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Études d'association génome entier guidées par des réseaux

Abstract : This thesis tackles methodologies to identify the genetic causes of complex diseases. This is usually done via genome-wide association studies (GWAS), when univariate association is studied, and genome-wide association interaction studies, when interactions between genetic factors (or epistasis) are considered (GWAIS). However, both settings present some challenges, namely low statistical power, difficult interpretation, and arbitrary choices at multiple points of the study. In this thesis I study how a framework that uses biological networks can help overcome these issues and boost biomarker discovery. This is done by incorporating prior knowledge into the statistical analysis and putting every single nucleotide polymorphism (SNP) and gene in relation to their biological context. By analyzing two datasets, on breast cancer and inflammatory bowel disease, I demonstrate the utility of networks to discover new mechanisms of susceptibility. These involve individual SNPs, as well as groups of SNPs in epistasis, two-way and higher. I also show how including networks in GWAS and GWAIS boosts the interpretability of the results and produces compelling biological hypotheses.
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Submitted on : Friday, June 25, 2021 - 11:05:56 AM
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  • HAL Id : tel-03270879, version 1


Héctor Climente González. Études d'association génome entier guidées par des réseaux. Bio-informatique [q-bio.QM]. Université Paris sciences et lettres, 2020. Français. ⟨NNT : 2020UPSLM001⟩. ⟨tel-03270879⟩



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