DESCRIPTION

Package: singlet
Type: Package
Title: Non-negative Matrix Factorization for single-cell analysis
Version: 0.99.8
Date: 2024-10-15
Author: Zach Debruine <debruinz@gvsu.edu>
Maintainer: Zach Debruine <debruinz@gvsu.edu>
Authors@R: c(person("Zach", "DeBruine", 
             email = "debruinz@gvsu.edu", 
             role = c("aut", "cre"), 
             comment = c(ORCID = "0000-0003-2234-4827")),
             person("Tim", "Triche",
             email = "trichelab@gmail.com", 
             role = c("aut"), 
             comment = c(ORCID = "0000-0001-5665-946X")),
             person("Chan Zuckerberg Initiative", 
             role = c("fnd"), 
             comment = "https://chanzuckerberg.com/science/programs-resources/single-cell-biology/data-insights/efficient-data-structures-for-single-cell-data-integration/"))
Description: Fast NMF with automatic rank-determination for dimension reduction of single-cell data using Seurat, RcppML nmf, SingleCellExperiments and similar.
License: GPL (>= 2)
Depends:
    Seurat,
    RcppML,
    dplyr,
    RcppEigen
Imports:
    Matrix,
    methods,
    stats,
    knitr,
    ggplot2,
    limma,
    reshape2,
    utils,
    fgsea,
    msigdbr,
    RcppML,
    statmod
LinkingTo: 
    Rcpp,
    RcppEigen
Suggests: 
    rmarkdown, 
    devtools,
    cowplot,
    viridis,
    testthat (>= 3.0.0),
    SingleCellExperiment,
    rWikiPathways,
    plotly,
    igvR
VignetteBuilder: knitr
RoxygenNote: 7.3.2
Config/testthat/edition: 3
URL: https://github.com/zdebruine/singlet
LazyData: true
BugReports: https://github.com/zdebruine/singlet/issues
Encoding: UTF-8