Package: scCB2
Version: 1.21.0
Date: 2023/4/18
Title: CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data 
Authors@R: c(
    person("Zijian", "Ni", role = c("aut", "cre"), email = "zni25@wisc.edu"), 
    person("Shuyang", "Chen", role="ctb"),
    person("Christina", "Kendziorski", role="ctb"))
Depends: 
    R (>= 3.6.0)
Imports: 
    SingleCellExperiment,
    SummarizedExperiment,
    Matrix,
    methods,
    utils,
    stats,
    edgeR,
    rhdf5,
    parallel,
    DropletUtils,
    doParallel,
    iterators,
    foreach,
    Seurat
Suggests: 
    testthat (>= 2.1.0),
    KernSmooth,
    beachmat,
    knitr,
    BiocStyle,
    rmarkdown
biocViews:
    DataImport,
    RNASeq,
    SingleCell,
    Sequencing,
    GeneExpression,
    Transcriptomics,
    Preprocessing,
    Clustering
Description: 
    scCB2 is an R package implementing CB2 for distinguishing real cells from empty droplets in droplet-based single cell RNA-seq experiments (especially for 10x Chromium). 
    It is based on clustering similar barcodes and calculating Monte-Carlo p-value for each cluster to test against background distribution. 
    This cluster-level test outperforms single-barcode-level tests in dealing with low count barcodes and homogeneous sequencing library, while keeping FDR well controlled.
License: GPL-3
NeedsCompilation: yes
VignetteBuilder: knitr
Encoding: UTF-8
SystemRequirements: C++11
RoxygenNote: 7.1.2
URL: https://github.com/zijianni/scCB2
BugReports: https://github.com/zijianni/scCB2/issues
git_url: https://git.bioconductor.org/packages/scCB2
git_branch: devel
git_last_commit: 6b117de
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
