Methods for testing association between uncertain genotypes and quantitative traits.

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State: Public
Version: author
Serval ID
serval:BIB_3B14FBDAAC90
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Methods for testing association between uncertain genotypes and quantitative traits.
Journal
Biostatistics
Author(s)
Kutalik Z., Johnson T., Bochud M., Mooser V., Vollenweider P., Waeber G., Waterworth D., Beckmann J.S., Bergmann S.
ISSN
1468-4357 (Electronic)
ISSN-L
1465-4644
Publication state
Published
Issued date
2011
Peer-reviewed
Oui
Volume
12
Number
1
Pages
1-17
Language
english
Notes
Publication types: Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
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.
Keywords
Data Interpretation, Statistical, Genetic Variation/genetics, Genome-Wide Association Study/methods, Genotype, Humans, Models, Genetic, Polymorphism, Single Nucleotide/genetics, Quantitative Trait, Heritable
Pubmed
Web of science
Open Access
Yes
Create date
19/01/2011 10:45
Last modification date
20/08/2019 13:30
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