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Activity Number: 537
Type: Contributed
Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #310224
Title: Response-Dependent Sampling Designs and Analysis in Studies with Rare Variants
Author(s): Andriy Derkach*+ and Lei Sun and Jerald F Lawless
Companies: University of Toronto and University of Toronto and University of Waterloo
Keywords: rare varinat ; response-selective sampling ; robust designs ; stratification ; genetic association studies
Abstract:

Rare variants play an important role in studies of complex human diseases and traits, and next generation sequencing technology provides rich data for analysis. This recent focus on rare variants has produced a significant number of sequencing studies as well as a large number of association tests. However, theoretical and empirical results have shown that in order to achieve high power large sample sizes are needed. Compared to random sampling, it has been shown that response-selective sampling designs can greatly improve the power of association studies with common variants and recently, rare variants. We extend the range of tests for multiple rare variants and show how adjustments to existing tests can increase power. We also investigate sampling strategies where random samples are taken from the tails of the response distribution and there may also be stratification on covariates. Through theoretical calculations and extensive simulations, we investigate what designs and testing approaches are efficient and robust across various genetic models.


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