Package: cytoKernel
Type: Package
Title: Differential expression using kernel-based score test
Version: 1.4.0
Date: 2021-09-27
Authors@R: 
    c(person("Tusharkanti", "Ghosh",
           email = "tusharkantighosh30@gmail.com",
           role = c("aut", "cre")),
    person("Victor", "Lui",
           role = c("aut")),
    person("Pratyaydipta", "Rudra",
           role = c("aut")),
    person("Souvik", "Seal",
           role = c("aut")), 
    person("Thao", "Vu",
           role = c("aut")),
    person("Elena", "Hsieh",
           role = c("aut")),
    person("Debashis", "Ghosh",
           role = c("aut", "cph")))
Imports: Rcpp, SummarizedExperiment, utils, methods, ComplexHeatmap,
        circlize, ashr, data.table, BiocParallel, dplyr, stats,
        magrittr, rlang, S4Vectors
LinkingTo: Rcpp
Depends: R (>= 4.1)
Suggests: knitr, rmarkdown, BiocStyle, testthat
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
Description: cytoKernel implements a kernel-based score test to
             identify differentially expressed features
             in high-dimensional biological experiments. This
             approach can be applied across many different
             high-dimensional biological data including gene 
             expression data and dimensionally reduced 
             cytometry-based marker expression data. 
             In this R package,
             we implement functions that compute the 
             feature-wise p values and their corresponding 
             adjusted p values. Additionally, it also computes
             the feature-wise shrunk effect sizes and 
             their corresponding shrunken effect size.
             Further, it calculates the percent of 
             differentially expressed features and plots 
             user-friendly heatmap of the top differentially
             expressed features on the rows and samples on the
             columns.
biocViews: ImmunoOncology, Proteomics, SingleCell, Software,
        OneChannel, FlowCytometry, DifferentialExpression,
        GeneExpression, Clustering
BugReports: https://github.com/Ghoshlab/cytoKernel/issues
RoxygenNote: 7.1.2
git_url: https://git.bioconductor.org/packages/cytoKernel
git_branch: RELEASE_3_16
git_last_commit: 0aaad3e
git_last_commit_date: 2022-11-01
Date/Publication: 2022-11-01
NeedsCompilation: yes
Packaged: 2022-11-01 23:41:27 UTC; biocbuild
Author: Tusharkanti Ghosh [aut, cre],
  Victor Lui [aut],
  Pratyaydipta Rudra [aut],
  Souvik Seal [aut],
  Thao Vu [aut],
  Elena Hsieh [aut],
  Debashis Ghosh [aut, cph]
Maintainer: Tusharkanti Ghosh <tusharkantighosh30@gmail.com>
Built: R 4.2.1; x86_64-w64-mingw32; 2022-11-02 13:28:12 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
