Application of quantile regression to recent genetic and -omic studies

This paper provides a review of recent applications of quantile regression to the fields of genetic and the emerging -omic studies. It begins with a general background about this statistical approach following the seminal paper of Koenker and Bassett (Econometrica 46:33–50, 1978). Applications are described, as diverse as genetic association studies, penetrance estimation, gene expression, CGH array experiments, RNAseq experiments, methylation data and proteomics. This paper also introduces recent extensions of quantile regression with a particular focus on the Copula-quantile regression, an approach we recently proposed for sib-pair analysis. A real data example from eQTL analysis is then presented and the (R) codes, which run the analyses are provided. Finally, we conclude with some statistical software presentation and some general statements about the potential and interests of quantile regression in modern biological experiments.