Abstract #300915

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JSM 2003 Abstract #300915
Activity Number: 316
Type: Invited
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: General Methodology
Abstract - #300915
Title: Bayesian Analysis of Variance for Microarrays
Author(s): J. Sunil Rao*+ and Hemant Ishwaran
Companies: Case Western Reserve University and The Cleveland Clinic Foundation
Address: Desk WG-57, Cleveland, OH, 44106-1712,
Keywords: DNA microarrays ; variable selection ; false detection rates ; ANOVA
Abstract:

We introduce a new method for detecting differentially expressed genes in DNA microarray experiments which strikes a balance between false detections and false nondetections. A hierarchical ANOVA model is constructed using parametric stochastic variable selection (P-SVS) ideas of earlier work. The basis of the new approach involves performing model selection on weighted averages of generalized ridge regression estimates. Improved performance can be attributed to shrinkage as well as model averaging properties of our estimators. A simple shrinkage plot allows one to visualize the trade-off between low false discovery rates and finding more genes. The methodology is illustrated on a colon cancer microarray database collected at Case Western Reserve University. The working hypothesis is that moderately differentially expressed genes that would otherwise be missed, may well be involved in colon cancer metastasis to the liver.

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