Bayesian two-stage approach to genome-wide association studies in genetic related populations

M. E. Castellanos Nueda, C. Armero, S. Cabras, A. Quirós Carretero

Genome-wide association studies (GWAS) aim to assess relationships between SNPs and diseases.
They are one of the problems most analyzed in genetics, and they have some peculiarities given the large number of SNPs compared to the small number of subjects in the study.
Individuals are not independent, especially in animal breeding studies or genetic diseases in isolated populations with highly inbred individuals.
We propose a GWAS model in a two-stage approach comprising a dimension reduction and a subsequent model selection.
The first stage, in which the genetic relatedness between subjects is taken into account, selects the promising SNPs.
The second stage uses Bayes factors for comparing among all candidate models and a random search strategy for exploring the space of all the regression models, in a fully Bayesian approach.
We illustrate its performance in a real dataset about Beta-Thalassemia in an isolated population from Sardinia.

Palabras clave: Bayes factors, Kinship, Model selection, SNP

L08.2 Grupo de Inferencia Bayesiana: Applications of Bayesian Modelling in Econometrics and Genetics
5 de septiembre de 2016  15:40
0.09 - Aula de proyectos 2

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