Fit penalized multivariable linear mixed models with a single random effect to control for population structure in genetic association studies. The goal is to simultaneously fit many genetic variants at the same time, in order to select markers that are independently associated with the response. Can also handle prior annotation information, for example, rare variants, in the form of variable weights. For more information, see the website below and the accompanying paper: Bhatnagar et al., "Simultaneous SNP selection and adjustment for population structure in high dimensional prediction models", 2020, <doi:10.1371/journal.pgen.1008766>.
Version: 0.0.2 Depends: R (≥ 3.4.0) Imports: glmnet, methods, stats, MASS, Matrix Suggests: RSpectra, popkin, bnpsd, testthat, covr, knitr, rmarkdown Published: 2021-04-13 DOI: 10.32614/CRAN.package.ggmix Author: Sahir Bhatnagar [aut, cre] (https://sahirbhatnagar.com/), Karim Oualkacha [aut] (http://karimoualkacha.uqam.ca/), Yi Yang [aut] (http://www.math.mcgill.ca/yyang/), Celia Greenwood [aut] (http://www.mcgill.ca/statisticalgenetics/) Maintainer: Sahir Bhatnagar <sahir.bhatnagar at gmail.com> BugReports: https://github.com/sahirbhatnagar/ggmix/issues License: MIT + file LICENSE URL: https://github.com/sahirbhatnagar/ggmix NeedsCompilation: no Materials: README, NEWS In views: MixedModels CRAN checks: ggmix results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=ggmix to link to this page.
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