BCGLMs: Bayesian modeling for disease prediction using compositional microbiome features

Abstract Motivation BCGLMs is a freely available R package that provides functions for setting up and fitting Bayesian compositional models for continuous, binary, ordinal and survival responses. It also includes models with random effects to capture sample-related accumulated small effects, improving prediction accuracy. The package includes tools for summarizing results from fitted models both numerically and graphically. Built on top of the widely used brms package, BCGLMs enable users to incorporate phylogenetic relationships between microbiome taxa into the modeling framework. Overall, BCGLMs package offers a flexible and powerful set of tools for analyzing compositional microbiome data. Availability and implementation The package is publicly available via GitHub https://github.com/Li-Zhang28/BCGLMs.