Package: MicrobiomeStat
Type: Package
Title: Statistical Methods for Microbiome Compositional Data
Version: 1.4
Date: 2026-03-03
Authors@R: c(
              person("Xianyang", "Zhang", role = "aut", email = "zhangxiany@stat.tamu.edu"),
              person("Jun", "Chen", role = c("aut", "cre"),
                     email = "chen.jun2@mayo.edu"),
              person("Huijuan", "Zhou", role = "ctb"),
              person("Linsui", "Deng", role = "ctb"))
Author: Xianyang Zhang [aut], Jun Chen [aut, cre], Huijuan Zhou [ctb],
        Linsui Deng [ctb]
Maintainer: Jun Chen <chen.jun2@mayo.edu>
Description: A suite of methods for powerful and robust microbiome data
        analysis addressing zero-inflation, phylogenetic structure and
        compositional effects. Includes the LinDA method for
        differential abundance analysis (Zhou et al.
        (2022)<doi:10.1186/s13059-022-02655-5>), the BMDD (Bimodal
        Dirichlet Distribution) method for accurate modeling and
        imputation of zero-inflated microbiome sequencing data (Zhou et
        al. (2025)<doi:10.1371/journal.pcbi.1013124>) and compositional
        sparse CCA methods for microbiome multi-omics data integration
        (Deng et al. (2024) <doi: 10.3389/fgene.2024.1489694>).
Depends: R (>= 3.5.0)
Imports: ggplot2, matrixStats, parallel, stats, utils, Matrix, statmod,
        MASS, ggrepel, lmerTest, foreach, modeest, dplyr, Rcpp, mlr3,
        mlr3mbo, bbotk, paradox
LinkingTo: Rcpp, RcppArmadillo
Suggests: DiceKriging, randomForest
NeedsCompilation: yes
SystemRequirements: NLopt library (optional, for high-performance BMDD
        mode)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Packaged: 2026-06-23 16:12:17 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2026-03-03 21:40:02 UTC
RemoteUrl: https://github.com/cran/MicrobiomeStat
RemoteRef: HEAD
RemoteSha: 67a6cc7d7254a67dcbde91f7fba7819405345626