BaHZING: Bayesian Hierarchical Zero-Inflated Negative Binomial Regression with G-Computation

A Bayesian model for examining the association between environmental mixtures and all Taxa measured in a hierarchical microbiome dataset in a single integrated analysis. Compared with analyzing the associations of environmental mixtures with each Taxa individually, 'BaHZING' controls Type 1 error rates and provides more stable effect estimates when dealing with small sample sizes.

Version: 1.0.0
Depends: R (≥ 4.1.0), rjags (≥ 4.0.0)
Imports: bayestestR, dplyr, magrittr, phyloseq, pscl, R2jags, stats, stringr, tidyr
Suggests: testthat (≥ 3.0.0)
Published: 2025-02-17
DOI: 10.32614/CRAN.package.BaHZING
Author: Hailey Hampson [aut], Jesse Goodrich ORCID iD [aut, cre], Hongxu Wang [aut], Tanya Alderete [ctb], Shardul Nazirkar [ctb], David Conti [aut]
Maintainer: Jesse Goodrich <jagoodri at usc.edu>
License: GPL (≥ 3)
NeedsCompilation: no
SystemRequirements: JAGS 4.x.y (http://mcmc-jags.sourceforge.net)
Materials: README NEWS
CRAN checks: BaHZING results

Documentation:

Reference manual: BaHZING.pdf

Downloads:

Package source: BaHZING_1.0.0.tar.gz
Windows binaries: r-devel: BaHZING_1.0.0.zip, r-release: BaHZING_1.0.0.zip, r-oldrel: BaHZING_1.0.0.zip
macOS binaries: r-devel (arm64): not available, r-release (arm64): not available, r-oldrel (arm64): not available, r-devel (x86_64): BaHZING_1.0.0.tgz, r-release (x86_64): BaHZING_1.0.0.tgz, r-oldrel (x86_64): BaHZING_1.0.0.tgz

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