Comparison of Affymetriz data normalization methods using 6,926 ezperiments across five array generations
Background: Gene expression microarray technologies are widely used across most areas of biological and medical research. Comparing and integrating microarray data from different experiments would be very useful, but is currently very challenging due to the experimental and hybridization conditions, as well as data preprocessing and normalization methods. Furthermore, even in the case of the widely-used, industry-standard Affymetrix oligonucleotide microarrays, the various array generations have different probe sets representing different genes, hindering the data integration.Results: In this study our objective is to find systematic approaches to normalize the data emerging from different Affymetrix array generations and from different laboratories. We compare and assess the accuracy of five normalization methods for Affymetrix gene expression data using 6,926 Affymetrix experiments from five array generations. The methods that we compare include 1) standardization, 2) housekeeping gene based normalization, 3) equalized quantile normalization, 4) Weibull distribution based normalization and 5) array generation based gene centering. Our results indicate that the best results are achieved when the data is normalized first within a sample and then between-samples with Array Generation based gene Centering (AGC) normalization.Conclusions: We conclude that with the AGC method integrating different Affymetrix datasets results in values that are significantly more comparable across the array generations than in the cases where no array generation based normalization is used.
Reija Autio Sami Kilpinen Matti Saarela Olli Kallioniemi Sampsa Hautaniemi Jaakko Astola
Department of Signal Processing, Tampere University of Technology, Tampere, Finland Medical Biotechnology, VTT Technical Research Centre and University of Turku, Turku, Finland Institu Medical Biotechnology, VTT Technical Research Centre and University of Turku, Turku, Finland Institu Computational Systems Biology Laboratory, Institute of Biomedicine and Genome-Scale Biology Research
国际会议
The 7th Asia-Pacific Bioinformatics Conference(第七届亚太生物信息学大会)
北京
英文
257-268
2009-01-01（万方平台首次上网日期，不代表论文的发表时间）