A comment on two-locus epistatic interaction models for genome-wide association studies

Detection of epistatic interactions in genome-wide association studies is a computationally hard problem. Many detection algorithms have been proposed and will continue to be. Most of those algorithms measure their predictive power by running on simulated data many times under various disease models...

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Bibliographic Details
Published inJournal of bioinformatics and computational biology Vol. 13; no. 6; p. 1571004
Main Authors Sohn, Kyung-Ah, Wee, Kyubum
Format Journal Article
LanguageEnglish
Published Singapore 01.12.2015
Subjects
Epistasis, Genetic
Genetic Predisposition to Disease
Genome-Wide Association Study - methods
Humans
Models, Genetic
Penetrance
Polymorphism, Single Nucleotide
GWAS
epistasis
disease models
simulation study
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Summary:Detection of epistatic interactions in genome-wide association studies is a computationally hard problem. Many detection algorithms have been proposed and will continue to be. Most of those algorithms measure their predictive power by running on simulated data many times under various disease models. However, we find that there have been subtle differences in interpreting the meaning of existing disease models among the previous studies on detection of epistatic interactions. We elucidate those differences and suggest that future studies on epistatic interactions in GWAS state explicitly which versions/interpretations are employed. We also provide a way to facilitate setting parameters of disease models.
ISSN:1757-6334
DOI:10.1142/S0219720015710043