@ARTICLE{10.3389/fgene.2020.00784, AUTHOR={Arabnejad, Marziyeh and Montgomery, Courtney G. and Gaffney, Patrick M. and McKinney, Brett A.}, TITLE={Nearest-Neighbor Projected Distance Regression for Epistasis Detection in GWAS With Population Structure Correction}, JOURNAL={Frontiers in Genetics}, VOLUME={11}, YEAR={2020}, URL={https://www.frontiersin.org/articles/10.3389/fgene.2020.00784}, DOI={10.3389/fgene.2020.00784}, ISSN={1664-8021}, ABSTRACT={Nearest-neighbor Projected-Distance Regression (NPDR) is a feature selection technique that uses nearest-neighbors in high dimensional data to detect complex multivariate effects including epistasis. NPDR uses a regression formalism that allows statistical significance testing and efficient control for multiple testing. In addition, the regression formalism provides a mechanism for NPDR to adjust for population structure, which we apply to a GWAS of systemic lupus erythematosus (SLE). We also test NPDR on benchmark simulated genetic variant data with epistatic effects, main effects, imbalanced data for case-control design and continuous outcomes. NPDR identifies potential interactions in an epistasis network that influences the SLE disorder.} }