rPGBS
stable variable selection for high-dimensional genomic data with strong correlations
rPGBS is a statistical framework for Stable Variable Selection for High-Dimensional Genomic Data with Strong Correlations. It implements two-stage hierarchical approach to variable selection consisting of a random pseudo-group clustering and bi-level variable selection.
Developed as part of an REU at UNC Greensoboro while I was an undergraduate at Texas A&M University.
You can install the package directly from Xiaoli Gao’s website: rPGBS Package.