Independence and reproducibility across microarray platforms (original) (raw)

Nature Methods volume 2, pages 337–344 (2005)Cite this article

Abstract

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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Acknowledgements

The authors wish to thank F. Pollock of Affymetrix, Inc. for providing the mouse GeneChips used in this study. Thanks also to N. Bhagabati and J. Braisted for valuable discussions. This work was supported by grants U01 HL66580-01 (J.Q.), R33 HL73712 (J.Q.), and U01 HL66617-01 (H.G.) from the National Institutes of Health.

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Authors and Affiliations

  1. The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, 20850, Maryland, USA
    Jennie E Larkin, Bryan C Frank, Razvan Sultana & John Quackenbush
  2. Boston University Medical Center, 715 Albany Street, Boston, 02118, Massachusetts, USA
    Haralambos Gavras
  3. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 44 Binney Street, Boston, 02115, Massachusetts, USA
    Razvan Sultana & John Quackenbush
  4. Department of Biochemistry, The George Washington University, Washington, 20037, DC, USA
    John Quackenbush
  5. Department of Statistics, Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, 21205, Maryland, USA
    John Quackenbush

Authors

  1. Jennie E Larkin
  2. Bryan C Frank
  3. Haralambos Gavras
  4. Razvan Sultana
  5. John Quackenbush

Corresponding author

Correspondence toJohn Quackenbush.

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The authors declare no competing financial interests.

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Larkin, J., Frank, B., Gavras, H. et al. Independence and reproducibility across microarray platforms.Nat Methods 2, 337–344 (2005). https://doi.org/10.1038/nmeth757

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