A. Quirós, C. Armero, S. Cabras, M. E. Castellanos
Genome-wide association studies assess relationships between single nucleotide polymorphisms (SNP) and diseases. They are popular problems in genetics in which the number of SNP is large compared to the number of subjects in the study. Individuals might not be independent, especially in animal breeding studies or genetic diseases in isolated populations. We propose a family-based model in a two-stage approach comprising a dimension reduction and a subsequent model selection. The first stage, in which the genetic relatedness between the subjects is taken into account, selects the promising SNP. 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, and compare with existing methods like Bayesian lasso or GEMMA, in a simulated study and in a real study about Beta-thalassemia disorder in an isolated population from Sardinia.
Palabras clave / Keywords: Bayes factor, kinship, model selection
Programado
Sesión GT08-2 Inferencia Bayesiana-2: Genomics and Spatial statistics under a Bayesian perspective (BAYES-2). Organizador: Stefano Cabras
29 de mayo de 2018 17:00
Sala 1
