Uniquorn

DOI: 10.18129/B9.bioc.Uniquorn    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see Uniquorn.

Identification of cancer cell lines based on their weighted mutational/ variational fingerprint

Bioconductor version: 3.15

This packages enables users to identify cancer cell lines. Cancer cell line misidentification and cross-contamination reprents a significant challenge for cancer researchers. The identification is vital and in the frame of this package based on the locations/ loci of somatic and germline mutations/ variations. The input format is vcf/ vcf.gz and the files have to contain a single cancer cell line sample (i.e. a single member/genotype/gt column in the vcf file). The implemented method is optimized for the Next-generation whole exome and whole genome DNA-sequencing technology. RNA-seq data is very likely to work as well but hasn't been rigiously tested yet. Panel-seq will require manual adjustment of thresholds

Author: Raik Otto

Maintainer: 'Raik Otto' <raik.otto at hu-berlin.de>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("Uniquorn")

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("Uniquorn")

 

HTML	R Script	Uniquorn vignette
PDF		Reference Manual
Text		NEWS

Details

biocViews	ExomeSeq, ImmunoOncology, Software, StatisticalMethod, WholeGenome
Version	2.16.0
In Bioconductor since	BioC 3.3 (R-3.3) (6.5 years)
License	Artistic-2.0
Depends	R (>= 3.5)
Imports	stringr, R.utils, WriteXLS, stats, doParallel, foreach, GenomicRanges, IRanges, VariantAnnotation
LinkingTo
Suggests	testthat, knitr, rmarkdown, BiocGenerics, RUnit
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	Uniquorn_2.16.0.tar.gz
Windows Binary	Uniquorn_2.16.0.zip
macOS Binary (x86_64)	Uniquorn_2.16.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/Uniquorn
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/Uniquorn
Package Short Url	https://bioconductor.org/packages/Uniquorn/
Package Downloads Report	Download Stats