A Robust Coefficient of Determination for Heritability Estimation in Genetic Association Studies

• Activity Number: 392
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Vanda Lourenco*+ and Paulo Canas Rodrigues and Ana Maria Pires
• Companies: NOVA University of Lisbon and University of Lisbon and Universidade Técnica de Lisboa
• Keywords: Robust regression ; Linear mixed model ; Coefficient of determination ; Single nucleotide polymorphism ; Heritability ; Genetic association studies

Abstract

Motivation.

Heritability is key in plant studies to help achieve better yield and other agronomic traits of interest. In candidate gene studies regression models are used to test for associations between phenotype and candidate SNPs. SNP imputation guarantees that marker information is complete and the data are balanced. So both the coefficient of determination, R2, and broad-sense heritability are equivalent. However, when the normality assumption is violated, the classical R2 may be seriously affected. Recently two R2 alternatives with good properties were proposed for the linear mixed model. However they were not studied under data contamination scenarios.

Results.

We evaluate the performance of the newly proposed coefficients of determination for the linear mixed model under contamination and step forward a robust version of these coefficients assessing their adequacy for heritability estimation via simulation. An example of application with a real data set from the literature is also presented.