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Study Determines MicroArray Data Reproducibility

By HospiMedica staff writers
Posted on 28 Sep 2006
A new study has demonstrated that at a high level, gene expression signatures generated by microarrays are repeatable, further advancing the field towards widespread use in clinical applications. More...


The MicroArray Quality Control (MAQC) study was a collaborative effort led by the U.S. Food and Drug Association (FDA, Rockville, MD, USA). The study included 137 scientists from private and public sector laboratories. Affymetrix (Santa Clara, CA, USA) and other microarray and reagent manufacturers participated in the two-year initiative designed to address the reproducibility of data generated from microarrays. The study's results were reported in the September 8, 2006, issue of Nature Biotechnology.

To generate the data for the study, six microarray manufacturers and the U.S. National Cancer Institute (Bethesda, MD, USA) each selected three sites to run assays. At each site, 20 RNA samples were processed, for a total of 60 samples for each participant. The FDA analyzed the data using each vendor's recommended software, and compared the results.

"The MAQC study has demonstrated that by practicing good scientific method in the laboratory, researchers can obtain accurate, reproducible data from microarrays,” said Janet Warrington, Ph.D., vice president, Emerging Markets and Molecular Diagnostics R&D at Affymetrix, who co-authored three of the eight manuscripts published as part of the study. "Microarrays are an important tool for advancing personalized medicine, drug target discovery, toxicogenomics and related fields, and this study supplies valuable performance information supporting the expansion of genomics in clinical applications.”

In addition to advancing the field as a whole, the data obtained from the study showed that Affymetrix GeneChip arrays demonstrated reproducibility within and across sites, an element critical for the success of clinical studies. Affymetrix GeneChip arrays also showed the ability to detect changes in gene expression, enabling the discovery of novel biomarkers that are the objective of many disease-related studies.



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