A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies |
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Authors: | Kuo Winston Patrick Liu Fang Trimarchi Jeff Punzo Claudio Lombardi Michael Sarang Jasjit Whipple Mark E Maysuria Malini Serikawa Kyle Lee Sun Young McCrann Donald Kang Jason Shearstone Jeffrey R Burke Jocelyn Park Daniel J Wang Xiaowei Rector Trent L Ricciardi-Castagnoli Paola Perrin Steven Choi Sangdun Bumgarner Roger Kim Ju Han Short Glenn F Freeman Mason W Seed Brian Jensen Roderick Church George M Hovig Eivind Cepko Connie L Park Peter Ohno-Machado Lucila Jenssen Tor-Kristian |
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Affiliation: | Department of Developmental Biology, Harvard School of Dental Medicine, 188 Longwood Ave., Boston, Massachusetts 02115, USA. wkuo@genetics.med.harvard.edu |
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Abstract: | Over the last decade, gene expression microarrays have had a profound impact on biomedical research. The diversity of platforms and analytical methods available to researchers have made the comparison of data from multiple platforms challenging. In this study, we describe a framework for comparisons across platforms and laboratories. We have attempted to include nearly all the available commercial and 'in-house' platforms. Using probe sequences matched at the exon level improved consistency of measurements across the different microarray platforms compared to annotation-based matches. Generally, consistency was good for highly expressed genes, and variable for genes with lower expression values as confirmed by quantitative real-time (QRT)-PCR. Concordance of measurements was higher between laboratories on the same platform than across platforms. We demonstrate that, after stringent preprocessing, commercial arrays were more consistent than in-house arrays, and by most measures, one-dye platforms were more consistent than two-dye platforms. |
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