Perform Logistic Normal Multinomial Clustering for Microbiome Compositional Data R package lnmCluster version 0.3.1 CRAN Task View: CompositionalData (https://CRAN.R-project.org/view=CompositionalData) An implementation of logistic normal multinomial (LNM) clustering. It is an extension of LNM mixture model proposed by Fang and Subedi (2020) <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) <arXiv:2101.01871> and Tu and Subedi (2022) <doi:10.1002/sam.11555>. Software Depends: R (>= 3.50) Imports: mclust, foreach, MASS, stringr, gtools, pgmm, utils LinkingTo: Rcpp Suggests: knitr, rmarkdown, testthat, mvtnorm Wangshu Tu <wangshu.tu@carleton.ca> Comprehensive R Archive Network (CRAN) Wangshu Tu [aut, cre], Sanjeena Dang [aut], Yuan Fang [aut] GPL (>= 2) 2022-07-20 application/tgz https://CRAN.R-project.org/package=lnmCluster doi:10.32614/CRAN.package.lnmCluster