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MicrobiomeStat (version 1.4)

Statistical Methods for Microbiome Compositional Data

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)), the BMDD (Bimodal Dirichlet Distribution) method for accurate modeling and imputation of zero-inflated microbiome sequencing data (Zhou et al. (2025)) and compositional sparse CCA methods for microbiome multi-omics data integration (Deng et al. (2024) ).

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Version

Install

install.packages('MicrobiomeStat')

Monthly Downloads

1,450

Version

1.4

License

GPL-3

Maintainer

Jun Chen

Last Published

March 3rd, 2026

Functions in MicrobiomeStat (1.4)

cscca.CV

Compositional Sparse Canonical Correlation Analysis (Cross Valication Version)
linda.plot

Plot LinDA Results
bmdd.nlopt

NLopt C++ Implementation of BMDD
linda.wald.test

Wald test for bias-corrected regression coefficients
smokers

Microbiome data from the human upper respiratory tract (left and right throat)
DGP_OC

Data Generating Process (Omics Data versus Compositional data)
bmdd

Bimodal Dirichlet Distribution Estimation
linda

Linear (Lin) Model for Differential Abundance (DA) Analysis of High-dimensional Compositional Data
cscca

Compositional Sparse Canonical Correlation Analysis