The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2006-09

AUTHORS

MAQC Consortium, Leming Shi, Laura H Reid, Wendell D Jones, Richard Shippy, Janet A Warrington, Shawn C Baker, Patrick J Collins, Francoise de Longueville, Ernest S Kawasaki, Kathleen Y Lee, Yuling Luo, Yongming Andrew Sun, James C Willey, Robert A Setterquist, Gavin M Fischer, Weida Tong, Yvonne P Dragan, David J Dix, Felix W Frueh, Federico M Goodsaid, Damir Herman, Roderick V Jensen, Charles D Johnson, Edward K Lobenhofer, Raj K Puri, Uwe Scherf, Jean Thierry-Mieg, Charles Wang, Mike Wilson, Paul K Wolber, Lu Zhang, Shashi Amur, Wenjun Bao, Catalin C Barbacioru, Anne Bergstrom Lucas, Vincent Bertholet, Cecilie Boysen, Bud Bromley, Donna Brown, Alan Brunner, Roger Canales, Xiaoxi Megan Cao, Thomas A Cebula, James J Chen, Jing Cheng, Tzu-Ming Chu, Eugene Chudin, John Corson, J Christopher Corton, Lisa J Croner, Christopher Davies, Timothy S Davison, Glenda Delenstarr, Xutao Deng, David Dorris, Aron C Eklund, Xiao-hui Fan, Hong Fang, Stephanie Fulmer-Smentek, James C Fuscoe, Kathryn Gallagher, Weigong Ge, Lei Guo, Xu Guo, Janet Hager, Paul K Haje, Jing Han, Tao Han, Heather C Harbottle, Stephen C Harris, Eli Hatchwell, Craig A Hauser, Susan Hester, Huixiao Hong, Patrick Hurban, Scott A Jackson, Hanlee Ji, Charles R Knight, Winston P Kuo, J Eugene LeClerc, Shawn Levy, Quan-Zhen Li, Chunmei Liu, Ying Liu, Michael J Lombardi, Yunqing Ma, Scott R Magnuson, Botoul Maqsodi, Tim McDaniel, Nan Mei, Ola Myklebost, Baitang Ning, Natalia Novoradovskaya, Michael S Orr, Terry W Osborn, Adam Papallo, Tucker A Patterson, Roger G Perkins, Elizabeth H Peters, Ron Peterson, Kenneth L Philips, P Scott Pine, Lajos Pusztai, Feng Qian, Hongzu Ren, Mitch Rosen, Barry A Rosenzweig, Raymond R Samaha, Mark Schena, Gary P Schroth, Svetlana Shchegrova, Dave D Smith, Frank Staedtler, Zhenqiang Su, Hongmei Sun, Zoltan Szallasi, Zivana Tezak, Danielle Thierry-Mieg, Karol L Thompson, Irina Tikhonova, Yaron Turpaz, Beena Vallanat, Christophe Van, Stephen J Walker, Sue Jane Wang, Yonghong Wang, Russ Wolfinger, Alex Wong, Jie Wu, Chunlin Xiao, Qian Xie, Jun Xu, Wen Yang, Liang Zhang, Sheng Zhong, Yaping Zong, William Slikker

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. More... »

PAGES

1151-1161

References to SciGraph publications

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  • Journal

    TITLE

    Nature Biotechnology

    ISSUE

    9

    VOLUME

    24

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nbt1239

    DOI

    http://dx.doi.org/10.1038/nbt1239

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1037875102

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/16964229


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