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Abstract:
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In family-based association studies, there are two orthogonal components of information often referred to as the 'between-' and 'within-' family information. Various strategies have been developed to make optimal use of family-based information in genetic studies. We propose a method for large-scale genetic association mapping using the between-family information to weight the robust, within-family association statistics. The method falls under the general framework of weighted hypothesis testing. Through simulations, we evaluate the overall power of the approach, particularly in the stratified samples. Finally, through application to the Framingham Heart Study, we demonstrate the utility of the approach to uncover genetic variants underlying substance abuse vulnerability.
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