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A novel test for detecting gene-gene interactions in trio studies

Brunilda Balliu, Noah Zaitlen
doi: https://doi.org/10.1101/021469
Brunilda Balliu
*Department of Pathology, Stanford University School of Medicine, 94305 Stanford, CA, USA
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Noah Zaitlen
†Department of Medicine, University California San Francisco, 94158 San Francisco, CA, USA
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Abstract

Epistasis plays a significant role in the genetic architecture of many complex phenotypes in model organisms. To date, there have been very few interactions replicated in human studies due in part to the multiple hypothesis burden implicit in genome-wide tests of epistasis. Therefore, it is of paramount importance to develop the most powerful tests possible for detecting interactions. In this work we develop a new gene-gene interaction test for use in trio studies called the trio correlation (TC) test. The TC test computes the expected joint distribution of marker pairs in offspring conditional on parental genotypes. This distribution is then incorporated into a standard one degree of freedom correlation test of interaction. We show via extensive simulations that our test substantially outperforms existing tests of interaction in trio studies. The gain in power under standard models of phenotype is large, with previous tests requiring more than twice the number of trios to obtain the power of our test. We also demonstrate a bias in a previous trio interaction test and identify its origin. We conclude that the TC test shows improved power to identify interactions in existing, as well as emerging, trio association studies. The method is publicly available at www.github.com/BrunildaBalliu/TrioEpi.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted June 25, 2015.
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A novel test for detecting gene-gene interactions in trio studies
Brunilda Balliu, Noah Zaitlen
bioRxiv 021469; doi: https://doi.org/10.1101/021469
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A novel test for detecting gene-gene interactions in trio studies
Brunilda Balliu, Noah Zaitlen
bioRxiv 021469; doi: https://doi.org/10.1101/021469

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