title: Expression QTLs Mapping and Analysis: A Bayesian Perspective.
abstract: The aim of expression Quantitative Trait Locus (eQTL) mapping is the identification of DNA sequence variants that explain variation in gene expression. Given the recent yield of trait-associated genetic variants identified by large-scale genome-wide association analyses (GWAS), eQTL mapping has become a useful tool to understand the functional context where these variants operate and eventually narrow down functional gene targets for disease. Despite its extensive application to complex (polygenic) traits and disease, the majority of eQTL studies still rely on univariate data modeling strategies, i.e., testing for association of all transcript-marker pairs. However these "one at-a-time" strategies are (1) unable to control the number of false-positives when an intricate Linkage Disequilibrium structure is present and (2) are often underpowered to detect the full spectrum of trans-acting regulatory effects. Here we present our viewpoint on the most recent advances on eQTL mapping approaches, with a focus on Bayesian methodology. We review the advantages of the Bayesian approach over frequentist methods and provide an empirical example of polygenic eQTL mapping to illustrate the different properties of frequentist and Bayesian methods. Finally, we discuss how multivariate eQTL mapping approaches have distinctive features with respect to detection of polygenic effects, accuracy, and interpretability of the results.
authors.affiliation: Centre for Complement and Inflammation Research, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK.
authors.forename: Martha
authors.initials: M
authors.lastname: Imprialou
authors.affiliation: Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore. enrico.petretto@duke-nus.edu.sg.
authors.forename: Enrico
authors.initials: E
authors.lastname: Petretto
authors.affiliation: Department of Medical Genetics, University of Cambridge, Box 238, Lv 6 Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. lb664@cam.ac.uk.|Department of Mathematics, Imperial College London, 180 Queen's Gate, London, SW7 2AZ, UK. lb664@cam.ac.uk.
authors.forename: Leonardo
authors.initials: L
authors.lastname: Bottolo
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002874:Chromosome Mapping / Q000379:methods*; D015870:Gene Expression; D014644:Genetic Variation; D055106:Genome-Wide Association Study / Q000379:methods; D015233:Models, Statistical; D040641:Quantitative Trait Loci; D012984:Software; D064878:Web Browser
keywords: Bayesian variable selection; IT-tools for systems genetics; LASSO; Penalized-regression; Polygenic eQTL; trans-eQTLs