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,
- Version0.0.2
- R version≥ 3.4.0
- LicenseMIT
- Licensefile LICENSE
- Needs compilation?No
- Last release04/13/2021
Documentation
Team
Sahir Bhatnagar
Karim Oualkacha
Show author detailsRolesAuthorYi Yang
Show author detailsRolesAuthorCelia Greenwood
Show author detailsRolesAuthor
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- Depends1 package
- Imports5 packages
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