fastglmpca: Fast Algorithms for Generalized Principal Component Analysis
Implements fast, scalable optimization algorithms for fitting generalized principal components analysis (GLM-PCA) models, as described in "A Generalization of Principal Components Analysis to the Exponential Family" Collins M, Dasgupta S, Schapire RE (2002, ISBN:9780262271738), and subsequently "Feature Selection and Dimension Reduction for Single-Cell RNA-Seq Based on a Multinomial Model" Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) <doi:10.1186/s13059-019-1861-6>.
| Version: | 0.1-108 |
| Depends: | R (≥ 3.6) |
| Imports: | utils,Matrix, stats,distr,daarem,Rcpp (≥ 1.0.8),RcppParallel (≥ 5.1.5) |
| LinkingTo: | Rcpp,RcppArmadillo,RcppParallel |
| Suggests: | testthat,knitr,rmarkdown,ggplot2,cowplot |
| Published: | 2025-03-13 |
| DOI: | 10.32614/CRAN.package.fastglmpca |
| Author: | Eric Weine [aut, cre], Peter Carbonetto [aut], Matthew Stephens [aut] |
| Maintainer: | Eric Weine <ericweine15 at gmail.com> |
| BugReports: | https://github.com/stephenslab/fastglmpca/issues |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/stephenslab/fastglmpca |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Materials: | NEWS |
| CRAN checks: | fastglmpca results |
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