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This is the development version of scCB2; for the stable release version, see scCB2.

CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data

Bioconductor version: Development (3.19)

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.

Author: Zijian Ni [aut, cre], Shuyang Chen [ctb], Christina Kendziorski [ctb]

Maintainer: Zijian Ni <zni25 at wisc.edu>

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biocViews Clustering, DataImport, GeneExpression, Preprocessing, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.13.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License GPL-3
Depends R (>= 3.6.0)
Imports SingleCellExperiment, SummarizedExperiment, Matrix, methods, utils, stats, edgeR, rhdf5, parallel, DropletUtils, doParallel, iterators, foreach, Seurat
System Requirements C++11
URL https://github.com/zijianni/scCB2
Bug Reports https://github.com/zijianni/scCB2/issues
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Suggests testthat (>= 2.1.0), KernSmooth, beachmat, knitr, BiocStyle, rmarkdown
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Source Package scCB2_1.13.0.tar.gz
Windows Binary scCB2_1.13.0.zip
macOS Binary (x86_64) scCB2_1.13.0.tgz
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Source Repository git clone https://git.bioconductor.org/packages/scCB2
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Bioc Package Browser https://code.bioconductor.org/browse/scCB2/
Package Short Url https://bioconductor.org/packages/scCB2/
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