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,