Sources of variation in Affymetrix microarray experiments

Stanislav O. Zakharkin, Kyoungmi Kim, Tapan Mehta, Lang Chen, Stephen Barnes, Katherine E. Scheirer, Rudolph S. Parrish, David B. Allison, Grier P. Page

Research output: Contribution to journalArticlepeer-review

89 Scopus citations


Background. A typical microarray experiment has many sources of variation which can be attributed to biological and technical causes. Identifying sources of variation and assessing their magnitude, among other factors, are important for optimal experimental design. The objectives of this study were: (1) to estimate relative magnitudes of different sources of variation and (2) to evaluate agreement between biological and technical replicates. Results. We performed a microarray experiment using a total of 24 Affymetrix GeneChip® arrays. The study included 4th mammary gland samples from eight 21-day-old Sprague Dawley CD female rats exposed to genistein (soy isoflavone). RNA samples from each rat were split to assess variation arising at labeling and hybridization steps. A general linear model was used to estimate variance components. Pearson correlations were computed to evaluate agreement between technical and biological replicates. Conclusion. The greatest source of variation was biological variation, followed by residual error, and finally variation due to labeling when *.cel files were processed with dChip and RMA image processing algorithms. When MAS 5.0 or GCRMA-EB were used, the greatest source of variation was residual error, followed by biology and labeling. Correlations between technical replicates were consistently higher than between biological replicate.

Original languageEnglish (US)
Article number214
JournalBMC Bioinformatics
StatePublished - Aug 29 2005
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)
  • Structural Biology
  • Applied Mathematics


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