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2011 | 58 | 4 | 573-580
Article title

Impact of DNA microarray data transformation on gene expression analysis - comparison of two normalization methods

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EN
Abstracts
EN
Two-color DNA microarrays are commonly used for the analysis of global gene expression. They provide information on relative abundance of thousands of mRNAs. However, the generated data need to be normalized to minimize systematic variations so that biologically significant differences can be more easily identified. A large number of normalization procedures have been proposed and many softwares for microarray data analysis are available. Here, we have applied two normalization methods (median and loess) from two packages of microarray data analysis softwares. They were examined using a sample data set. We found that the number of genes identified as differentially expressed varied significantly depending on the method applied. The obtained results, i.e. lists of differentially expressed genes, were consistent only when we used median normalization methods. Loess normalization implemented in the two software packages provided less coherent and for some probes even contradictory results. In general, our results provide an additional piece of evidence that the normalization method can profoundly influence final results of DNA microarray-based analysis. The impact of the normalization method depends greatly on the algorithm employed. Consequently, the normalization procedure must be carefully considered and optimized for each individual data set.
Publisher

Year
Volume
58
Issue
4
Pages
573-580
Physical description
Dates
published
2011
received
2011-05-16
revised
2011-11-25
accepted
2011-12-12
(unknown)
2011-12-20
Contributors
  • Department of Biotechnology and Food Microbiology, Poznan University of Life Sciences, Poznań, Poland
  • Institute of Bioorganic Chemistry PAS, Poznań, Poland
  • Department of Mathematical and Statistical Methods, Poznan University of Life Sciences, Poznań, Poland
  • Department of Mathematical and Statistical Methods, Poznan University of Life Sciences, Poznań, Poland
  • Department of Biotechnology and Food Microbiology, Poznan University of Life Sciences, Poznań, Poland
  • Department of Mathematical and Statistical Methods, Poznan University of Life Sciences, Poznań, Poland
  • Poznan University of Medical Sciences, Department of Hematology, Poznań, Poland and Institute of Computing Science, Poznan University of Technology, Poznań, Poland
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Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.bwnjournal-article-abpv58p573kz
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