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

   

This package is for version 3.4 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: 3.4

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>

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 1.2.0
In Bioconductor since BioC 3.3 (R-3.3) (1 year)
License Artistic-2.0
Depends R (>= 3.3)
Imports DBI, stringr, RSQLite, R.utils, WriteXLS, stats
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.

Package Source Uniquorn_1.2.0.tar.gz
Windows Binary Uniquorn_1.2.0.zip
Mac OS X 10.9 (Mavericks) Uniquorn_1.2.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/Uniquorn/tree/release-3.4
Package Short Url http://bioconductor.org/packages/Uniquorn/
Package Downloads Report Download Stats

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