Activity Number:
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52
- New Challenges in Complex Data Analysis
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Type:
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Invited
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Date/Time:
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Sunday, July 30, 2017 : 4:00 PM to 5:50 PM
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Sponsor:
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Korean International Statistical Society
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Abstract #322279
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Title:
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Marginal Screening of 2 X 2 Tables in Large-Scale Case-Control Studies
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Author(s):
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Ian McKeague*
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Companies:
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Columbia University
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Keywords:
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Genome-wide association studies ;
Marginal screening ;
Multiple testing
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Abstract:
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Assessing statistical significance when screening large numbers of 2 x 2 tables that cross-classify disease status with different types of exposure poses a challenging multiple testing problem. The problem becomes especially acute in large-scale genetic studies. We develop a potentially more powerful and computationally efficient approach (compared with existing Bonferroni and permutation-based methods) that takes into account the presence of complex dependencies between the 2 x 2 tables. Our approach uses direct Monte Carlo simulation from the limiting null distribution of a maximally selected log-odds ratio. We apply the method to case-control data from a study of a large collection of genetic variants related to the risk of early onset stroke. The talk is based on joint work with Min Qian.
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Authors who are presenting talks have a * after their name.