DESCRIPTION

Type: Package
Package: ROSeq
Title: Modeling expression ranks for noise-tolerant differential expression 
    analysis of scRNA-Seq data
Version: 1.3.10
Authors@R: c(person("Krishan", "Gupta", 
    email = "krishang@iiitd.ac.in", role = c("aut","cre")),
    person("Manan", "Lalit", 
    email = "manan.lalit@gmail.com", role = c("aut")),
    person("Aditya", "Biswas", 
    email = "Adbiswa@microsoft.com", role = c("aut")),
    person("Abhik", "Ghosh", 
    email = "abhianik@gmail.com", role = c("aut")),
    person("Debarka", "Sengupta", 
    email = "debarka@gmail.com", role = c("aut")))
Description: ROSeq - A rank based approach to modeling gene expression
    with filtered and normalized read count matrix. ROSeq takes
    filtered and normalized read matrix and cell-annotation/condition
    as input and determines the differentially expressed genes between 
    the contrasting groups of single cells. One of the input parameters
    is the number of cores to be used.
URL: https://github.com/krishan57gupta/ROSeq
BugReports: https://github.com/krishan57gupta/ROSeq/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 4.0)
biocViews: 
    GeneExpression,
    DifferentialExpression,
    SingleCell
Imports: 
    pbmcapply,
    edgeR,
    limma
Suggests: 
    knitr,
    rmarkdown,
    testthat,
    RUnit, 
    BiocGenerics
VignetteBuilder: 
    knitr