CellBarcode

This is the released version of CellBarcode; for the devel version, see CellBarcode.

Cellular DNA Barcode Analysis toolkit


Bioconductor version: Release (3.20)

The package CellBarcode performs Cellular DNA Barcode analysis. It can handle all kinds of DNA barcodes, as long as the barcode is within a single sequencing read and has a pattern that can be matched by a regular expression. \code{CellBarcode} can handle barcodes with flexible lengths, with or without UMI (unique molecular identifier). This tool also can be used for pre-processing some amplicon data such as CRISPR gRNA screening, immune repertoire sequencing, and metagenome data.

Author: Wenjie Sun [cre, aut] , Anne-Marie Lyne [aut], Leila Perie [aut]

Maintainer: Wenjie Sun <sunwjie at gmail.com>

Citation (from within R, enter citation("CellBarcode")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("CellBarcode")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("CellBarcode")
10X_Barcode HTML R Script
UMI_Barcode HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews CRISPR, Preprocessing, QualityControl, Sequencing, Software
Version 1.12.0
In Bioconductor since BioC 3.14 (R-4.1) (3 years)
License Artistic-2.0
Depends R (>= 4.1.0)
Imports methods, stats, Rcpp (>= 1.0.5), data.table (>= 1.12.6), plyr, ggplot2, stringr, magrittr, ShortRead(>= 1.48.0), Biostrings(>= 2.58.0), egg, Ckmeans.1d.dp, utils, S4Vectors, seqinr, zlibbioc, Rsamtools
System Requirements
URL https://wenjie1991.github.io/CellBarcode/
Bug Reports https://github.com/wenjie1991/CellBarcode/issues
See More
Suggests BiocStyle, testthat (>= 3.0.0), knitr, rmarkdown
Linking To Rcpp, BH
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package CellBarcode_1.12.0.tar.gz
Windows Binary (x86_64) CellBarcode_1.12.0.zip
macOS Binary (x86_64) CellBarcode_1.12.0.tgz
macOS Binary (arm64) CellBarcode_1.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/CellBarcode
Source Repository (Developer Access) git clone [email protected]:packages/CellBarcode
Bioc Package Browser https://code.bioconductor.org/browse/CellBarcode/
Package Short Url https://bioconductor.org/packages/CellBarcode/
Package Downloads Report Download Stats