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Abstract Details

Activity Number: 164
Type: Topic Contributed
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305098
Title: Estimation of Effect Size Distribution for Large-Scale Association Studies with Sparse Signals
Author(s): Dmitri Zaykin*+ and Chia-Ling Kuo
Companies: and National Institute of Environmental Health Sciences
Address: NIEHS, Raleigh, NC, ,
Keywords: large-scale association studies ; GWAS ; false discovery rate ; multiple testing ; linkage disequilibrium

In large scale genetic association studies, true positives typically represent only a very small portion of all tests. This fact has been hampering the adoption of statistical approaches that allow estimation the proportion of false positives among discoveries. We develop novel efficient methods for characterizing the effect size distribution among true positives in large scale genetic association studies. These methods allow straightforward estimation of the proportion of false positives among top association signals and calculation of ranking probabilities: i.e. chances that a true positive will rank among a specified number of top hits.

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