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Article
Nature Methods  2, 337 - 344 (2005)
Published online: 21 April 2005; | doi:10.1038/nmeth757

Independence and reproducibility across microarray platforms

Jennie E Larkin1, Bryan C Frank1, Haralambos Gavras2, Razvan Sultana1, 3 & John Quackenbush1, 3, 4, 5

1  The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, Maryland 20850, USA.

2  Boston University Medical Center, 715 Albany Street, Boston, Massachusetts 02118, USA.

3  Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, Massachusetts 02115, USA.

4  Department of Biochemistry, The George Washington University, Washington, DC 20037, USA.

5  Department of Statistics, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, Maryland 21205, USA.

Correspondence should be addressed to John Quackenbush johnq@jimmy.harvard.edu
Microarrays have been widely used for the analysis of gene expression, but the issue of reproducibility across platforms has yet to be fully resolved. To address this apparent problem, we compared gene expression between two microarray platforms: the short oligonucleotide Affymetrix Mouse Genome 430 2.0 GeneChip and a spotted cDNA array using a mouse model of angiontensin II−induced hypertension. RNA extracted from treated mice was analyzed using Affymetrix and cDNA platforms and then by quantitative RT-PCR (qRT-PCR) for validation of specific genes. For the 11,710 genes present on both arrays, we assessed the relative impact of experimental treatment and platform on measured expression and found that biological treatment had a far greater impact on measured expression than did platform for more than 90% of genes, a result validated by qRT-PCR. In the small number of cases in which platforms yielded discrepant results, qRT-PCR generally did not confirm either set of data, suggesting that sequence-specific effects may make expression predictions difficult to make using any technique.

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Nature Methods
ISSN: 1548-7091
EISSN: 1548-7105
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