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:	0.1-103
Depends:	R (≥ 3.6)
Imports:	utils, Matrix, MatrixExtra, stats, distr, daarem, Rcpp (≥ 1.0.8), RcppParallel (≥ 5.1.5)
LinkingTo:	Rcpp, RcppArmadillo, RcppParallel
Suggests:	testthat, knitr, rmarkdown, ggplot2, cowplot
Published:	2024-01-31
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

Documentation:

Reference manual:	fastglmpca.pdf
Vignettes:	Analysis of single-cell RNA-seq data using fastglmpca

Downloads:

Package source:	fastglmpca_0.1-103.tar.gz
Windows binaries:	r-devel: fastglmpca_0.1-103.zip, r-release: fastglmpca_0.1-103.zip, r-oldrel: fastglmpca_0.1-103.zip
macOS binaries:	r-release (arm64): fastglmpca_0.1-103.tgz, r-oldrel (arm64): fastglmpca_0.1-103.tgz, r-release (x86_64): fastglmpca_0.1-103.tgz, r-oldrel (x86_64): fastglmpca_0.1-103.tgz

Linking:

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