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>).
| Version: |
1.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
ggplot2, matrixStats, parallel, stats, utils, Matrix, statmod, MASS, ggrepel, lmerTest, foreach, modeest, dplyr, mlrMBO, Rcpp, ParamHelpers, smoof, lhs, mlr, BBmisc |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
DiceKriging, randomForest |
| Published: |
2026-01-09 |
| DOI: |
10.32614/CRAN.package.MicrobiomeStat |
| Author: |
Xianyang Zhang [aut],
Jun Chen [aut, cre],
Huijuan Zhou [ctb],
Linsui Deng [ctb] |
| Maintainer: |
Jun Chen <chen.jun2 at mayo.edu> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| SystemRequirements: |
NLopt library (optional, for high-performance BMDD
mode) |
| In views: |
CompositionalData |
| CRAN checks: |
MicrobiomeStat results |