JSM 2005 Online Program

Abstract #303679

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	514
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Biometrics Section
Abstract - #303679
Title:	The Effects of Normalization on the Correlation Structure of Microarray Data
Author(s):	Xing Qiu*+ and Andrew I. Brooks and Lev Klebanov and Andrei Yakovlev
Companies:	University of Rochester and University of Rochester and Charls University and University of Rochester
Address:	Department of Biostatistics and Computational Biology, Rochester, NY, 14642, United States
Keywords:	microarray ; normalization ; bayesian ; correlation
Abstract:	Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test statistics across genes. It is assumed frequently that dependence between genes (or tests) is sufficiently weak to justify the proposed methods of testing for differentially expressed genes. A potential impact of between-gene correlations on the performance of such methods has yet to be explored. We present a systematic study of correlation between the t-statistics associated with different genes. We report the effects of four normalization methods using a large set of microarray data on childhood leukemia in addition to several sets of simulated data. Our findings help decipher the correlation structure of microarray data before and after the application of normalization procedures. A long-range correlation in microarray data manifests itself in thousands of genes heavily correlated with a given gene in terms of the associated t-statistics.

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