Package: cydar
Version: 1.36.0
Date: 2024-08-11
Title: Using Mass Cytometry for Differential Abundance Analyses
Authors@R: c(person("Aaron", "Lun", role=c("aut", "cre"), email = 
        "infinite.monkeys.with.keyboards@gmail.com"))
Depends: SingleCellExperiment
Imports: viridis, methods, shiny, graphics, stats, grDevices, utils,
        BiocGenerics, S4Vectors, BiocParallel, SummarizedExperiment,
        flowCore, Biobase, Rcpp, BiocNeighbors
Suggests: ncdfFlow, testthat, rmarkdown, knitr, edgeR, limma, glmnet,
        BiocStyle, flowStats
biocViews: ImmunoOncology, FlowCytometry, MultipleComparison,
        Proteomics, SingleCell
Description: Identifies differentially abundant populations between
        samples and groups in mass cytometry data. Provides methods for
        counting cells into hyperspheres, controlling the spatial false
        discovery rate, and visualizing changes in abundance in the
        high-dimensional marker space.
License: GPL-3
NeedsCompilation: yes
VignetteBuilder: knitr
LinkingTo: Rcpp
SystemRequirements: C++11
RoxygenNote: 7.3.2
Config/pak/sysreqs: cmake make libuv1-dev zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2026-04-28 12:45:20 UTC
RemoteUrl: https://github.com/bioc/cydar
RemoteRef: RELEASE_3_23
RemoteSha: f118583576d273530b366919fb87a5932f7a915e
Packaged: 2026-04-29 20:51:28 UTC; root
Author: Aaron Lun [aut, cre]
Maintainer: Aaron Lun <infinite.monkeys.with.keyboards@gmail.com>
Built: R 4.6.0; x86_64-w64-mingw32; 2026-04-29 20:57:48 UTC; windows
Archs: x64
