eclust: Environment Based Clustering for Interpretable Predictive Models in High Dimensional Data

Companion package to the paper: An analytic approach for interpretable predictive models in high dimensional data, in the presence of interactions with exposures. Bhatnagar, Yang, Khundrakpam, Evans, Blanchette, Bouchard, Greenwood (2017) <doi:10.1101/102475>. This package includes an algorithm for clustering high dimensional data that can be affected by an environmental factor.

Version:	0.1.0
Depends:	R (≥ 3.3.1)
Imports:	caret, data.table, dynamicTreeCut, magrittr, pacman, WGCNA, stringr, pander, stats
Suggests:	cluster, earth, ncvreg, knitr, rmarkdown, protoclust, factoextra, ComplexHeatmap, circlize, pheatmap, viridis, pROC, glmnet
Published:	2017-01-26
Author:	Sahir Rai Bhatnagar [aut, cre] (http://sahirbhatnagar.com/)
Maintainer:	Sahir Rai Bhatnagar <sahir.bhatnagar at gmail.com>
BugReports:	https://github.com/sahirbhatnagar/eclust/issues
License:	MIT + file LICENSE
URL:	https://github.com/sahirbhatnagar/eclust/, http://sahirbhatnagar.com/eclust/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	eclust results

Documentation:

Reference manual:	eclust.pdf
Vignettes:	Introduction to eclust

Downloads:

Package source:	eclust_0.1.0.tar.gz
Windows binaries:	r-devel: eclust_0.1.0.zip, r-release: eclust_0.1.0.zip, r-oldrel: eclust_0.1.0.zip
macOS binaries:	r-release (arm64): eclust_0.1.0.tgz, r-oldrel (arm64): eclust_0.1.0.tgz, r-release (x86_64): eclust_0.1.0.tgz, r-oldrel (x86_64): eclust_0.1.0.tgz

Linking:

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