hierGWAS

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

Asessing statistical significance in predictive GWA studies


Bioconductor version: 3.18

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>

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

Installation

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


if (!require("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")
User manual for R-Package hierGWAS PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, LinkageDisequilibrium, SNP, Software
Version 1.32.0
In Bioconductor since BioC 3.2 (R-3.2) (8.5 years)
License GPL-3
Depends R (>= 3.2.0)
Imports fastcluster, glmnet, fmsb
System Requirements
URL
See More
Suggests BiocGenerics, RUnit, MASS
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 hierGWAS_1.32.0.tar.gz
Windows Binary hierGWAS_1.32.0.zip (64-bit only)
macOS Binary (x86_64) hierGWAS_1.32.0.tgz
macOS Binary (arm64) hierGWAS_1.32.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/hierGWAS
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/hierGWAS
Bioc Package Browser https://code.bioconductor.org/browse/hierGWAS/
Package Short Url https://bioconductor.org/packages/hierGWAS/
Package Downloads Report Download Stats