lnmCluster: Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data

An implementation of logistic normal multinomial (LNM) clustering. It is an extension of LNM mixture model proposed by Fang and Subedi (2020) <doi:10.48550/arXiv.2011.06682>, and is designed for clustering compositional data. The package includes 3 extended models: LNM Factor Analyzer (LNM-FA), LNM Bicluster Mixture Model (LNM-BMM) and Penalized LNM Factor Analyzer (LNM-FA). There are several advantages of LNM models: 1. LNM provides more flexible covariance structure; 2. Factor analyzer can reduce the number of parameters to estimate; 3. Bicluster can simultaneously cluster subjects and taxa, and provides significant biological insights; 4. Penalty term allows sparse estimation in the covariance matrix. Details for model assumptions and interpretation can be found in papers: Tu and Subedi (2021) <doi:10.48550/arXiv.2101.01871> and Tu and Subedi (2022) <doi:10.1002/sam.11555>.

Version: 0.3.1
Depends: R (≥ 3.50)
Imports: mclust, foreach, MASS, stringr, gtools, pgmm, utils
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat, mvtnorm
Published: 2022-07-20
Author: Wangshu Tu [aut, cre], Sanjeena Dang [aut], Yuan Fang [aut]
Maintainer: Wangshu Tu <wangshu.tu at carleton.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: lnmCluster results

Documentation:

Reference manual: lnmCluster.pdf
Vignettes: lnmCluster

Downloads:

Package source: lnmCluster_0.3.1.tar.gz
Windows binaries: r-devel: lnmCluster_0.3.1.zip, r-release: lnmCluster_0.3.1.zip, r-oldrel: lnmCluster_0.3.1.zip
macOS binaries: r-release (arm64): lnmCluster_0.3.1.tgz, r-oldrel (arm64): lnmCluster_0.3.1.tgz, r-release (x86_64): lnmCluster_0.3.1.tgz

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