title: Effect of linkage disequilibrium on the identification of functional variants.
abstract: We summarize the contributions of Group 9 of Genetic Analysis Workshop 17. This group addressed the problems of linkage disequilibrium and other longer range forms of allelic association when evaluating the effects of genotypes on phenotypes. Issues raised by long-range associations, whether a result of selection, stratification, possible technical errors, or chance, were less expected but proved to be important. Most contributors focused on regression methods of various types to illustrate problematic issues or to develop adaptations for dealing with high-density genotype assays. Study design was also considered, as was graphical modeling. Although no method emerged as uniformly successful, most succeeded in reducing false-positive results either by considering clusters of loci within genes or by applying smoothing metrics that required results from adjacent loci to be similar. Two unexpected results that questioned our assumptions of what is required to model linkage disequilibrium were observed. The first was that correlations between loci separated by large genetic distances can greatly inflate single-locus test statistics, and, whether the result of selection, stratification, possible technical errors, or chance, these correlations seem overabundant. The second unexpected result was that applying principal components analysis to genome-wide genotype data can apparently control not only for population structure but also for linkage disequilibrium.
authors: Division of Genetic Epidemiology, University of Utah, Salt Lake City, UT 84108, USA. alun@genepi.med.utah.edu
authors: Alun
authors: A
authors: Thomas
authors: Haley J
authors: HJ
authors: Abel
authors: Yanming
authors: Y
authors: Di
authors: Laura L
authors: LL
authors: Faye
authors: Jing
authors: J
authors: Jin
authors: Jin
authors: J
authors: Liu
authors: Zheyan
authors: Z
authors: Wu
authors: Andrew D
authors: AD
authors: Paterson
mesh_terms: D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D056914:Genomic Structural Variation; D016045:Human Genome Project; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D015233:Models, Statistical; D017720:Molecular Epidemiology / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D025341:Principal Component Analysis; D012044:Regression Analysis