geneAttribution

DOI: 10.18129/B9.bioc.geneAttribution    

Identification of candidate genes associated with genetic variation

Bioconductor version: Release (3.6)

Identification of the most likely gene or genes through which variation at a given genomic locus in the human genome acts. The most basic functionality assumes that the closer gene is to the input locus, the more likely the gene is to be causative. Additionally, any empirical data that links genomic regions to genes (e.g. eQTL or genome conformation data) can be used if it is supplied in the UCSC .BED file format.

Author: Arthur Wuster

Maintainer: Arthur Wuster <wustera at gene.com>

Installation

To install this package, start R and enter:

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

Documentation

HTML		Vignette Title
PDF		Reference Manual
Text		NEWS

Details

biocViews	GenePrediction, GenomeWideAssociation, GenomicVariation, SNP, Software, VariantAnnotation
Version	1.4.0
In Bioconductor since	BioC 3.4 (R-3.3) (1.5 years)
License	Artistic-2.0
Depends
Imports	utils, GenomicRanges, org.Hs.eg.db, BiocGenerics, GenomeInfoDb, GenomicFeatures, IRanges, rtracklayer
LinkingTo
Suggests	TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown, testthat
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	geneAttribution_1.4.0.tar.gz
Windows Binary	geneAttribution_1.4.0.zip
Mac OS X 10.11 (El Capitan)	geneAttribution_1.4.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/geneAttribution
Package Short Url	http://bioconductor.org/packages/geneAttribution/
Package Downloads Report	Download Stats