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Nat Rev Genet. 2014 Nov;15(11):722-33. doi: 10.1038/nrg3747. Epub 2014 Sep 9.

Detecting epistasis in human complex traits.

Author information

1
1] Arthritis Research UK Centre for Genetics and Genomics, Institute of Inflammation and Repair, University of Manchester, Manchester M13 9PT, UK. [2] Medical Research Council (MRC) Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK. [3].
2
1] MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK. [2] Queensland Brain Institute Centre, University of Queensland, Brisbane, Queensland 4072, Australia. [3] University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland 4072, Australia. [4].
3
1] Medical Research Council (MRC) Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK. [2] The Roslin Institute and Royal (Dick) School of Veterinary Sciences, University of Edinburgh, Midlothian EH25 9RG, UK.

Abstract

Genome-wide association studies (GWASs) have become the focus of the statistical analysis of complex traits in humans, successfully shedding light on several aspects of genetic architecture and biological aetiology. Single-nucleotide polymorphisms (SNPs) are usually modelled as having additive, cumulative and independent effects on the phenotype. Although evidently a useful approach, it is often argued that this is not a realistic biological model and that epistasis (that is, the statistical interaction between SNPs) should be included. The purpose of this Review is to summarize recent directions in methodology for detecting epistasis and to discuss evidence of the role of epistasis in human complex trait variation. We also discuss the relevance of epistasis in the context of GWASs and potential hazards in the interpretation of statistical interaction terms.

PMID:
25200660
DOI:
10.1038/nrg3747
[Indexed for MEDLINE]

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