The analysis of G×E interaction is likely to be of increasing importance as researchers attempt to unravel the etiology of complex diseases using high-volume genetic data. A researcher primarily interested in environmental risk factors may be interested in identifying genes that modify the effect of a target environmental risk factor for a disease, while a researcher primarily interested in genetic risk factors may want to know how an environmental factor affects the penetrance of a gene on a disease. Either situation can be viewed as G×E interaction, and for both, the researcher will be charged with conducting the most efficient analysis possible. At a minimum, this will include consideration of sample size and power, potential population stratification, and the best way to measure the environmental exposure. The Group 10 contributions have provided examples of several approaches one might take in testing G×E interactions, for example, jointly testing for a main and interaction effect, testing for population stratification, and the use of longitudinal data with multiple measurements of the environmental exposure to lessen the problem of measurement error. Although several new
