Bayesian Regression Analysis of Quantitative Trait with Correlated Phenotypic Data

• Activity Number: 657
• Type: Contributed
• Date/Time: Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Lan Zhu*+ and Hung-Chih Ku
• Companies: Oklahoma State University and Oklahoma State University
• Keywords: Bayesian regression model ; QTL mapping ; Heritability ; False discovery rate

Abstract

Identifying Quantitative trait loci (QTL) is critical for understanding the genetic architecture of complex diseases. Thus, many statistical methods have been developed to estimate the effects of genes and locate these genes that are responsible for quantitative traits. The penalized maximum likelihood method, initially proposed by Zhang and Xu (2005), is one of the powerful statistical tool for QTL mapping to deal with the problem that the number of markers is larger than the number of individuals. However, the method is limited to single trait with unrelated individuals. The purpose of this research is to extend the penalized maximum likelihood method on multiple traits with related individuals by conducting simulation studies. Simulation results show that the method is able to localize and estimate QTL effects with consistently high power, especially for complex traits with high heritabilities.