Title: "Statistical Methods For Analyzing Gene-Environment Interaction"
Speaker: Bhramar Mukherjee; Department of Biostatistics, University of Michigan
Place: HORT 117; November 15, 2011, Tuesday, 4:30pm


In the post-GWAS era, development of novel statistical methods for characterizing the interplay of genes and environment has become increasingly important. In this talk I will present various approaches to characterize gene-gene and gene-environment interactions in large-scale association studies. In particular, we will discuss modern shrinkage and hybrid approaches that leverage the assumption of gene-environment independence in a data-adaptive way. The methods will be illustrated by analysis of gene-environment interaction in a population-based case-control study of colorectal cancer.

Associated reading:

1. B. Mukherjee and N. Chatterjee. 2008. Exploiting Gene-Environment Independence for Analysis of Case-Control Studies: An Empirical Bayes-Type Shrinkage Estimator to Trade-Off between Bias and Effciency. Biometrics 64, 685-694.

2. B. Mukherjee, J. Ahn, S.B. Gruber and N. Chatterjee. Testing Gene-Environment Interaction in Large Scale Case-Control Association Studies: Possible Choices and Comparisons. American Journal of Epidemiology (to appear).

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