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Independence and reproducibility across microarray platforms

Nature Methods volume 2, pages 337344 (2005) | Download Citation



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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  1. 1.

    , , , & Analysis of matched mRNA measurements from two different microarray technologies. Bioinformatics 18, 405–412 (2002).

  2. 2.

    et al. Performance evaluation of commercial short-oligonucleotide microarrays and the impact of noise in making cross-platform correlations. BMC Genomics 5, 61 (2004).

  3. 3.

    , , & Comprehensive comparison of six microarray technologies. Nucleic Acids Res. 32, e124 (2004).

  4. 4.

    et al. Current issues for DNA microarrays: platform comparison, double linear amplification, and universal RNA reference. J. Biotechnol. 112, 225–245 (2004).

  5. 5.

    et al. A comparison of oligonucleotide and cDNA-based microarray systems. Physiol. Genomics 16, 361–370 (2004).

  6. 6.

    , , & Comparing the use of Affymetrix to spotted oligonucleotide microarrays using two retinal pigment epithelium cell lines. Mol. Vis. 9, 482–496 (2003).

  7. 7.

    et al. Multicomponent analysis of the pancreatic adenocarcinoma progression model using a pancreatic intraepithelial neoplasia tissue microarray. Mod. Pathol. 16, 902–912 (2003).

  8. 8.

    , , & Overview of an interlaboratory collaboration on evaluating the effects of model hepatotoxicants on hepatic gene expression. Environ. Health Perspect. 112, 423–427 (2004).

  9. 9.

    et al. Are data from different gene expression microarray platforms comparable? Genomics 83, 1164–1168 (2004).

  10. 10.

    et al. Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 31, 5676–5684 (2003).

  11. 11.

    et al. Cardiac transcriptional response to acute and chronic angiotensin II treatments. Physiol. Genomics 18, 152–166 (2004).

  12. 12.

    & Antisense RNA Amplification: A Linear Amplification Method for Analyzing the mRNA Population from Single Living Cells. Methods 10, 283–288 (1996).

  13. 13.

    , , & A robust method for the amplification of RNA in the sense orientation. BMC Genomics 6, 27 (2005).

  14. 14.

    et al. A concise guide to cDNA microarray analysis. Biotechniques 29, 548–550, 552–544, 556 (2000).

  15. 15.

    et al. TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34, 374–378 (2003).

  16. 16.

    Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979).

  17. 17.

    & Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection. Proc. Natl. Acad. Sci. USA 98, 31–36 (2001).

  18. 18.

    et al. Resourcerer: a database for annotating and linking microarray resources within and across species. Genome Biology 2, software0002.0001–0002.0004 (2001).

  19. 19.

    et al. Current issues for DNA microarrays: platform comparison, double linear amplification, and universal RNA reference. J. Biotechnol. 112, 225–245 (2004).

  20. 20.

    et al. Multiple lab comparison of microarray platforms. Nat. Methods 2, 345–349 (2004).

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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.

Author information


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

    • Jennie E Larkin
    • , Bryan C Frank
    • , Razvan Sultana
    •  & John Quackenbush
  2. Boston University Medical Center, 715 Albany Street, Boston, Massachusetts 02118, USA.

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

    • Razvan Sultana
    •  & John Quackenbush
  4. Department of Biochemistry, The George Washington University, Washington, DC 20037, USA.

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

    • John Quackenbush


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Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to John Quackenbush.

Supplementary information

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  1. 1.

    Supplementary Table 1

    Forward and reverse primers used for qRT-PCR.

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    Supplementary Methods

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