hierGWAS
Asessing statistical significance in predictive GWA studies
Bioconductor version: Release (3.20)
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")
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 | R Script | |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Clustering, LinkageDisequilibrium, SNP, Software |
Version | 1.36.0 |
In Bioconductor since | BioC 3.2 (R-3.2) (9 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_1.36.0.tar.gz |
Windows Binary (x86_64) | hierGWAS_1.36.0.zip |
macOS Binary (x86_64) | hierGWAS_1.36.0.tgz |
macOS Binary (arm64) | hierGWAS_1.36.0.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 |