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Novel Methods for Epistasis Detection in Genome-Wide Association Studies

Abstract : As the size of genome-wide association studies (GWAS) increases, detecting interactions among single nucleotide polymorphisms (SNP) or genes associated to particular phenotypes is garnering more and more interest as a means to decipher the full genetic basis of complex diseases. Systematically testing interactions is however challenging both from a computational and from a statistical point of view, given the large number of possible interactions to consider. In this paper we propose a framework to identify pairwise interactions with a particular target variant, using a penalized regression approach. Narrowing the scope of interaction identification around a predetermined target provides increased statistical power and better interpretability, as well as computational scalability. We compare our new methods to state-of-the-art techniques for epistasis detection on simulated and real data, and demonstrate the benefits of our framework to identify pairwise interactions in several experimental settings.
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Contributor : Chloé-Agathe Azencott Connect in order to contact the contributor
Submitted on : Monday, January 18, 2021 - 6:13:57 PM
Last modification on : Monday, January 10, 2022 - 10:16:05 AM


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Lotfi Slim, Clement Chatelain, Jean-Philippe Vert, Chloé-Agathe Azencott. Novel Methods for Epistasis Detection in Genome-Wide Association Studies. PLoS ONE, Public Library of Science, 2020, 15 (11), pp.e0242927. ⟨10.1371/journal.pone.0242927⟩. ⟨hal-01984919v2⟩



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