ggmix: Variable Selection in Linear Mixed Models for SNP Data

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>.

Package details

AuthorSahir Bhatnagar [aut, cre] (, Karim Oualkacha [aut] (, Yi Yang [aut] (, Celia Greenwood [aut] (
MaintainerSahir Bhatnagar <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the ggmix package in your browser

Any scripts or data that you put into this service are public.

ggmix documentation built on April 13, 2021, 9:06 a.m.