Risk Predictions from Genomewide Association Data

• Activity Number: 100
• Type: Invited
• Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Hongyu Zhao*+ and Jia Kang and Ruiyan Luo and Judy Cho
• Companies: Yale University and Yale University and Yale University and Yale University
• Keywords: risk prediction ; genome wide association study ; single nucleotide polymorphism ; model selection ; high dimensional data ; statistical genomics

Abstract

Recent genome wide association studies have identified many genetic variants affecting complex human diseases. It is of great interest to build disease risk prediction models based on these data. In this presentation, we will discuss statistical challenges in using genome wide association data for risk predictions, and propose alternative methods to select markers and then combine information from these markers for risk prediction. We will demonstrate the performance of different methods through both simulation studies and applications to real-world data.