This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see scCB2.
Bioconductor version: 3.13
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>
Citation (from within R,
enter citation("scCB2")
):
To install this package, start R (version "4.1") and enter:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("scCB2")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("scCB2")
HTML | R Script | CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data |
Reference Manual | ||
Text | NEWS |
biocViews | Clustering, DataImport, GeneExpression, Preprocessing, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Version | 1.2.0 |
In Bioconductor since | BioC 3.12 (R-4.0) (1 year) |
License | GPL-3 |
Depends | R (>= 3.6.0) |
Imports | SingleCellExperiment, SummarizedExperiment, Matrix, methods, utils, stats, edgeR, rhdf5, parallel, DropletUtils, doParallel, iterators, foreach, Seurat |
LinkingTo | |
Suggests | testthat (>= 2.1.0), KernSmooth, beachmat, knitr, BiocStyle, rmarkdown |
SystemRequirements | C++11 |
Enhances | |
URL | https://github.com/zijianni/scCB2 |
BugReports | https://github.com/zijianni/scCB2/issues |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | scCB2_1.2.0.tar.gz |
Windows Binary | scCB2_1.2.0.zip |
macOS 10.13 (High Sierra) | scCB2_1.2.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/scCB2 |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/scCB2 |
Package Short Url | https://bioconductor.org/packages/scCB2/ |
Package Downloads Report | Download Stats |
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