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An Ancestry Based Approach for Detecting Interactions

Danny S. Park, Itamar Eskin, Eun Yong Kang, Eric R. Gamazon, Celeste Eng, Christopher R. Gignoux, Joshua M. Galanter, Esteban Burchard, Chun J. Ye, Hugues Aschard, Eleazar Eskin, Eran Halperin, Noah Zaitlen
doi: https://doi.org/10.1101/036640
Danny S. Park
1Department of Bioengineering and Therapeutic Sciences. University of California San Francisco. San Francisco, CA.
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  • For correspondence: danny.park@ucsf.edu noah.zaitlen@ucsf.edu
Itamar Eskin
2The Blavatnik School of Computer Science. Tel-Aviv University. Tel Aviv, Israel.
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Eun Yong Kang
3Department of Computer Science. University of California Los Angeles. Los Angeles, CA.
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Eric R. Gamazon
4Division of Genetic Medicine, Department of Medicine. Vanderbilt University. Nashville, TN.
5Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
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Celeste Eng
6Department of Medicine. University of California San Francisco. San Francisco, CA.
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Christopher R. Gignoux
1Department of Bioengineering and Therapeutic Sciences. University of California San Francisco. San Francisco, CA.
7Department of Genetics. Stanford University. Palo Alto, CA.
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Joshua M. Galanter
6Department of Medicine. University of California San Francisco. San Francisco, CA.
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Esteban Burchard
1Department of Bioengineering and Therapeutic Sciences. University of California San Francisco. San Francisco, CA.
6Department of Medicine. University of California San Francisco. San Francisco, CA.
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Chun J. Ye
8Institute of Human Genetics. University of California San Francisco. San Francisco, CA.
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Hugues Aschard
9Department of Epidemiology. Harvard School of Public Health. Boston, MA.
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Eleazar Eskin
3Department of Computer Science. University of California Los Angeles. Los Angeles, CA.
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Eran Halperin
2The Blavatnik School of Computer Science. Tel-Aviv University. Tel Aviv, Israel.
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Noah Zaitlen
1Department of Bioengineering and Therapeutic Sciences. University of California San Francisco. San Francisco, CA.
6Department of Medicine. University of California San Francisco. San Francisco, CA.
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  • For correspondence: danny.park@ucsf.edu noah.zaitlen@ucsf.edu
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I Abstract

Background: Epistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies.

Results: In this work, we develop a new statistical approach to address these issues that leverages genetic ancestry in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals respectively, identifying nine interactions that were significant at p < 5×10−8, we show that two of the interactions in methylation data replicate, and the remaining six are significantly enriched for low p-values (p < 1.8×10−6).

Conclusion: We show that genetic ancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 01, 2016.
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An Ancestry Based Approach for Detecting Interactions
Danny S. Park, Itamar Eskin, Eun Yong Kang, Eric R. Gamazon, Celeste Eng, Christopher R. Gignoux, Joshua M. Galanter, Esteban Burchard, Chun J. Ye, Hugues Aschard, Eleazar Eskin, Eran Halperin, Noah Zaitlen
bioRxiv 036640; doi: https://doi.org/10.1101/036640
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An Ancestry Based Approach for Detecting Interactions
Danny S. Park, Itamar Eskin, Eun Yong Kang, Eric R. Gamazon, Celeste Eng, Christopher R. Gignoux, Joshua M. Galanter, Esteban Burchard, Chun J. Ye, Hugues Aschard, Eleazar Eskin, Eran Halperin, Noah Zaitlen
bioRxiv 036640; doi: https://doi.org/10.1101/036640

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