JSM 2005 - Toronto

Abstract #302373

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 87
Type: Invited
Date/Time: Monday, August 8, 2005 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #302373
Title: Large p, Small n Asymptotics for Significance Analysis in High-throughput Screening
Author(s): Michael Kosorok and Shuangge Ma*+
Companies: University of Wisconsin, Madison and University of Washington
Address: Bldg 29 Suite 310, Seattle, WA, 98115, United States
Keywords: Asymptotics ; Microarrays ; False discovery rate
Abstract:

In this talk, we develop large p small n asymptotics suitable for significance analysis in microarray gene expression studies and other high throughput screening settings. We consider one-sample and two-sample comparisons where the number n of replications (arrays) per group is extremely small relative to the number p of items (genes). Provided the log of p squared divided by n goes to zero, we show under general dependency structures that p-values based on a variety of marginal test statistics are uniformly valid in a manner that allows accurate control of the false discovery rate. We demonstrate the results with simulation studies and several real microarray studies.

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