JSM 2005 - Toronto

Abstract #304280

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 477
Type: Topic Contributed
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #304280
Title: Bayesian Finite Mixture Models and Metaanalysis for Multitissue Polygenic Phenomena in Complex Biological Systems
Author(s): Yulan Liang*+ and Xueya Cai and Arpad Kelemen
Companies: University at Buffalo and University at Buffalo and Niagara University
Address: 249 Farber Hall, Buffalo, NY, 14214-3000, United States
Keywords: Bayesian ; Finite Mixture Model ; Meta Analysis ; Multiple Tissues ; Affymetrix data
Abstract:

This paper addresses key problems in the analysis of large gene expression datasets that describe systemic temporal response cascades to therapeutic doses in multiple tissues. Critical statistical issues include identification of the significant gene expression in the temporal fashions, identification of the common profiles among multiple tissues derived from affymetrix experiments, and clustering of genes with common mechanisms of regulation in response to different dosing regimens. First, three stage-filtering procedures are developed: correlation study of tissue datasets through the Spearman Correlation Coefficients; Bayesian models with Dirichlet prior for the estimations of the proportion of the "call" information of Present, Absent, and Marginal; and hierarchical Bayesian finite mixture model and DIC criteria for the identification of significant gene expressions and clusters. Furthermore, metaanalysis is performed to identify common related genes from multiple tissues that may serve as ideal targets for novel treatment strategies.

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Revised March 2005