Package: hierGWAS
Title: Asessing statistical significance in predictive GWA studies
Version: 1.43.0
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'
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:41:24 UTC
RemoteUrl: https://github.com/bioc/hierGWAS
RemoteRef: HEAD
RemoteSha: ff417c38bc2c855f4e323e88013dfe8166ea529c
NeedsCompilation: no
Packaged: 2026-07-03 19:10:06 UTC; root