Nonparametric Independence Tests in High-Dimensional Settings, with Applications to the Genetics of Complex Disease
- Castro Prado, Fernando
- Wenceslao González Manteiga Doktorvater
- Javier Costas Costas Doktorvater/Doktormutter
Universität der Verteidigung: Universidade de Santiago de Compostela
Jahr der Verteidigung: 2024
Art: Dissertation
Zusammenfassung
Nowadays, genetics studies large amounts of very diverse variables. Mathematical statistics has evolved in parallel to its applications, with much recent interest high-dimensional settings. In the genetics of human common disease, a number of relevant problems can be formulated as tests of independence. We show how defining adequate premetric structures on the support spaces of the genetic data allows for novel approaches to such testing. This yields a solid theoretical framework, which reflects the underlying biology, and allows for computationally-efficient implementations. For each problem, we provide mathematical results, simulations and the application to real data.