hierGWAS

DOI: 10.18129/B9.bioc.hierGWAS    

Asessing statistical significance in predictive GWA studies

Bioconductor version: Release (3.13)

Testing individual SNPs, as well as arbitrarily large groups of SNPs in GWA studies, using a joint model of all SNPs. The method controls the FWER, and provides an automatic, data-driven refinement of the SNP clusters to smaller groups or single markers.

Author: Laura Buzdugan

Maintainer: Laura Buzdugan <buzdugan at stat.math.ethz.ch>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("hierGWAS")

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("hierGWAS")

 

PDF	R Script	User manual for R-Package hierGWAS
PDF		Reference Manual
Text		NEWS

Details

biocViews	Clustering, LinkageDisequilibrium, SNP, Software
Version	1.22.0
In Bioconductor since	BioC 3.2 (R-3.2) (6 years)
License	GPL-3
Depends	R (>= 3.2.0)
Imports	fastcluster, glmnet, fmsb
LinkingTo
Suggests	BiocGenerics, RUnit, MASS
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	hierGWAS_1.22.0.tar.gz
Windows Binary	hierGWAS_1.22.0.zip
macOS 10.13 (High Sierra)	hierGWAS_1.22.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/hierGWAS
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/hierGWAS
Package Short Url	https://bioconductor.org/packages/hierGWAS/
Package Downloads Report	Download Stats