Package: vGWAS 2025.05.18
vGWAS: Variance Heterogeneity Genome-wide Association Study - Reimplementation
The package reimplementation provides models and tests for variance heterogeneity genome-wide association study (vGWAS).
Authors:
vGWAS_2025.05.18.tar.gz
vGWAS_2025.05.18.zip(r-4.7-any)vGWAS_2025.05.18.zip(r-4.6-any)vGWAS_2025.05.18.zip(r-4.5-any)
vGWAS_2025.05.18.tgz(r-4.6-any)vGWAS_2025.05.18.tgz(r-4.5-any)
vGWAS_2025.05.18.tar.gz(r-4.7-any)vGWAS_2025.05.18.tar.gz(r-4.6-any)
vGWAS_2025.05.18.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
vGWAS/json (API)
| # Install 'vGWAS' in R: |
| install.packages('vGWAS', repos = c('https://kullrich.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kullrich/vgwas/issues
Pkgdown/docs site:https://kullrich.github.io
- chr - Chromosome Indices for The Markers of The Simulated Data
- geno - The Marker Genotypes of The Simulated Data
- geno.df - The Marker Genotypes of The Simulated Data
- geno.num - The Marker Genotypes of The Simulated Data
- geno.sparse - The Marker Genotypes of The Simulated Data
- map - Map Positions for The Markers of The Simulated Data
- pheno - Phenotypic Values for The Markers of The Simulated Data
Last updated from:1b053e39f3. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 337 | ||
| source / vignettes | OK | 335 | ||
| linux-release-x86_64 | OK | 327 | ||
| macos-release-arm64 | OK | 199 | ||
| macos-oldrel-arm64 | OK | 167 | ||
| windows-devel | OK | 313 | ||
| windows-release | OK | 235 | ||
| windows-oldrel | OK | 263 | ||
| wasm-release | OK | 138 |
Exports:bfmedian.testbrown.forsythe.testgetMAFvGWASvGWAS.gcvGWAS.variancevGWASparallel
Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11DerivdoBydoParalleldplyrfarverforeachforecastFormulafracdiffgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrmomentsnlmenloptrnnetnortestnumDerivonewaytestspbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewesandersonwithrzoo
Last update: 2025-05-17
Started: 2019-08-22
Last update: 2024-10-23
Started: 2024-10-23
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Brown-Forsythe's Test of Equality of Variances | bfmedian.test |
| Brown-Forsythe's Test of Equality of Variances | brown.forsythe.test |
| Chromosome Indices for The Markers of The Simulated Data | chr chr-data |
| The Marker Genotypes of The Simulated Data | geno geno-data |
| The Marker Genotypes of The Simulated Data (as data.frame) | geno.df geno.df-data |
| The Marker Genotypes of The Simulated Data (as matrix) | geno.num geno.num-data |
| The Marker Genotypes of The Simulated Data (as sparse matrix) | geno.sparse geno.sparse-data |
| Get minor-allele-frequency | getMAF |
| Map Positions for The Markers of The Simulated Data | map map-data |
| Variance Heterogeneity Genome-wide Association Study | package-vGWAS |
| Phenotypic Values for The Markers of The Simulated Data | pheno pheno-data |
| Variance GWA Manhattan Plot | plot.vGWAS |
| Variance GWA Summary | summary.vGWAS |
| Variance Genome-wide Association | vGWAS |
| Genomic Control for vGWAS | vGWAS.gc |
| Calculating Variance Explained by A Single Marker | vGWAS.variance |
| Variance Genome-wide Association (parallel) | vGWASparallel |
