Abstract #302347

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JSM 2003 Abstract #302347
Activity Number: 219
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 9:00 AM to 10:50 AM
Sponsor: Biopharmaceutical Section
Abstract - #302347
Title: Local Pooled Error Methods for Differential Expression Analysis of Microarray Data.
Author(s): Stephen Kaluzny*+ and Michael O'Connell and Tim Hesterberg and Jae Kyun Lee
Companies: Statistical Sciences, Inc. and Insightful Corporation and Insighful Corporation and University of Virginia
Address: 1700 Westlake Ave. N, Seattle, WA, 98109-3012,
Keywords:
Abstract:

The local pooled error (LPE) method for differential expression analysis was recently described by Lee and O'Connell (2003) and Jain et al. (2003). The local pooled error is derived by estimating a baseline variance function for each experimental condition, say F and G. For example, when duplicated arrays (F1, F2) are used for condition F, the variance of M (=F1-F2 and F2-F1) on each percentile range of A=(F1+F2)/2 is evaluated (log scale). When there are more than duplicates, all pairwise comparisons of (M, A) are pooled together for such estimation. These local pooled variances are then combined to form a smoothed variance function with respect to the average expression intensity for each experimental condition. The test statistic for differential expression is formed using a difference in medians as the numerator and a corresponding variance estimate from the local pooled error variance function as the denominator. This poster presents results regarding the power and size of the local pooled error test from simulations based on microarray experiments run at the University of Virginia. The simulation experiments are summarized as power curves, tables of test sizes and boost


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