Distribution of the Number of False Discoveries in Large-Scale Family-Based Association Testing with Applications to SAPPHIRe Data

• Activity Number: 452
• Type: Topic Contributed
• Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Biometrics Section
• Author(s): I-Shou Chang*+
• Companies: National Health Research Institutes, Taiwan
• Keywords: false-discovery rate ; family-based association studies ; large-scale simultaneous testing ; haplotype-based association tests

Abstract

We present a model-free approach to false discovery rate (FDR) for a large-scale simultaneous family based association tests (FBATs). When association between a set of markers in a candidate gene and a group of phenotypes is studied by FBATs, we indicate that a joint null hypothesis distribution for these FBATs can be obtained by the fundamental statistical method of conditioning on sufficient statistics for the null hypothesis. This joint null distribution is used to compute the distribution of the number of tail counts, which defines the FDR. This approach to false discovery rate takes advantage of the correlation between the FBATs. The usefulness of this approach is illustrated by providing false discovery rates to several genetic studies based on data from Stanford Asia and Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe).