WITHDRAWN: A Weighted Mulivariate Phenotype-Genotype Association Analysis in Genome-Wide Association Studies

• Activity Number: 514
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Saonli Basu and Debashree Ray
• Companies: University of Minnesota and University of Minnesota
• Keywords: Multivariate trait association ; Genome-wide association study ; MANOVA

Abstract

In the study of a complex disease, several correlated traits are often measured as risk factors for the disease. Joint modeling of multiple disease-related correlated traits may improve power to detect association between a genetic variant and the disease. Moreover this joint analysis can reveal some pleiotropic genes involved in the biological development of the disease. We show that standard MANOVA is very powerful when a genetic variant is associated with a subset of the traits or the effect of causal variant is in different directions with these correlated traits, but loses significant power when the variant is associated with all the traits and the effect direction is same as the direction of dependence between the traits. We propose a powerful weighted approach that maximizes power by adaptively using the data to optimally combine MANOVA and a test that potentially ignore the correlation between the traits. Our framework covers both studies of unrelated individuals and family studies. We illustrate our proposed test through simulation studies and compare the performance of different approaches under various alternative models.