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A unified genetic association test robust to latent population structure for a count phenotype

Authors
Song, Minsun
Issue Date
Sep-2018
Publisher
WILEY
Keywords
count phenotype; genome-wide association studies; latent population structure
Citation
STATISTICS IN MEDICINE, v.37, no.20, pp.2954 - 2967
Journal Title
STATISTICS IN MEDICINE
Volume
37
Number
20
Start Page
2954
End Page
2967
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4306
DOI
10.1002/sim.7634
ISSN
0277-6715
Abstract
Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure.
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