CellBarcode

DOI: 10.18129/B9.bioc.CellBarcode  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see CellBarcode.

Cellular DNA Barcode Analysis toolkit

Bioconductor version: 3.17

This package performs Cellular DNA Barcode (genetic lineage tracing) analysis. The package can handle all kinds of DNA barcodes, as long as the barcode within a single sequencing read and has a pattern which can be matched by a regular expression. This package can handle barcode with flexible length, with or without UMI (unique molecular identifier). This tool also can be used for pre-processing of some amplicon sequencing such as CRISPR gRNA screening, immune repertoire sequencing and meta genome data.

Author: Wenjie Sun [cre], 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 "4.3") 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")

 

HTML R Script 10X_Barcode
HTML R Script UMI_Barcode
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews CRISPR, Preprocessing, QualityControl, Sequencing, Software
Version 1.6.0
In Bioconductor since BioC 3.14 (R-4.1) (2 years)
License MIT + file LICENSE
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
LinkingTo Rcpp, BH
Suggests BiocStyle, testthat (>= 3.0.0), knitr, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package CellBarcode_1.6.0.tar.gz
Windows Binary CellBarcode_1.6.0.zip (64-bit only)
macOS Binary (x86_64) CellBarcode_1.6.0.tgz
macOS Binary (arm64) CellBarcode_1.6.0.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

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