1. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements
- Author
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Alan Brunner, Glenda C. Delenstarr, Timothy K. McDaniel, Lisa J. Croner, Chunlin Xiao, Raymond R. Samaha, Wen Yang, Lei Guo, Stephen J. Walker, Terry Osborn, Federico Goodsaid, P. Scott Pine, J. Christopher Corton, Yuling Luo, Yaron Turpaz, Alexander Wong, Raj K. Puri, Jean Thierry-Mieg, Michael A Wilson, Anne Bergstrom Lucas, Heather Harbottle, Eli Hatchwell, Donna Brown, Jie Wu, Shawn Levy, Wendell D. Jones, Ola Myklebost, Craig A. Hauser, Vincent Bertholet, J. Eugene LeClerc, David J. Dix, Scott A. Jackson, Eugene Chudin, Beena Vallanat, Susan D. Hester, Mark Schena, Barry A. Rosenzweig, James J. Chen, Paul K. Wolber, Adam Papallo, Yongming Andrew Sun, Shawn C. Baker, Uwe Scherf, Zoltan Szallasi, William Slikker, Kenneth L. Philips, Xutao Deng, Lajos Pusztai, Sue Jane Wang, Janet Hager, Xu Guo, Tao Han, Charles Wang, Frank Staedtler, Hongmei Sun, Svetlana Shchegrova, Christopher Davies, Liang Zhang, James C. Willey, Yaping Zong, Kathleen Y. Lee, Paul K. Haje, James C. Fuscoe, Ying Liu, Natalia Novoradovskaya, Russell D. Wolfinger, Kathryn Gallagher, Roderick V. Jensen, Feng Qian, Wenjun Bao, Christophe Van, Bud Bromley, Janet A. Warrington, Leming Shi, Tucker A. Patterson, David Dorris, Huixiao Hong, Winston Patrick Kuo, Hongzu Ren, Xiaoxi Megan Cao, Cecilie Boysen, Michael S. Orr, Danielle Thierry-Mieg, Xiaohui Fan, Felix W. Frueh, Gary P. Schroth, Yonghong Wang, Chunmei Liu, Yunqing Ma, Shashi Amur, Lu Zhang, Michael Lombardi, Dave D. Smith, Tzu Ming Chu, Jun Xu, Charles D. Johnson, Baitang Ning, Timothy Davison, Botoul Maqsodi, Karol L. Thompson, Thomas A. Cebula, Richard Shippy, Edward K. Lobenhofer, Weida Tong, Quan Zhen Li, Catalin Barbacioru, Qian Xie, Aron Charles Eklund, Ernest S. Kawasaki, Patrick J. Collins, Zivana Tezak, Elizabeth Herness Peters, Francoise de Longueville, Stephanie Fulmer-Smentek, Hong Fang, Patrick Hurban, Scott R. Magnuson, Hanlee P. Ji, Roger Perkins, Mitch Rosen, Ron L. Peterson, Weigong Ge, Stephen C. Harris, Sheng Zhong, Charles R. Knight, Damir Herman, Zhenqiang Su, Roger D. Canales, Nan Mei, Jing Cheng, Irina Tikhonova, Gavin M. Fischer, Laura H. Reid, Robert Setterquist, Yvonne P. Dragan, Jing Han, and John F. Corson
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Quality Control ,Quality Assurance, Health Care ,Microarray ,media_common.quotation_subject ,Biomedical Engineering ,Bioengineering ,Computational biology ,Biology ,Bioinformatics ,Sensitivity and Specificity ,Applied Microbiology and Biotechnology ,Article ,Resource (project management) ,Gene expression ,Quality (business) ,Oligonucleotide Array Sequence Analysis ,media_common ,Gene Expression Profiling ,Reproducibility of Results ,Equipment Design ,United States ,Equipment Failure Analysis ,Gene expression profiling ,Expression data ,Gene chip analysis ,Molecular Medicine ,DNA microarray ,Biotechnology - Abstract
Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.
- Published
- 2006
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