Uniquorn

This package is for version 3.6 of Bioconductor; for the stable, up-to-date release version, see Uniquorn.

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


Bioconductor version: 3.6

Identifies cancer cell lines with their small variant fingerprint. 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 or loci of somatic and germline mutations or variations. The input format is vcf and the files have to contain a single cancer cell line sample. 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>

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

Installation

To install this package, start R (version "3.4") 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

Reference Manual PDF
NEWS Text

Details

biocViews ExomeSeq, Software, StatisticalMethod, WholeGenome
Version 1.6.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License Artistic-2.0
Depends R (>= 3.4)
Imports DBI, stringr, RSQLite, R.utils, WriteXLS, stats, BiocParallel
System Requirements
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Suggests testthat, knitr, rmarkdown, BiocGenerics, RUnit
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Package Archives

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

Source Package Uniquorn_1.6.0.tar.gz
Windows Binary Uniquorn_1.6.0.zip
Mac OS X 10.11 (El Capitan) Uniquorn_1.6.0.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/
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Old Source Packages for BioC 3.6 Source Archive