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.
|Author||Junsouk Choi [aut, cre]|
|Maintainer||Junsouk Choi <email@example.com>|
|Package repository||View on GitHub|
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