title: Methods for testing association between uncertain genotypes and quantitative traits.
abstract: Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.
authors.affiliation: Department of Medical Genetics, University of Lausanne, Rue du Bugnon 27, 1005 Lausanne, Switzerland. zoltan.kutalik@unil.ch
authors.forename: Zoltán
authors.initials: Z
authors.lastname: Kutalik
authors.forename: Toby
authors.initials: T
authors.lastname: Johnson
authors.forename: Murielle
authors.initials: M
authors.lastname: Bochud
authors.forename: Vincent
authors.initials: V
authors.lastname: Mooser
authors.forename: Peter
authors.initials: P
authors.lastname: Vollenweider
authors.forename: Gérard
authors.initials: G
authors.lastname: Waeber
authors.forename: Dawn
authors.initials: D
authors.lastname: Waterworth
authors.forename: Jacques S
authors.initials: JS
authors.lastname: Beckmann
authors.forename: Sven
authors.initials: S
authors.lastname: Bergmann
mesh_terms: D003627:Data Interpretation, Statistical; D014644:Genetic Variation / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D019655:Quantitative Trait, Heritable