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: 2026-10-27 20:24:39 UTC; root
Author: Yaoxiang Li [aut, cre]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-10-27 18:48:44 UTC
RemoteUrl: https://github.com/cran/cudacellr
RemoteRef: HEAD
RemoteSha: 4c94e8e4aaa41ecce2e2b3d3384e6e8a58d246f7