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plsgenomics: PLS Analyses for Genomics

Routines for PLS-based genomic analyses, implementing PLS methods for classification with microarray data and prediction of transcription factor activities from combined ChIP-chip analysis. The >=1.2-1 versions include two new classification methods for microarray data: GSIM and Ridge PLS. The >=1.3 versions includes a new classification method combining variable selection and compression in logistic regression context: logit-SPLS; and an adaptive version of the sparse PLS.

Version: 1.5-3
Depends: R (≥ 3.0)
Imports: MASS, boot, parallel, reshape2, plyr, fields, RhpcBLASctl
Published: 2024-03-28
Author: Anne-Laure Boulesteix, Ghislain Durif, Sophie Lambert-Lacroix, Julie Peyre, and Korbinian Strimmer.
Maintainer: Ghislain Durif <gd.dev at libertymail.net>
BugReports: https://github.com/gdurif/plsgenomics/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/gdurif/plsgenomics
NeedsCompilation: no
Materials: README
CRAN checks: plsgenomics results

Documentation:

Reference manual: plsgenomics.pdf

Downloads:

Package source: plsgenomics_1.5-3.tar.gz
Windows binaries: r-devel: plsgenomics_1.5-3.zip, r-release: plsgenomics_1.5-3.zip, r-oldrel: plsgenomics_1.5-3.zip
macOS binaries: r-release (arm64): plsgenomics_1.5-3.tgz, r-oldrel (arm64): plsgenomics_1.5-3.tgz, r-release (x86_64): plsgenomics_1.5-3.tgz, r-oldrel (x86_64): plsgenomics_1.5-3.tgz
Old sources: plsgenomics archive

Reverse dependencies:

Reverse imports: MAIT, MultiGroupO
Reverse suggests: ClusterSignificance, CMA

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.
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