hierGWAS
This is the development version of hierGWAS; for the stable release version, see hierGWAS.
All Bioconductor versions of hierGWAS
3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4, 3.3, 3.2
Asessing statistical significance in predictive GWA studies
Bioconductor version: 3.24 · Package version: 1.43.0
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"):
Laura Buzdugan. hierGWAS: Asessing statistical significance in predictive GWA studies. doi:10.18129/B9.bioc.hierGWAS, R package version 1.43.0, https://bioconductor.org/packages/hierGWAS.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
BiocManager::install("hierGWAS")For older versions of R, please refer to the appropriate Bioconductor release.
Details
| Version | 1.43.0 |
| License | GPL-3 |
| Last updated | 2026-04-28 |
| In Bioconductor since | BioC 3.2 (R-3.2) (10 years) |
| Downloads rank | 1422 of 2,456 |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Clustering, LinkageDisequilibrium, SNP, Software |
| Package Short Url | https://bioconductor.org/packages/hierGWAS/ |
Documentation
| Reference Manual | |
| NEWS | Text |
Download
Follow the installation instructions to use this package in your R session.
| Source package | hierGWAS_1.43.0.tar.gz |
| Windows binary (x86_64) | hierGWAS_1.43.0.zip |
| macOS binary (arm64) | hierGWAS_1.43.0.tgz |
| macOS binary (x86_64) | hierGWAS_1.43.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/hierGWAS |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/hierGWAS |
| Package Downloads Report | Download Stats |
Dependencies
Depends: R (>= 3.2.0)
Imports: fastcluster, glmnet, fmsb
Suggests: BiocGenerics, RUnit, MASS