DESCRIPTION

Package: scPCA
Title: Sparse Contrastive Principal Component Analysis
Version: 1.17.0
Authors@R: c(
    person(given = "Philippe",
           family = "Boileau",
           role = c("aut", "cre", "cph"),
           email = "philippe_boileau@berkeley.edu",
           comment = c(ORCID = "0000-0002-4850-2507")),
    person(given = "Nima",
           family = "Hejazi",
           role = "aut",
           email = "nh@nimahejazi.org",
           comment = c(ORCID = "0000-0002-7127-2789")),
    person(given = "Sandrine",
           family = "Dudoit",
           role = c("ctb", "ths"),
           email = "sandrine@stat.berkeley.edu",
           comment = c(ORCID = "0000-0002-6069-8629"))
   )
Description: A toolbox for sparse contrastive principal component analysis
    (scPCA) of high-dimensional biological data. scPCA combines the stability
    and interpretability of sparse PCA with contrastive PCA's ability to
    disentangle biological signal from unwanted variation through the use of
    control data. Also implements and extends cPCA.
Depends: R (>= 4.0.0)
Imports:
    stats,
    methods,
    assertthat,
    tibble,
    dplyr,
    purrr,
    stringr,
    Rdpack,
    matrixStats,
    BiocParallel,
    elasticnet,
    sparsepca,
    cluster,
    kernlab,
    origami,
    RSpectra,
    coop,
    Matrix,
    DelayedArray,
    ScaledMatrix,
    MatrixGenerics
Suggests:
    DelayedMatrixStats,
    sparseMatrixStats,
    testthat (>= 2.1.0),
    covr,
    knitr,
    rmarkdown,
    BiocStyle,
    ggplot2,
    ggpubr,
    splatter,
    SingleCellExperiment,
    microbenchmark
License: MIT + file LICENSE
URL: https://github.com/PhilBoileau/scPCA
BugReports: https://github.com/PhilBoileau/scPCA/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.3.1
RdMacros: Rdpack
biocViews:
    PrincipalComponent,
    GeneExpression,
    DifferentialExpression,
    Sequencing,
    Microarray,
    RNASeq