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Multiple-laboratory comparison of microarray platforms
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
Affiliation:Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA. rafa@jhu.edu
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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