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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
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Identification of cancer cell lines based on their weighted mutational/ variational fingerprint
Bioconductor version: Release (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
| HTML | R Script | Vignette Title |
| 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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