Abstract #301208

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JSM 2002 Abstract #301208
Activity Number: 318
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section*
Abstract - #301208
Title: Multiple Testing and Genetic Marker Data: An Ordered Approach
Author(s): Lauren McIntyre*+ and Katy Simonsen and Yu Qin
Affiliation(s): Purdue University and Purdue University and Purdue University
Address: 1150 Lilly Hall of Life Science, West Lafayette, Indiana, 47907, USA
Keywords: alpha spending ; multiple testing ; order statistic
Abstract:

The plethora of genomic data makes dealing with the issue of multiple testing of paramount importance. The Bonferroni correction is a well-known mechanism for controlling type I error. Alternatively, the maximum order statistic (the statistic with the minimum p-value) has been suggested and demonstrated to work well in several different contexts. In this case, no adjustment for multiple testing is required, as only a single test is conducted. This paper extends the application of the maximum statistic by examining the complete set of order statistics. In this case, type I error adjustments are necessary. We propose a novel application of the alpha-spending approach to address the type I error. We examine the impact of using the set of order statistics, coupled with different allocations of type I error, on the power to detect loci associated with a quantitative trait in experimental and natural populations.

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