Package: cydar
Version: 1.12.0
Date: 2020-04-06
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, 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: 7.1.0
git_url: https://git.bioconductor.org/packages/cydar
git_branch: RELEASE_3_11
git_last_commit: 84e89cc
git_last_commit_date: 2020-04-27
Date/Publication: 2020-04-27
Packaged: 2020-04-28 02:58:57 UTC; biocbuild
Author: Aaron Lun [aut, cre]
Maintainer: Aaron Lun <infinite.monkeys.with.keyboards@gmail.com>
Built: R 4.0.0; x86_64-conda_cos6-linux-gnu; 2020-05-17 23:08:15 UTC; unix
