JSM 2005 - Toronto

Abstract #304619

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 277
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #304619
Title: Interval Estimation of a Finite Mixture Model: Modeling a Distribution of P-values
Author(s): Qinfang Xiang*+ and Gary Gadbury and Jode Edwards
Companies: University of Missouri, Rolla and University of Missouri, Rolla and Iowa State University
Address: Rolla Building 202, Rolla, MO, 65409, United States
Keywords: microarray ; MCMC ; Bootstrap ; pvalue ; gene expression
Abstract:

DNA microarray is a new technology that measures the expression levels of thousands of genes simultaneously. It often is used to identify genes that express differentially between two types of tissues or between two experimental conditions. Recently, investigators analyzing data from microarray experiments found the distribution of P-values from tests for differential genetic expression can contain useful information regarding several quantities of interest. A mixture of a beta distribution and a uniform distribution has been used to model the distribution of P-values. The resulting fitted model can be used to compute derived quantities such as a true positive (TP) probability. This presentation focuses on the precision of estimates from such a mixture model by evaluating the confidence interval for estimates. Three computational methods are applied to investigate the performance of confidence intervals for model parameters. The role of the number of tests (i.e., number of P-values) in the precision of estimates also is considered. The advantages and their limitations for three methods are discussed.

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Revised March 2005