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Selecting Cases and Controls for DNA Sequencing Studies Using Family Histories of Disease
About the work In this work, we propose a new statistical method for selecting cases and controls for sequencing studies based on disease family history. We assume that disease status is determined by unobserved liability score. Our method consists of two steps: first, the conditional means of liability are estimated given the individual’s disease status and those of their relatives with the liability threshold model, and second, the informative subjects are selected with the estimated conditional means. Our simulation studies showed that statistical power is substantially affected by the subject selection strategy chosen, and power is maximized when affected (unaffected) subjects with high (low) risks are selected as cases (controls). The proposed method was successfully applied to genome-wide association studies for type-2 diabetes, and our analysis results reveal the practical value of the proposed methods.
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