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Discovering genetic interactions bridging pathways in genome-wide association studies

Gang Fang, Wen Wang, Vanja Paunic, Hamed Heydari, Michael Costanzo, Xiaoye Liu, Xiaotong Liu, Benjamin Oately, Michael Steinbach, Brian Van Ness, Eric E. Schadt, Nathan D. Pankratz, Charles Boone, Vipin Kumar, Chad L. Myers
doi: https://doi.org/10.1101/182741
Gang Fang
1.Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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  • For correspondence: gang.fang@mssm.edu kumar@cs.umn.edu cmyers@cs.umn.edu
Wen Wang
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Vanja Paunic
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Hamed Heydari
3.Donnelly Centre, University of Toronto, Toronto, ON, Canada M5S 3E1
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Michael Costanzo
3.Donnelly Centre, University of Toronto, Toronto, ON, Canada M5S 3E1
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Xiaoye Liu
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Xiaotong Liu
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Benjamin Oately
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Michael Steinbach
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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Brian Van Ness
4.Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, MN 55455, USA.
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Eric E. Schadt
1.Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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Nathan D. Pankratz
5.Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA.
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Charles Boone
3.Donnelly Centre, University of Toronto, Toronto, ON, Canada M5S 3E1
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Vipin Kumar
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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  • For correspondence: gang.fang@mssm.edu kumar@cs.umn.edu cmyers@cs.umn.edu
Chad L. Myers
2.Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
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  • For correspondence: gang.fang@mssm.edu kumar@cs.umn.edu cmyers@cs.umn.edu
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Abstract

Genetic interactions have been reported to underlie phenotypes in a variety of systems, but the extent to which they contribute to complex disease in humans remains unclear. In principle, genome-wide association studies (GWAS) provide a platform for detecting genetic interactions, but existing methods for identifying them from GWAS data tend to focus on testing individual locus pairs, which undermines statistical power. Importantly, the global genetic networks mapped for a model eukaryotic organism revealed that genetic interactions often connect genes between compensatory functional modules in a highly coherent manner. Taking advantage of this expected structure, we developed a computational approach called BridGE that identifies pathways connected by genetic interactions from GWAS data. Applying BridGE broadly, we discovered significant interactions in Parkinson’s disease, schizophrenia, hypertension, prostate cancer, breast cancer, and type 2 diabetes. Our novel approach provides a general framework for mapping complex genetic networks underlying human disease from genome-wide genotype data.

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Posted August 30, 2017.
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Discovering genetic interactions bridging pathways in genome-wide association studies
Gang Fang, Wen Wang, Vanja Paunic, Hamed Heydari, Michael Costanzo, Xiaoye Liu, Xiaotong Liu, Benjamin Oately, Michael Steinbach, Brian Van Ness, Eric E. Schadt, Nathan D. Pankratz, Charles Boone, Vipin Kumar, Chad L. Myers
bioRxiv 182741; doi: https://doi.org/10.1101/182741
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Discovering genetic interactions bridging pathways in genome-wide association studies
Gang Fang, Wen Wang, Vanja Paunic, Hamed Heydari, Michael Costanzo, Xiaoye Liu, Xiaotong Liu, Benjamin Oately, Michael Steinbach, Brian Van Ness, Eric E. Schadt, Nathan D. Pankratz, Charles Boone, Vipin Kumar, Chad L. Myers
bioRxiv 182741; doi: https://doi.org/10.1101/182741

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