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Nucleic Acids Research 2005 33(18):5914-5923; doi:10.1093/nar/gki890
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Published online 19 October 2005

© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oxfordjournals.org

Article

Experimental comparison and cross-validation of the Affymetrix and Illumina gene expression analysis platforms

Michael Barnes, Johannes Freudenberg1, Susan Thompson, Bruce Aronow1 and Paul Pavlidis2,*

Cincinnati Children's Hospital Medical Center, Division of Rheumatology Cincinnati OH, USA 1Cincinnati Children's Hospital Medical Center, Division of Biomedical Informatics Cincinnati OH, USA 2Columbia University Department of Biomedical Informatics New York, NY, USA

*To whom correspondence should be addressed. Tel: +1 212 851 5141; Fax: +1 212 851 5290; Email: pavlidis{at}dbmi.columbia.edu

Received May 31, 2005. Revised August 11, 2005. Accepted September 25, 2005.

The growth in popularity of RNA expression microarrays has been accompanied by concerns about the reliability of the data especially when comparing between different platforms. Here, we present an evaluation of the reproducibility of microarray results using two platforms, Affymetrix GeneChips and Illumina BeadArrays. The study design is based on a dilution series of two human tissues (blood and placenta), tested in duplicate on each platform. The results of a comparison between the platforms indicate very high agreement, particularly for genes which are predicted to be differentially expressed between the two tissues. Agreement was strongly correlated with the level of expression of a gene. Concordance was also improved when probes on the two platforms could be identified as being likely to target the same set of transcripts of a given gene. These results shed light on the causes or failures of agreement across microarray platforms. The set of probes we found to be most highly reproducible can be used by others to help increase confidence in analyses of other data sets using these platforms.


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