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

DOI: 10.18129/B9.bioc.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 (3.6)

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")

 

PDF R Script User manual for R-Package hierGWAS
PDF   Reference Manual
Text   NEWS

Details

biocViews Clustering, LinkageDisequilibrium, SNP, Software
Version 1.7.0
In Bioconductor since BioC 3.2 (R-3.2) (2 years)
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.

Source Package hierGWAS_1.7.0.tar.gz
Windows Binary hierGWAS_1.7.0.zip
Mac OS X 10.11 (El Capitan) hierGWAS_1.7.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/hierGWAS
Package Short Url http://bioconductor.org/packages/hierGWAS/
Package Downloads Report Download Stats

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