Package: hierGWAS 1.37.0

Laura Buzdugan

hierGWAS: Asessing statistical significance in predictive GWA studies

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.

Authors:Laura Buzdugan

hierGWAS_1.37.0.tar.gz
hierGWAS_1.37.0.zip(r-4.5)hierGWAS_1.37.0.zip(r-4.4)hierGWAS_1.37.0.zip(r-4.3)
hierGWAS_1.37.0.tgz(r-4.4-any)hierGWAS_1.37.0.tgz(r-4.3-any)
hierGWAS_1.37.0.tar.gz(r-4.5-noble)hierGWAS_1.37.0.tar.gz(r-4.4-noble)
hierGWAS_1.37.0.tgz(r-4.4-emscripten)hierGWAS_1.37.0.tgz(r-4.3-emscripten)
hierGWAS.pdf |hierGWAS.html✨
hierGWAS/json (API)
NEWS

# Install 'hierGWAS' in R:
install.packages('hierGWAS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On BioConductor:hierGWAS-1.35.0(bioc 3.20)hierGWAS-1.34.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

snplinkagedisequilibriumclustering

3.30 score 1 scripts 205 downloads 4 exports 12 dependencies

Last updated 23 days agofrom:06911bf824. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winWARNINGOct 30 2024
R-4.5-linuxWARNINGOct 30 2024
R-4.4-winWARNINGOct 30 2024
R-4.4-macWARNINGOct 30 2024
R-4.3-winWARNINGOct 30 2024
R-4.3-macWARNINGOct 30 2024

Exports:cluster.snpcompute.r2multisplittest.hierarchy

Dependencies:codetoolsfastclusterfmsbforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival

User manual for R-Package hierGWAS

Rendered fromhierGWAS.Rnwusingutils::Sweaveon Oct 30 2024.

Last update: 2015-06-08
Started: 2015-06-08