junsoukchoi/ZIPBN: Zero-Inflated Poisson Bayesian Networks for Zero-Inflated Count Data

Markov chain Monte Carlo (MCMC) implementation to fit zero-inflated poisson Bayesian network models for zero-inflated count data such as scRNA-seq data. Each local distribution of a Bayesian network is assumed to be a zero-inflated poisson model. The algorithm uses Metropolis-Within-Gibbs sampling for posterior inference.

Getting started

Package details

AuthorJunsouk Choi [aut, cre]
MaintainerJunsouk Choi <jchoi@stat.tamu.edu>
LicenseGPL (>=2)
Version1.0.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("junsoukchoi/ZIPBN")
junsoukchoi/ZIPBN documentation built on Dec. 10, 2019, 9:35 a.m.