Two-stage two-locus models in genome-wide association

Evans D.M., Marchini J., Morris A.P. and Cardon L.R. (2006) Two-stage two-locus models in genome-wide association. PLoS Genetics, 2 9: 1424-1432. doi:10.1371/journal.pgen.0020157


Author Evans D.M.
Marchini J.
Morris A.P.
Cardon L.R.
Title Two-stage two-locus models in genome-wide association
Journal name PLoS Genetics   Check publisher's open access policy
ISSN 1553-7390
Publication date 2006
Sub-type Article (original research)
DOI 10.1371/journal.pgen.0020157
Open Access Status DOI
Volume 2
Issue 9
Start page 1424
End page 1432
Total pages 591
Language eng
Subject 1105 Dentistry
1306 Cancer Research
1311 Genetics
1312 Molecular Biology
2716 Genetics (clinical)
Abstract Studies in model organisms suggest that epistasis may play an important role in the etiology of complex diseases and traits in humans. With the era of large-scale genome-wide association studies fast approaching, it is important to quantify whether it will be possible to detect interacting loci using realistic sample sizes in humans and to what extent undetected epistasis will adversely affect power to detect association when single-locus approaches are employed. We therefore investigated the power to detect association for an extensive range of two-locus quantitative trait models that incorporated varying degrees of epistasis. We compared the power to detect association using a single-locus model that ignored interaction effects, a full two-locus model that allowed for interactions, and, most important, two two-stage strategies whereby a subset of loci initially identified using single-locus tests were analyzed using the full two-locus model. Despite the penalty introduced by multiple testing, fitting the full two-locus model performed better than single-locus tests for many of the situations considered, particularly when compared with attempts to detect both individual loci. Using a two-stage strategy reduced the computational burden associated with performing an exhaustive two-locus search across the genome but was not as powerful as the exhaustive search when loci interacted. Two-stage approaches also increased the risk of missing interacting loci that contributed little effect at the margins. Based on our extensive simulations, our results suggest that an exhaustive search involving all pairwise combinations of markers across the genome might provide a useful complement to single-locus scans in identifying interacting loci that contribute to moderate proportions of the phenotypic variance.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
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