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hierGWAS

This is the development version of hierGWAS; for the stable release version, see hierGWAS.

Asessing statistical significance in predictive GWA studies


Bioconductor version: Development (3.19)

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 "4.4") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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 1.33.0
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
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Suggests BiocGenerics, RUnit, MASS
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Package Archives

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

Source Package hierGWAS_1.33.0.tar.gz
Windows Binary hierGWAS_1.33.0.zip (64-bit only)
macOS Binary (x86_64) hierGWAS_1.33.0.tgz
macOS Binary (arm64) hierGWAS_1.33.0.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