This site is a development preview. As such the content and styling may not be final and is subject to change before going into production. To see more information about the redesign click here.

CellBarcode

Cellular DNA Barcode Analysis toolkit

Bioconductor version: Release (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")
10X_Barcode HTML R Script
UMI_Barcode HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

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
Linking To Rcpp, BH
Suggests BiocStyle, testthat (>= 3.0.0), knitr, rmarkdown
System Requirements
Enhances
URL
See More
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 git@git.bioconductor.org:packages/CellBarcode
Bioc Package Browser https://code.bioconductor.org/browse/CellBarcode/
Package Short Url https://bioconductor.org/packages/CellBarcode/
Package Downloads Report Download Stats