geneAttribution

This package is for version 3.18 of Bioconductor; for the stable, up-to-date release version, see geneAttribution.

Identification of candidate genes associated with genetic variation


Bioconductor version: 3.18

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>

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

Installation

To install this package, start R (version "4.3") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("geneAttribution")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("geneAttribution")
Vignette Title HTML
Reference Manual PDF
NEWS Text

Details

biocViews GenePrediction, GenomeWideAssociation, GenomicVariation, SNP, Software, VariantAnnotation
Version 1.28.0
In Bioconductor since BioC 3.4 (R-3.3) (7.5 years)
License Artistic-2.0
Depends
Imports utils, GenomicRanges, org.Hs.eg.db, BiocGenerics, GenomeInfoDb, GenomicFeatures, IRanges, rtracklayer
System Requirements
URL
See More
Suggests TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Hsapiens.UCSC.hg19.knownGene, knitr, rmarkdown, testthat
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package geneAttribution_1.28.0.tar.gz
Windows Binary geneAttribution_1.28.0.zip (64-bit only)
macOS Binary (x86_64) geneAttribution_1.28.0.tgz
macOS Binary (arm64) geneAttribution_1.28.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/geneAttribution
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/geneAttribution
Bioc Package Browser https://code.bioconductor.org/browse/geneAttribution/
Package Short Url https://bioconductor.org/packages/geneAttribution/
Package Downloads Report Download Stats