JSM 2005 Online Program

Abstract #303691

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	359
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor:	General Methodology
Abstract - #303691
Title:	Instability of Multiple Testing Procedures in Microarray Data Analysis
Author(s):	Yuanhui Xiao*+ and Andrei Yakovlev
Companies:	University of Rochester and University of Rochester
Address:	601 Elmwood Avenue, Box 630 , Rochester, NY, 14642, United States
Keywords:
Abstract:	In the context of microarray data analysis, the term "stability" means "replication stability" for the selection of differentially expressed genes. Using crossvalidation techniques, we have found that some genes are selected much less frequently (across cross-validation samples) than other genes with the same adjusted p-values. The extent to which this type of instability manifests itself depends on a specific multiple testing procedure and the choice of a test statistic. We conducted a study to assess instability of multiple testing procedures with simulated and biological data. In this presentation, we report our findings in conjunction with the Bonferroni adjustment versus the Westfall and Young Algorithm and the Kolmogorov-Smirnov statistic versus the t-statistic. Crossvalidation represents a tool for reducing the set of initially selected genes to those with a sufficiently high frequency of occurrence in this set.

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