Effect of normalization on microarray-based classification

Jianping Hua, Yoganand Balagurunathan, Yidong Chen, James Lowey, Michael L. Bittner, Zixiang Xiong, Edward Suh, Edward R. Dougherty

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When using cDNA microarrays, normalization to correct biases is a common preliminary step before carrying out any data analysis, its objective being to reduce the systematic variations between the arrays. The biases are due to various systematic factors - scanner setting, amount of mRNA in the sample pool, and dye response characteristics between the channels. Since expression-based phenotype classification is a major use of microarrays, it is important to evaluate microarray normalization procedures relative to classification. Using a model-based approach, we model the systemic-error process to generate synthetic gene-expression values with known ground truth. Three normalization methods and three classification rules are then considered. Our simulation shows that normalization can have a significant benefit for classification under difficult experimental conditions.

Original languageEnglish (US)
Title of host publication2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006
Pages7-8
Number of pages2
DOIs
StatePublished - 2006
Externally publishedYes
Event2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006 - College Station, TX, United States
Duration: May 28 2006May 30 2006

Publication series

Name2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006

Other

Other2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006
Country/TerritoryUnited States
CityCollege Station, TX
Period5/28/065/30/06

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Statistics and Probability

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