Reproducibility of gene expression across generations of Affymetrix microarrays

Ashish Nimgaonkar, Despina Sanoudou, Atul J. Butte, Judith N. Haslett, Louis M. Kunkel, Alan H. Beggs, Isaac S. Kohane

Research output: Contribution to journalArticle

Abstract

Background: The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips® (HuGeneFL and HG-U95A) was measured. Results: Correlation coefficients were computed for gene expression values across chip generations based on different measures of similarity. Comparing the absolute calls assigned to the individual probe sets across the generations found them to be largely unchanged. Conclusion: We show that experimental replicates are highly reproducible, but that reproducibility across generations depends on the degree of similarity of the probe sets and the expression level of the corresponding transcript.

Original languageEnglish (US)
Article number27
JournalBMC Bioinformatics
Volume4
DOIs
StatePublished - Jun 25 2003
Externally publishedYes

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Reproducibility of gene expression across generations of Affymetrix microarrays'. Together they form a unique fingerprint.

  • Cite this

    Nimgaonkar, A., Sanoudou, D., Butte, A. J., Haslett, J. N., Kunkel, L. M., Beggs, A. H., & Kohane, I. S. (2003). Reproducibility of gene expression across generations of Affymetrix microarrays. BMC Bioinformatics, 4, [27]. https://doi.org/10.1186/1471-2105-4-27