A Mutual Information-based method to select informative pairs of variables in case-control genetic association studies to improve the power of detecting interaction between genetic variants

Résumé : We propose a novel procedure for tagging Single Nucleotide Polymorphisms (SNPs), called EpiTag, to deal with interaction detection in Genome-Wide Association Studies. The aim of our method is to select a set of tag-SNPs that optimally represents the whole set of pairs of SNPs whereas usual approaches are univariate. The linkage between two pairs of SNPs is measured by the Normalized Mutual Information. The proposed algorithm is assessed considering the power of interaction detection compared to a no-tagging strategy and a usual one-dimensional tagging procedure, both on simulated and real genotype structures. EpiTag demonstrates good power performances along with various signal strengths or data sizes w.r.t the competing methods.
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Article dans une revue
Journal de la Société Française de Statistique, Société Française de Statistique et Société Mathématique de France, 2018, 152 (2), pp.84-110
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https://hal.archives-ouvertes.fr/hal-01880547
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Soumis le : mardi 25 septembre 2018 - 08:51:46
Dernière modification le : jeudi 15 novembre 2018 - 11:58:50

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  • HAL Id : hal-01880547, version 1

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Mathieu Emily, Chloé Friguet. A Mutual Information-based method to select informative pairs of variables in case-control genetic association studies to improve the power of detecting interaction between genetic variants. Journal de la Société Française de Statistique, Société Française de Statistique et Société Mathématique de France, 2018, 152 (2), pp.84-110. 〈hal-01880547〉

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