Discovery and validation of sub-threshold genome-wide association study loci using epigenomic signatures

Genetic variants identified by genome-wide association studies explain only a modest proportion of heritability, suggesting that meaningful associations lie 'hidden' below current thresholds. Here, we integrate information from association studies with epigenomic maps to demonstrate that e...

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Bibliographic Details
Main Authors: Wang, Xinchen (Contributor), Rizki, Gizem (Contributor), Mills, Robert (Author), de Wit, Elzo (Author), Subramanian, Vidya (Contributor), Nguyen, Xinh-Xinh (Author), Ye, Jiangchuan (Author), Leyton-Mange, Jordan (Author), van der Harst, Pim (Author), de Laat, Wouter (Author), Newton-Cheh, Christopher (Author), Kellis, Manolis (Contributor), Tucker, Nathan R. (Author), Krijger, Peter H. L. (Author), Bartell, Eric R. (Contributor), Dolmatova, Elena V. (Author), Ellinor, Patrick T. (Author), Milan, David J. (Author), Boyer, Laurie Ann (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Boyer, Laurie (Contributor)
Format: Article
Language:English
Published: eLife Sciences Publications, Ltd., 2016-05-11T16:42:08Z.
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