To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("Uniquorn")

In most cases, you don't need to download the package archive at all.

Uniquorn

DOI: 10.18129/B9.bioc.Uniquorn    

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

Bioconductor version: Release (3.5)

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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("Uniquorn")

Documentation

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PDF   Reference Manual
Text   NEWS

Details

biocViews ExomeSeq, Software, StatisticalMethod, WholeGenome
Version 1.4.2
In Bioconductor since BioC 3.3 (R-3.3) (1.5 years)
License Artistic-2.0
Depends R (>= 3.4)
Imports DBI, stringr, RSQLite, R.utils, WriteXLS, stats, BiocParallel
LinkingTo
Suggests testthat, knitr, rmarkdown, BiocGenerics, RUnit
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package Uniquorn_1.4.2.tar.gz
Windows Binary Uniquorn_1.4.2.zip
Mac OS X 10.11 (El Capitan) Uniquorn_1.4.2.tgz
Source Repository git clone https://git.bioconductor.org/packages/Uniquorn
Package Short Url http://bioconductor.org/packages/Uniquorn/
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