Package: diffcyt
Version: 1.0.10
Title: Differential discovery in high-dimensional cytometry via
        high-resolution clustering
Description: Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on (i) high-resolution clustering and (ii) empirical Bayes moderated tests adapted from transcriptomics.
Authors@R: person("Lukas M.", "Weber", email = "lukmweber@gmail.com", role = c("aut", "cre"))
URL: https://github.com/lmweber/diffcyt
BugReports: https://github.com/lmweber/diffcyt/issues
License: MIT + file LICENSE
biocViews: FlowCytometry, Proteomics, SingleCell, CellBasedAssays,
        CellBiology, Clustering, FeatureExtraction, Software
Depends: R (>= 3.5.0)
Imports: flowCore, FlowSOM, SummarizedExperiment, S4Vectors, limma,
        edgeR, lme4, multcomp, dplyr, tidyr, reshape2, magrittr, stats,
        methods, utils, grDevices, graphics, ComplexHeatmap, circlize,
        grid
VignetteBuilder: knitr
Suggests: BiocStyle, knitr, rmarkdown, HDCytoData, CATALYST
RoxygenNote: 6.1.0
git_url: https://git.bioconductor.org/packages/diffcyt
git_branch: RELEASE_3_7
git_last_commit: 7792f0c
git_last_commit_date: 2018-08-15
Date/Publication: 2018-08-15
NeedsCompilation: no
Packaged: 2018-08-16 04:06:13 UTC; biocbuild
Author: Lukas M. Weber [aut, cre]
Maintainer: Lukas M. Weber <lukmweber@gmail.com>
Built: R 3.5.1; ; 2018-08-16 10:05:06 UTC; windows
