Novel methods for epistasis detection in genome-wide association studies

被引:9
作者
Slim, Lotfi [1 ,2 ]
Chatelain, Clement [2 ]
Azencott, Chloe-Agathe [1 ,3 ]
Vert, Jean-Philippe [1 ,4 ]
机构
[1] Mines ParisTech, CBIO Ctr Computat Biol, Paris, France
[2] SANOFI R&D, Translat Sci, Chilly Mazarin, France
[3] PSL Res Univ, Inst Curie, INSERM, U900, Paris, France
[4] Google Brain, Paris, France
来源
PLOS ONE | 2020年 / 15卷 / 11期
基金
英国惠康基金;
关键词
GENE-GENE INTERACTIONS; PROPENSITY SCORE; MODELS; REGULARIZATION; INFERENCE; SELECTION; DESIGN; TOOL;
D O I
10.1371/journal.pone.0242927
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
More and more genome-wide association studies are being designed to uncover the full genetic basis of common diseases. Nonetheless, the resulting loci are often insufficient to fully recover the observed heritability. Epistasis, or gene-gene interaction, is one of many hypotheses put forward to explain this missing heritability. In the present work, we propose epiGWAS, a new approach for epistasis detection that identifies interactions between a target SNP and the rest of the genome. This contrasts with the classical strategy of epistasis detection through exhaustive pairwise SNP testing. We draw inspiration from causal inference in randomized clinical trials, which allows us to take into account linkage disequilibrium. EpiGWAS encompasses several methods, which we compare to state-of-the-art techniques for epistasis detection on simulated and real data. The promising results demonstrate empirically the benefits of EpiGWAS to identify pairwise interactions.
引用
收藏
页数:18
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