Package: hierGWAS
Title: Asessing statistical significance in predictive GWA studies
Version: 1.20.0
Author: Laura Buzdugan
Maintainer: Laura Buzdugan <buzdugan@stat.math.ethz.ch>
Description: 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.
Depends: R (>= 3.2.0)
License: GPL-3
LazyData: true
Imports: fastcluster,glmnet, fmsb
Suggests: BiocGenerics, RUnit, MASS
biocViews: SNP, LinkageDisequilibrium, Clustering
Collate: 'cluster.snp.R' 'lasso.select.R' 'multisplit.R' 'MEL.R'
        'test.snp.R' 'adj.pval.R' 'comp.cluster.pval.R'
        'iterative.DFS.R' 'test.hierarchy.R' 'return.r2.R'
        'compute.r2.R'
git_url: https://git.bioconductor.org/packages/hierGWAS
git_branch: RELEASE_3_12
git_last_commit: 1559099
git_last_commit_date: 2020-10-27
Date/Publication: 2020-10-27
NeedsCompilation: no
Packaged: 2020-10-28 02:16:45 UTC; biocbuild
Built: R 4.0.3; ; 2020-10-28 14:25:52 UTC; windows
