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Nucleic Acids Research Advance Access originally published online on December 22, 2008
Nucleic Acids Research 2009 37(2):e17; doi:10.1093/nar/gkn932
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Nucleic Acids Research, 2009, Vol. 37, No. 2 e17
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Methods Online

Quality Assessment and Data Analysis for microRNA Expression Arrays

D. Sarkar1,*, R. Parkin1, S. Wyman1, A. Bendoraite1, C. Sather1, J. Delrow1, A. K. Godwin2, C. Drescher1, W. Huber3, R. Gentleman1 and M. Tewari1

1Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, 2Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA and 3EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

*To whom correspondence should be addressed. Tel: 206 667 5660; Fax: 206 667 1319; Email: dsarkar{at}fhcrc.org

Received July 17, 2008. Revised October 16, 2008. Accepted November 5, 2008.

MicroRNAs are small (~22 nt) RNAs that regulate gene expression and play important roles in both normal and disease physiology. The use of microarrays for global characterization of microRNA expression is becoming increasingly popular and has the potential to be a widely used and valuable research tool. However, microarray profiling of microRNA expression raises a number of data analytic challenges that must be addressed in order to obtain reliable results. We introduce here a universal reference microRNA reagent set as well as a series of nonhuman spiked-in synthetic microRNA controls, and demonstrate their use for quality control and between-array normalization of microRNA expression data. We also introduce diagnostic plots designed to assess and compare various normalization methods. We anticipate that the reagents and analytic approach presented here will be useful for improving the reliability of microRNA microarray experiments.


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D. Risso, M. S. Massa, M. Chiogna, and C. Romualdi
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[Abstract] [Full Text] [PDF]


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