zinLDA

Zero-inflated latent Dirichlet allocation (zinLDA) is an unsupervised, hierarchical, generative probabilistic model that facilitates dimensionality reduction and detection of sparse latent clusters. This package, hosted on GitHub, provides implementation of a Markov chain Monte Carlo (MCMC) sampling procedure for the zinLDA model. Additionally, it provides a method for simulating sparse count data from an underlying zinLDA model.

While the original paper developed this model for applications to microbiome data and microbial subcommunity detection, it is designed to be portable to numerous types of discrete count data.