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Statistical Methods in Microarray Gene Expression Data Analysis

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Probabilistic Modeling in Bioinformatics and Medical Informatics

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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Summary

Microarrays allow the simultaneous measurement of the expression levels of thousands of genes. This unique data structure has inspired a completely new area of research in statistics and bioinformatics. The objective of the present chapter is to review some of the main statistical tools used in this context. We will mainly focus on low-level preprocessing steps: image analysis, data transformation, normalization, and multiple testing for differential expression. The high-level inference of genetic regulatory interactions from preprocessed microarray data will be covered in Chapters 8 and 9.

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Author information

Authors and Affiliations

  1. BioSS Office at the Rowett Research Institute, Biomathematics & Statistics Scotland, Aberdeen, AB21 9SB, UK

    Claus-Dieter Mayer

  2. Biomathematics & Statistics Scotland, King’s Buildings, Edinburgh, EH9 3JZ, UK

    Chris A. Glasbey

Authors
  1. Claus-Dieter Mayer
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  2. Chris A. Glasbey
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Editor information

Editors and Affiliations

  1. Biomathematics and Statistics-BioSS, UK

    Dirk Husmeier DiplPhys, MSc, PhD

  2. InferSpace, UK

    Richard Dybowski BSc, MSc, PhD

  3. Oxford University, UK

    Stephen Roberts MA, DPhil, MIEEE, MIoP, CPhys

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© 2005 Springer-Verlag London Limited

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Mayer, CD., Glasbey, C.A. (2005). Statistical Methods in Microarray Gene Expression Data Analysis. In: Husmeier, D., Dybowski, R., Roberts, S. (eds) Probabilistic Modeling in Bioinformatics and Medical Informatics. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/1-84628-119-9_7

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  • DOI: https://doi.org/10.1007/1-84628-119-9_7

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-778-0

  • Online ISBN: 978-1-84628-119-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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