title: Bayesian statistical methods for genetic association studies.
abstract: Bayesian statistical methods have recently made great inroads into many areas of science, and this advance is now extending to the assessment of association between genetic variants and disease or other phenotypes. We review these methods, focusing on single-SNP tests in genome-wide association studies. We discuss the advantages of the Bayesian approach over classical (frequentist) approaches in this setting and provide a tutorial on basic analysis steps, including practical guidelines for appropriate prior specification. We demonstrate the use of Bayesian methods for fine mapping in candidate regions, discuss meta-analyses and provide guidance for refereeing manuscripts that contain Bayesian analyses.
authors.affiliation: Departments of Statistics and Human Genetics, University of Chicago, Chicago, IL 60637, USA. mstephens@uchicago.edu
authors.forename: Matthew
authors.initials: M
authors.lastname: Stephens
authors.forename: David J
authors.initials: DJ
authors.lastname: Balding
mesh_terms: D001499:Bayes Theorem; D055106:Genome-Wide Association Study; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*