ToxSci Advance Access published online on April 6, 2006
Toxicological Sciences, doi:10.1093/toxsci/kfj184
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1 Dept. of Environmental and Occupational Health Sciences, University of Washington
* To whom correspondence should be addressed. Although microarray technology has emerged as a powerful tool to explore expression levels of thousands of genes or even complete genomes after exposure to toxicants, the functional interpretation of microarray datasets still represents a time-consuming and challenging task. Gene ontology (GO) and pathway mapping have both been shown to be powerful approaches to generate a global view of biological processes and cellular components impacted by toxicants. However, current methods only allow for comparisons across two experimental settings at one particular time point. In addition, the resulting annotations are presented in extensive gene lists with minimal or limited quantitative information, data that is crucial in the application of toxicogenomic data for risk assessment. To facilitate quantitative interpretation of dose or time dependent genomic data, we propose to use combined average raw gene expression values (e.g. intensity or ratio) of genes associated with specific functional categories derived from the GO database. We developed an extended program (GO-Quant) to extract quantitative gene expression values and to calculate the average intensity or ratio for those significantly altered by functional gene category based on MAPPFinder results. To demonstrate its application, we applied this approach to a previously published dose- and time-dependent toxicogenomic data set (Dillman et al. 2005). Our results indicate that the above systems approach can describe quantitatively the degree to which functional gene systems change across dose or time. Additionally, this approach provides a robust measurement to illustrate our results compared to single gene assessments and enables the user to calculate the corresponding ED50 for each specific functional GO term, important for risk assessment.
Received March 30, 2006
Accepted April 1, 2006
Systems Toxicology
A System Based Approach to Interpret Dose and Time-dependent Microarray Data: Quantitative Integration of GO Ontology Analysis for Risk Assessment
Xiaozhong Yu 1,
William C. Griffith 1,
Kristina Hanspers 2,
James F. Dillman III 3,
Hansel Ong 1,
Melinda A. Vredevoogd 4,
and
Elaine M. Faustman 1 *
2 GenMAPP Development Team, Bioinformatics Research Associate/Conklin Lab Gladstone Institute of Cardiovascular Disease/UCSF
3 Cell and Molecular Biology Branch, U.S. Army Medical Research Institute of Chemical Defense
4 Risk Analysis and Risk Communication, Environmental and Occupational Health Sciences, WA, USA
Elaine M. Faustman, E-mail: faustman{at}u.washington.edu
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