DESCRIPTION

Package: diffcyt
Version: 1.23.1
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 a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.
Authors@R: person("Lukas M.", "Weber", email = "lmweberedu@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3282-1730"))
URL: https://github.com/lmweber/diffcyt
BugReports: https://github.com/lmweber/diffcyt/issues
License: MIT + file LICENSE
biocViews:
    ImmunoOncology, 
    FlowCytometry, 
    Proteomics, 
    SingleCell, 
    CellBasedAssays, 
    CellBiology, 
    Clustering, 
    FeatureExtraction, 
    Software
Depends: R (>= 3.4.0)
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,
    testthat,
    HDCytoData,
    CATALYST
RoxygenNote: 7.1.1