Ying Wei, Columbia University
Genetic research is of great importance for public health. The current analysis tools employed in genetic research are mostly mean-based, which only reveal a partial picture of the genetic association. More and more recent studies discovered heterogeneity in genetic associations, and such heterogeneity plays an important role in genetic functions. By estimating conditional quantiles, quantile regression, proposed by Koenker and Bassett (1978), offers a systematic strategy for examining how covariates influence the entire response distribution. This talk will review recent methodology development and applications of quantile regression in genetic research, and provide two case studies where quantile regression enhances the Genome Wide Association Studies and eQTL discoveries.