Package: hierGWAS 1.43.0

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:
hierGWAS_1.43.0.tar.gz
hierGWAS_1.43.0.zip(r-4.7)hierGWAS_1.43.0.zip(r-4.6)hierGWAS_1.43.0.zip(r-4.5)
hierGWAS_1.43.0.tgz(r-4.6-any)hierGWAS_1.43.0.tgz(r-4.5-any)
hierGWAS_1.43.0.tar.gz(r-4.7-any)hierGWAS_1.43.0.tar.gz(r-4.6-any)
hierGWAS_1.43.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
hierGWAS/json (API)
NEWS
| # Install 'hierGWAS' in R: |
| install.packages('hierGWAS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- simGWAS - Simulated GWAS data
On BioConductor:hierGWAS-1.43.0(bioc 3.24)hierGWAS-1.42.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
snplinkagedisequilibriumclustering
Last updated from:ff417c38bc. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 158 | ||
| linux-devel-x86_64 | WARNING | 187 | ||
| source / vignettes | OK | 253 | ||
| linux-release-x86_64 | WARNING | 246 | ||
| macos-release-arm64 | WARNING | 129 | ||
| macos-oldrel-arm64 | WARNING | 138 | ||
| windows-devel | WARNING | 99 | ||
| windows-release | WARNING | 90 | ||
| windows-oldrel | WARNING | 85 | ||
| wasm-release | OK | 92 |
Exports:cluster.snpcompute.r2multisplittest.hierarchy
Dependencies:codetoolsfastclusterfmsbforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Hierarchical Clustering of SNP Data | cluster.snp |
| R2 computation | compute.r2 |
| Asessing statistical significance in predictive GWA studies | hierGWAS-package hierGWAS |
| Variable Selection on Random Sample Splits. | multisplit |
| Simulated GWAS data | simGWAS |
| Hierarchical Testing of SNPs | test.hierarchy |