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Nucleic Acids Research 2005 33(20):e175; doi:10.1093/nar/gni179
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Published online 10 November 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


Methods Online

Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data

Manhong Dai, Pinglang Wang, Andrew D. Boyd1, Georgi Kostov1, Brian Athey1, Edward G. Jones2, William E. Bunney3, Richard M. Myers4, Terry P. Speed5, Huda Akil, Stanley J. Watson and Fan Meng*

Molecular and Behavioural Neuroscience Institute and Department of Psychiatry, University of Michigan Ann Arbor, MI 48109, USA 1Michigan Center for Biological Information, University of Michigan Ann Arbor, MI 48105, USA 2Department of Psychiatry and Center for Neuroscience, University of California Davis, CA 95616, USA 3Department of Psychiatry and Human Behavior, University of California Irvine, CA 92697, USA 4Department of Genetics, Stanford University School of Medicine Stanford, CA 94305, USA 5Department of Statistics, University of California Berkeley, CA 94720, USA

*To whom correspondence should be addressed. Tel: +1 734 615 7099; Fax: +1 734 647 4130; Email: mengf{at}umich.edu

Received September 26, 2005. Revised October 17, 2005. Accepted October 25, 2005.

Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals ~30–50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.


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