Sources of variation in Affymetrix microarray experiments

Stanislav O. Zakharkin(University of Alabama at Birmingham), Kyoungmi Kim(University of Alabama at Birmingham), Tapan Mehta(University of Alabama at Birmingham), Lang Chen(University of Alabama at Birmingham), Stephen Barnes(University of Alabama at Birmingham), Katherine E Scheirer(University of Alabama at Birmingham), Rudolph S. Parrish(University of Louisville), David B. Allison(University of Alabama at Birmingham), Grier P. Page(University of Alabama at Birmingham)
BMC Bioinformatics
August 29, 2005
Cited by 120Open Access
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Abstract

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 replicates.


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