MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

摘要

The human microbiome is a collection of prokaryotes, archaea, fungi, and viruses which may vary in composition depending on an individual’s health, diet, and environment [1, 2]. High-throughput sequencing technologies enable researchers to characterize the composition of the microbiome by quantifying richness, diversity, and abundances (see [2] for a detailed review). Characterization of the microbiome is especially critical to the study of chronic diseases such as cancer and diabetes that may be associated with key changes in the microbiome [2].