Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies
Haohan Wang, Bryon Aragam, Eric P. Xing
This paper develops a truncated-rank sparse linear mixed model for variable selection in heterogeneous datasets, demonstrating its effectiveness on genomic data from plants, mice, and humans.
Methods · Aug 1, 2018Peer-reviewedGenomics