hierGWAS
Asessing statistical significance in predictive GWA studies
Bioconductor version: 3.23 · Package version: 1.42.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("hierGWAS") Details
| Maintainer | Laura Buzdugan <buzdugan@stat.math.ethz.ch> |
| Author | Laura Buzdugan |
| License | GPL-3 |
| Downloads rank | 452 |
| Source branch | RELEASE_3_23 |
| biocViews | Clustering, LinkageDisequilibrium, SNP, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | hierGWAS_1.42.0.tar.gz |
| Windows binary (x86_64) | hierGWAS_1.42.0.zip |
| macOS binary (arm64) | hierGWAS_1.42.0.tgz |
| macOS binary (x86_64) | hierGWAS_1.42.0.tgz |
Dependencies
Depends: R (>= 3.2.0)
Imports: fastcluster, glmnet, fmsb
Suggests: BiocGenerics, RUnit, MASS