Package: scCB2 1.23.0

Zijian Ni

scCB2: CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data

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.

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

scCB2_1.23.0.tar.gz
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scCB2_1.23.0.tgz(r-4.6-any)scCB2_1.23.0.tgz(r-4.5-any)
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manual.pdf |manual.html✨
card.svg |card.png
scCB2/json (API)
NEWS

# Install 'scCB2' in R:
install.packages('scCB2', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/zijianni/sccb2/issues

Datasets:
  • mbrainSub - Subset of 1k Brain Cells from an E18 Mouse

On BioConductor:scCB2-1.23.0(bioc 3.24)scCB2-1.22.0(bioc 3.23)

dataimportrnaseqsinglecellsequencinggeneexpressiontranscriptomicspreprocessingclustering

5.42 score 11 stars 12 scripts 296 downloads 7 exports 185 dependencies

Last updated from:77e6f0162c. Checks:6 NOTE, 4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE236
linux-devel-x86_64NOTE576
source / vignettesOK438
linux-release-x86_64NOTE531
macos-release-arm64NOTE337
macos-oldrel-arm64OK328
windows-develNOTE503
windows-releaseNOTE448
windows-oldrelOK401
wasm-releaseOK190

Exports:CB2FindCellCheckBackgroundCutoffFilterGBGetCellMatQuickCB2Read10xRawRead10xRawH5

Dependencies:abindaskpassassortheadbase64encbeachmatBHBiobaseBiocGenericsbiocmakeBiocParallelbitopsbslibcachemcaToolscliclustercodetoolscommonmarkcowplotcpp11crosstalkcurldata.tableDelayedArrayDelayedMatrixStatsdeldirdigestdir.expirydoParalleldotCall64dplyrdqrngDropletUtilsedgeRevaluatefarverfastDummiesfastmapfilelockfitdistrplusFNNfontawesomeforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolsh5mreadHDF5ArrayherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalistenvlmtestlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemimeminiUInlmeopensslotelparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR.methodsS3R.ooR.utilsR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreshape2reticulaterhdf5rhdf5filtersRhdf5librlangrmarkdownROCRrprojrootRSpectraRtsneS4ArraysS4VectorsS7sassscalesscattermoresctransformscuttleSeqinfoSeuratSeuratObjectshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArraysparseMatrixStatsspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstatmodstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzoo

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

Zijian Ni and Christina Kendziorski

Rendered fromscCB2.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2022-01-18
Started: 2019-10-06