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Unfortunately, detecting gene\u2010gene interactions is extremely challenging due to the large number of potential interactions and ambiguity regarding marker coding and interaction scale. For many data sets, there is insufficient statistical power to evaluate all candidate gene\u2010gene interactions. In these cases, a global test for gene\u2010gene interactions may be the best option. Global tests have much greater power relative to multiple individual interaction tests and can be used on subsets of the markers as an initial filter prior to testing for specific interactions. In this paper, we describe a novel global test for gene\u2010gene interactions, the global epistasis test (GET), that is based on results from random matrix theory. As we show via simulation studies based on previously proposed models for common diseases including rheumatoid arthritis, type 2 diabetes, and breast cancer, our proposed GET method has superior performance characteristics relative to existing global gene\u2010gene interaction tests. A glaucoma GWAS data set is used to demonstrate the practical utility of the GET method.<\/jats:p>","DOI":"10.1002\/gepi.21990","type":"journal-article","created":{"date-parts":[[2016,7,8]],"date-time":"2016-07-08T04:24:13Z","timestamp":1467951853000},"page":"689-701","source":"Crossref","is-referenced-by-count":5,"title":["A global test for gene\u2010gene interactions based on random matrix theory"],"prefix":"10.1002","volume":"40","author":[{"given":"H. 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