Alanocallaghan/BASiCStan: Stan implementation of BASiCS

Provides an interface to infer the parameters of BASiCS using the variational inference (ADVI), Markov chain Monte Carlo (NUTS), and maximum a posteriori (BFGS) inference engines in the Stan programming language. BASiCS is a Bayesian hierarchical model that uses an adaptive Metropolis within Gibbs sampling scheme. Alternative inference methods provided by Stan may be preferable in some situations, for example for particularly large data or posterior distributions with difficult geometries.

Getting started

Package details

Bioconductor views Bayesian CellBiology DifferentialExpression GeneExpression ImmunoOncology Normalization RNASeq Sequencing SingleCell Software Transcriptomics
Maintainer
LicenseGPL-3
Version1.5.1
URL https://github.com/Alanocallaghan/BASiCStan
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("Alanocallaghan/BASiCStan")
Alanocallaghan/BASiCStan documentation built on Feb. 19, 2024, 10:40 p.m.