Contributions of the EMERALD Project to Assessing and Improving Microarray Data Quality

While minimum information about a microarray experiment (MIAME) standards have helped to increase the value of the microarray data deposited into public databases like ArrayExpress and Gene Expression Omnibus (GEO), limited means have been available to assess the quality of this data or to identify the procedures used to normalize and transform raw data. The EMERALD FP6 Coordination Action was designed to deliver approaches to assess and enhance the overall quality of microarray data and to disseminate these approaches to the microarray community through an extensive series of workshops, tutorials, and symposia. Tools were developed for assessing data quality and used to demonstrate how the removal of poor-quality data could improve the power of statistical analyses and facilitate analysis of multiple joint microarray data sets. These quality metrics tools have been disseminated through publications and through the software package arrayQualityMetrics. Within the framework provided by the Ontology of Biomedical Investigations, ontology was developed to describe data transformations, and software ontology was developed for gene expression analysis software. In addition, the consortium has advocated for the development and use of external reference standards in microarray hybridizations and created the Molecular Methods (MolMeth) database, which provides a central source for methods and protocols focusing on microarray-based technologies.JRC.DG.D.2-Reference material

Inter- and intra-laboratory study to determine the reproducibility of toxicogenomics datasets

The application of toxicogenomics as a predictive tool for chemical risk assessment has been under evaluation by the toxicology community for more than a decade. However, toxicogenomics predominately remains a tool for investigative research rather than for regulatory risk assessment. In this study, we aimed to determine whether the current generation of microarray technology in combination with an in vitro experimental design was capable of generating robust, reproducible data of sufficient quality to show promise as a tool for regulatory risk assessment. To this end, we designed a prospective collaborative study to determine the level of inter- and intra-laboratory reproducibility between three independent laboratories. All Test Centres adopted the same protocols for all aspects of the toxicogenomic experiment including cell culture, chemical exposure, RNA extraction, microarray data generation and analysis. As a case study, the genotoxic carcinogen Benzo[a]pyrene (B[a]P) and the human hepatoma cell line HepG2 were used to generate three comparable toxicogenomic data sets. High levels of technical reproducibility were demonstrated using a widely employed gene expression microarray platform. While differences at the global transcriptome level were observed between the Test Centres, a common subset of B[a]P responsive genes (n=400 gene probes) was identified at all Test Centres which included many genes previously reported in the literature as B[a]P responsive. These data show promise that the current generation of microarray technology in combination with a standard in vitro experimental design can produce robust data that can be reproducibly generated in independent laboratories. Future work will need to determine whether in vitro model(s) can not only be reproducible but also predictive for a range of toxic chemicals with different mechanisms of action. Such an approach may potentially be part of future in vitro testing regimes for regulatory risk assessment.JRC.I.3-Molecular Biology and Genomic