Bioinformatics Vol. 19 no. 2 2003
Pages 185-193
© 2003 Oxford University Press
A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
1 Group in Biostatistics, University of California, Berkeley, CA 94720, USA
2 Department of Biostatistics, John Hopkins University, Baltimore, MD, USA
3 AstraZeneca R & D Mölndal, Sweden
4 Department of Statistics, University of California, Berkeley, CA 94720, USA
5 Division of Genetics and Bioinformatics, WEHI, Melbourne, Australia
Received on June 13, 2002
; revised on September 11, 2002
; accepted on September 17, 2002
Motivation: When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations.
Results: We present three methods of performing normalization at the probe intensity level. These methods are called complete data methods because they make use of data from all arrays in an experiment to form the normalizing relation. These algorithms are compared to two methods that make use of a baseline array: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure. Two publicly available datasets are used to carry out the comparisons. The simplest and quickest complete data method is found to perform favorably.
Availability: Software implementing all three of the complete data normalization methods is available as part of the R package Affy, which is a part of the Bioconductor project http://www.bioconductor.org.
Contact: bolstad{at}stat.berkeley.edu.
Supplementary information: Additional figures may be found at http://www.stat.berkeley.edu/~bolstad/normalize/index.html
* To whom correspondence should be addressed.
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G. A. Ramirez-Carvajal, A. M. Morse, C. Dervinis, and J. M. Davis The Cytokinin Type-B Response Regulator PtRR13 Is a Negative Regulator of Adventitious Root Development in Populus Plant Physiology, June 1, 2009; 150(2): 759 - 771. [Abstract] [Full Text] [PDF]
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S. A. Gharib, W. C. Liles, L. S. Klaff, and W. A. Altemeier Noninjurious mechanical ventilation activates a proinflammatory transcriptional program in the lung Physiol Genomics, May 13, 2009; 37(3): 239 - 248. [Abstract] [Full Text] [PDF]
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J.-Y. Sul, C.-w. K. Wu, F. Zeng, J. Jochems, M. T. Lee, T. K. Kim, T. Peritz, P. Buckley, D. J. Cappelleri, M. Maronski, et al. Transcriptome transfer produces a predictable cellular phenotype PNAS, May 5, 2009; 106(18): 7624 - 7629. [Abstract] [Full Text] [PDF]
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V. Jayaswal, M. Lutherborrow, D. D. F. Ma, and Y. Hwa Yang Identification of microRNAs with regulatory potential using a matched microRNA-mRNA time-course data Nucleic Acids Res., May 1, 2009; 37(8): e60 - e60. [Abstract] [Full Text] [PDF]
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S. Bruno, C. Grange, M. C. Deregibus, R. A. Calogero, S. Saviozzi, F. Collino, L. Morando, A. Busca, M. Falda, B. Bussolati, et al. Mesenchymal Stem Cell-Derived Microvesicles Protect Against Acute Tubular Injury J. Am. Soc. Nephrol., May 1, 2009; 20(5): 1053 - 1067. [Abstract] [Full Text] [PDF]
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M. Klinger, J. K. Kim, S. A. Chmura, A. Barczak, D. J. Erle, and N. Killeen Thymic OX40 Expression Discriminates Cells Undergoing Strong Responses to Selection Ligands J. Immunol., April 15, 2009; 182(8): 4581 - 4589. [Abstract] [Full Text] [PDF]
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D. Getnet, C. H. Maris, E. L. Hipkiss, J. F. Grosso, T. J. Harris, H.-R. Yen, T. C. Bruno, S. Wada, A. Adler, R. W. Georgantas, et al. Tumor Recognition and Self-Recognition Induce Distinct Transcriptional Profiles in Antigen-Specific CD4 T Cells J. Immunol., April 15, 2009; 182(8): 4675 - 4685. [Abstract] [Full Text] [PDF]
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M. Marotta, C. Ruiz-Roig, Y. Sarria, J. L. Peiro, F. Nunez, J. Ceron, F. Munell, and M. Roig-Quilis Muscle genome-wide expression profiling during disease evolution in mdx mice Physiol Genomics, April 10, 2009; 37(2): 119 - 132. [Abstract] [Full Text] [PDF]
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Y. Halperin, C. Linhart, I. Ulitsky, and R. Shamir Allegro: Analyzing expression and sequence in concert to discover regulatory programs Nucleic Acids Res., April 1, 2009; 37(5): 1566 - 1579. [Abstract] [Full Text] [PDF]
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H. Bengtsson, A. Ray, P. Spellman, and T. P. Speed A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods Bioinformatics, April 1, 2009; 25(7): 861 - 867. [Abstract] [Full Text] [PDF]
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J. A. Christianson, I. W. Wilson, D. J. Llewellyn, and E. S. Dennis The Low-Oxygen-Induced NAC Domain Transcription Factor ANAC102 Affects Viability of Arabidopsis Seeds following Low-Oxygen Treatment Plant Physiology, April 1, 2009; 149(4): 1724 - 1738. [Abstract] [Full Text] [PDF]
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L. Ho, R. Jothi, J. L. Ronan, K. Cui, K. Zhao, and G. R. Crabtree An embryonic stem cell chromatin remodeling complex, esBAF, is an essential component of the core pluripotency transcriptional network PNAS, March 31, 2009; 106(13): 5187 - 5191. [Abstract] [Full Text] [PDF]
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