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Nature Biotechnology 24, 832–840 (1 July 2006) | doi:10.1038/nbt1217

A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies

Winston Patrick Kuo , Fang Liu , Jeff Trimarchi , Claudio Punzo , Michael Lombardi , Jasjit Sarang , Mark E Whipple , Malini Maysuria , Kyle Serikawa , Sun Young Lee , Donald McCrann , Jason Kang , Jeffrey R Shearstone , Jocelyn Burke , Daniel J Park , Xiaowei Wang , Trent L Rector , Paola Ricciardi-Castagnoli , Steven Perrin , Sangdun Choi , Roger Bumgarner , Ju Han Kim , Glenn F Short , Mason W Freeman , Brian Seed , Roderick Jensen , George M Church , Eivind Hovig , Connie L Cepko , Peter Park , Lucila Ohno-Machado & Tor-Kristian Jenssen

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.