A review on probabilistic models used in microbiome studies

Abstract

In this paper, we first briefly review the background and signifi-cance of the microbiome, the technologies used for collecting microbiome data, and some public resources for downloading microbiome data. We then review the probabilistic models used in the literature in two categories: (1) for read counts from a specific feature, including Poisson, negative binomial, zero-inflated and hurdle models; (2) for read counts from multiple features, including Dirichlet-multinomial, generalized Dirichlet-multinomial, and zero-inflated models, as well as a nonparametric Bayesian model for a flexible number of features. We also review comprehensive comparisons among different probabilistic models.