Package: cudacellr
Title: GPU-Aware Single-Cell Analysis Workflows
Version: 0.4.0
Authors@R: 
    person("Yaoxiang", "Li", email = "liyaoxiang@outlook.com",
           role = c("aut", "cre"))
Description: Provides single-cell analysis primitives
    for sparse count matrices, including library-size normalization,
    log-normalization, highly variable feature selection, principal component
    analysis, and nearest-neighbour construction. Integrates the 'cudaverse'
    numerical and sparse layers while preserving matrix identifiers and
    recording the computation backend for each stage.
    Optional adapters preserve native 'SingleCellExperiment' and
    'SeuratObject' version 5 object structures.
License: MIT + file LICENSE
URL: https://cudaverse.github.io/cudacellr/,
        https://github.com/cudaverse/cudacellr
BugReports: https://github.com/cudaverse/cudacellr/issues
Encoding: UTF-8
Imports: cudaverse (>= 0.4.1), Matrix, methods
Suggests: DelayedArray, knitr, rmarkdown, S4Vectors, SeuratObject (>=
        5.0.0), SingleCellExperiment, SummarizedExperiment, testthat
        (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-10-07 18:09:04 UTC; Li
Author: Yaoxiang Li [aut, cre]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: CRAN
Date/Publication: 2026-10-27 18:00:14 UTC
