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To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("hierGWAS")
In most cases, you don't need to download the package archive at all.
hierGWAS
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Asessing statistical significance in predictive GWA studies
Bioconductor version: Release (3.3)
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 and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("hierGWAS")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("hierGWAS")
| R Script | User manual for R-Package hierGWAS | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Clustering, LinkageDisequilibrium, SNP, Software |
| Version | 1.2.0 |
| In Bioconductor since | BioC 3.2 (R-3.2) (1 year) |
| License | GPL-3 |
| Depends | R (>= 3.2.0) |
| Imports | fastcluster, glmnet, fmsb |
| LinkingTo | |
| Suggests | BiocGenerics, RUnit, MASS |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | hierGWAS_1.2.0.tar.gz |
| Windows Binary | hierGWAS_1.2.0.zip |
| Mac OS X 10.9 (Mavericks) | hierGWAS_1.2.0.tgz |
| Subversion source | (username/password: readonly) |
| Git source | https://github.com/Bioconductor-mirror/hierGWAS/tree/release-3.3 |
| Package Short Url | http://bioconductor.org/packages/hierGWAS/ |
| Package Downloads Report | Download Stats |
Documentation »
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