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Tzu-Ming Chu,¹ Shibing Deng,¹ Russ Wolfinger,¹ Richard S. Paules,² and Hisham K. Hamadeh³

¹SAS Institute Inc., Cary, North Carolina, USA; ²National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA; ³Amgen Inc., Thousand Oaks, California, USA

Abstract
Consistency and coherence of gene expression data across multiple sites depends on several factors such as platform (oligo, cDNA, etc.) , environmental conditions at each laboratory, and data quality. The Hepatotoxicity Working Group of the International Life Sciences Institute Health and Environmental Sciences Institute consortium on the application of genomics to mechanism-based risk assessment is investigating these factors by comparing high-density gene expression data sets generated on two sets of RNA from methapyrilene (MP) experiments conducted at Abbott Laboratories and Boehringer-Ingelheim Pharmaceuticals, Inc. using a single platform (Affymetrix Rat Genome U34A GeneChip) at seven different sites. This article focuses on the evaluation of data quality and statistical models that facilitate the comparison of such data sets at the probe level. We present methods for exploring and quantitatively assessing differences in the data, with the principal goal being the generation of lists of site-insensitive genes responsive to low and high doses of MP. A combination of numerical and graphical techniques reveals important patterns and partitions of variability in the data, including the magnitude of the site effects. Although the site effects are significantly large in the analysis results, they appear to be primarily additive and therefore can be adjusted in the statistical calculations in a way that does not bias conclusions regarding treatment differences. Key words: cross-site comparison, gene expression, hepatotoxicity, ILSI, toxicogenomics. Environ Health Perspect 112:449-455 (2004) . doi:10.1289/txg.6787 available via http://dx.doi.org/ [Online 15 January 2004]

This article is part of the mini-monograph "Application of Genomics to Mechanism-Based Risk Assessment."

Address correspondence to H.K. Hamadeh, Amgen Inc., One Amgen Center Dr., Mail Drop 5-1-A, Thousand Oaks, CA 91320 USA. Telephone: (805) 447-4818. Fax: (805) 499-2936. E-mail: hhamadeh@amgen.com

We thank our colleague H. Chen, at SAS Institute, Inc., for creating some of the figures in this article. We also thank the Hepatotoxicity Working Group of the ILSI Health and Environmental Sciences Institute's Committee on the Application of Genomics to Mechanism-Based Risk Assessment testing program, a scientific consortium organized to facilitate further development and advances in genomics and proteomic methodologies to increase the utility of gene expression data for mechanism-based risk assessment.

The authors declare they have no competing financial interests.

Received 6 October 2003 ; accepted 15 December 2003.

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