BASiCStan
Stan implementation of BASiCS
Bioconductor version: 3.23 · Package version: 1.14.1
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("BASiCStan") Details
| Maintainer | Alan O'Callaghan <alan.ocallaghan@outlook.com> |
| Author | Alan O'Callaghan [aut, cre], Catalina Vallejos [aut] |
| License | GPL-3 |
| URL | https://github.com/Alanocallaghan/BASiCStan |
| Bug Reports | https://github.com/Alanocallaghan/BASiCStan/issues |
| System Requirements | GNU make |
| Downloads rank | 196 |
| Source branch | RELEASE_3_23 |
| biocViews | Bayesian, CellBiology, DifferentialExpression, GeneExpression, ImmunoOncology, Normalization, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Documentation
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Dependencies
Depends: R (>= 4.2), BASiCS, rstan (>= 2.18.1)
Imports: methods, glmGamPoi, scran, scuttle, stats, utils, SingleCellExperiment, SummarizedExperiment, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstantools (>= 2.1.1)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown