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Activity Number: 420
Type: Contributed
Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract #316952 View Presentation
Title: Association Analysis of Survival Traits at Gene Level by Functional Regression Models
Author(s): Ruzong Fan* and Yifan Wang and Qi Yan and Ying Ding and Daniel E. Weeks and Haobo Ren and Richard Cook and momiao Xiong and Wei Chen
Companies: Eunice Kennedy Shriver National Institute of Child Health and Human Development and FDA and and University of Pittsburgh and University of Pittsburgh and Regeneron Pharmaceuticals and University of Waterloo and The University of Texas at Houston and University of Pittsburgh Children's Hospital of Pittsburgh
Keywords: rare variants ; common variants ; complex diseases ; association study ; functional data analysis ; Cox models

We developed functional regression based Cox proportional hazard models to perform a gene-based association analysis of survival traits adjusting for covariates. The proposed Cox models are fixed effect models and genetic effects of multiple genetic variants are assumed to be fixed. By fitting the proposed Cox models, we introduced likelihood ratio test (LRT) statistics to test for association between the survival traits and multiple genetic variants in a genetic region. Extensive simulations are performed to evaluate empirical type I error rates and power performance of the proposed Cox models and LRT statistics. We show that the proposed LRT statistics control the type I error very well. To evaluate the power performance, we compared the proposed LRT with the previously developed Cox SKAT LRT, which are based on mixed effect models to assume the contributions of major gene locus to be random. The LRT statistics of the proposed Cox models have higher power than or similar power as Cox SKAT LRT in most cases. The models and related test statistics can be useful in the whole genome and whole exome association studies. The methods were applied to analyze genetic data of eye study.

Authors who are presenting talks have a * after their name.

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