American Statistical Association
Modern genome-wide association studies have led to the discoveries of thousands of susceptibility loci across a variety of quantitative and qualitative traits. Although the loci discovered so far have limited ability for prediction of any individual trait, recent estimates of “hidden heritability” indicate that power for predictive models can be potentially increased by building polygenic models on larger data sets. In this report, we provide a theoretical framework for characterizing predictive performance of a polygenic model based on the sample size of a training dataset, the threshold for variable selection, the number of underlying predictive variables and the distribution of their effect-sizes. Using this framework and empirical estimates of effect-size distribution, we provide estimates of prediction accuracy for future polygenic models as a function sample sizes for eight different complex traits. We estimated, for example, to achieve 90% of the prediction power associated with hidden heritability; future studies may need sample size in the order of 500K-700K for adult height and 50K-70K for Prostate cancer.
Dr. Chatterjee is the Chief and a Senior Investigator of the Biostatistics Branch of the Division of Cancer Epidemiology and Genetics (DECG), National Cancer Institute (NCI). He received his Bachelor’s and Master’s degree (with a specialization in Mathematical Statistics and Probability Theory) from the Indian Statistical Institute, Calcutta. He received his Ph.D. in Statistics from the University of Washington, Seattle in 1999. His research focuses on statistical methods for modern genetic and molecular epidemiologic studies. He also actively collaborates in design and analysis of a variety of major cancer epidemiologic studies at NCI. He is an elected Fellow of the American Statistical Association (2008) and is recipient of the Mortimer Spiegelman Award (2010).
|Date:||Thursday, January 26, 2012|
|Time:||4:00 - 5:00 P.M.|
Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
New York, New York