Package: scry
Title: Small-Count Analysis Methods for High-Dimensional Data
Version: 1.23.0
Description: Many modern biological datasets consist of small counts that are 
            not well fit by standard linear-Gaussian methods such as principal
            component analysis. This package provides implementations of 
            count-based feature selection and dimension reduction algorithms.
            These methods can be used to facilitate unsupervised analysis
            of any high-dimensional data such as single-cell RNA-seq.
Authors@R: c(person("Kelly", "Street", email = "street.kelly@gmail.com", 
                role = c("aut", "cre")),
            person("F. William", "Townes", email = "will.townes@gmail.com",
                role = c("aut",  "cph")),
            person("Davide", "Risso", email = "risso.davide@gmail.com",
                role = "aut"),
            person("Stephanie", "Hicks", email = "shicks19@jhu.edu",
                role = "aut")
            )
License: Artistic-2.0
Depends:
    R (>= 4.0),
    stats,
    methods
Imports:
    DelayedArray,
    glmpca (>= 0.2.0),
    Matrix,
    SingleCellExperiment,
    SummarizedExperiment,
    BiocSingular
Suggests:
    BiocGenerics,
    covr,
    DuoClustering2018,
    ggplot2,
    HDF5Array,
    knitr,
    markdown,
    rmarkdown,
    TENxPBMCData,
    testthat
VignetteBuilder: knitr
LazyData: false
URL: https://bioconductor.org/packages/scry.html
BugReports: https://github.com/kstreet13/scry/issues
RoxygenNote: 7.2.2
Encoding: UTF-8
biocViews:
    DimensionReduction,
    GeneExpression,
    Normalization,
    PrincipalComponent,
    RNASeq,
    Software,
    Sequencing,
    SingleCell,
    Transcriptomics
git_url: https://git.bioconductor.org/packages/scry
git_branch: devel
git_last_commit: 0eeb235
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
