Multiple-laboratory comparison of microarray platforms |
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Authors: | Irizarry Rafael A Warren Daniel Spencer Forrest Kim Irene F Biswal Shyam Frank Bryan C Gabrielson Edward Garcia Joe G N Geoghegan Joel Germino Gregory Griffin Constance Hilmer Sara C Hoffman Eric Jedlicka Anne E Kawasaki Ernest Martínez-Murillo Francisco Morsberger Laura Lee Hannah Petersen David Quackenbush John Scott Alan Wilson Michael Yang Yanqin Ye Shui Qing Yu Wayne |
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Affiliation: | Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA. rafa@jhu.edu |
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Abstract: | Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC-Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well. |
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