Package: scCB2 1.17.0

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]

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scCB2.pdf |scCB2.html✨
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NEWS

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

Peer review:

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

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

On BioConductor:scCB2-1.17.0(bioc 3.21)scCB2-1.16.0(bioc 3.20)

dataimportrnaseqsinglecellsequencinggeneexpressiontranscriptomicspreprocessingclustering

5.30 score 10 stars 5 scripts 151 downloads 7 exports 188 dependencies

Last updated 2 months agofrom:1e577d447c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 30 2024
R-4.5-winOKNov 30 2024
R-4.5-linuxOKNov 30 2024
R-4.4-winOKNov 30 2024
R-4.4-macOKNov 30 2024
R-4.3-winOKNov 30 2024
R-4.3-macOKNov 30 2024

Exports:CB2FindCellCheckBackgroundCutoffFilterGBGetCellMatQuickCB2Read10xRawRead10xRawH5

Dependencies:abindaskpassassortheadbase64encbeachmatBHBiobaseBiocGenericsBiocParallelbitopsbslibcachemcaToolscliclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArrayDelayedMatrixStatsdeldirdigestdoParalleldotCall64dplyrdqrngDropletUtilsedgeRevaluatefansifarverfastDummiesfastmapfitdistrplusFNNfontawesomeforeachformatRfsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolsHDF5ArrayherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlifecyclelimmalistenvlmtestlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImunsellnlmeopensslparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR.methodsS3R.ooR.utilsR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreshape2reticulaterhdf5rhdf5filtersRhdf5librlangrmarkdownROCRrprojrootRSpectraRtsneS4ArraysS4VectorssassscalesscattermoresctransformscuttleSeuratSeuratObjectshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArraysparseMatrixStatsspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstatmodstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo

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

Zijian Ni and Christina Kendziorski

Rendered fromscCB2.Rmdusingknitr::rmarkdownon Nov 30 2024.

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