |
Depends: | R (≥ 3.4.0) |
Imports: | sparcl, sigclust |
Published: | 2022-06-09 |
DOI: | 10.32614/CRAN.package.SCBiclust |
Author: | Erika S. Helgeson, Qian Liu, Guanhua Chen, Michael R. Kosorok , and Eric Bair |
Maintainer: | Erika S. Helgeson <helge at umn.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
CRAN checks: | SCBiclust results |
Reference manual: | SCBiclust.pdf |
Package source: | SCBiclust_1.0.1.tar.gz |
Windows binaries: | r-devel: SCBiclust_1.0.1.zip, r-release: SCBiclust_1.0.1.zip, r-oldrel: SCBiclust_1.0.1.zip |
macOS binaries: | r-release (arm64): SCBiclust_1.0.1.tgz, r-oldrel (arm64): SCBiclust_1.0.1.tgz, r-release (x86_64): SCBiclust_1.0.1.tgz, r-oldrel (x86_64): SCBiclust_1.0.1.tgz |
Old sources: | SCBiclust archive |
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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.
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