Chapter 5. Aspects of Technical Bias

  1. Andreas Scherer Founder/CEO of Spheromics
  1. Martin Schumacher1,
  2. Frank Staedtler1,
  3. Wendell D Jones2 and
  4. Andreas Scherer Founder/CEO of Spheromics3

Published Online: 2 NOV 2009

DOI: 10.1002/9780470685983.ch5

Batch Effects and Noise in Microarray Experiments: Sources and Solutions

Batch Effects and Noise in Microarray Experiments: Sources and Solutions

How to Cite

Schumacher, M., Staedtler, F., Jones, W. D. and Scherer, A. (2009) Aspects of Technical Bias, in Batch Effects and Noise in Microarray Experiments: Sources and Solutions (ed A. Scherer), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470685983.ch5

Editor Information

  1. Spheromics, Kontiolahti, Finland

Author Information

  1. 1

    Biomarker Development, Novartis Pharma AG, Basel, Switzerland

  2. 2

    Expression Analysis Inc., Durham, NC, USA

  3. 3

    Spheromics, Kontiolahti, Finland

Publication History

  1. Published Online: 2 NOV 2009
  2. Published Print: 30 OCT 2009

ISBN Information

Print ISBN: 9780470741382

Online ISBN: 9780470685983

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Keywords:

  • observational studies;
  • technical variation;
  • directionality;
  • probe set level;
  • nucleotide sequence;
  • batch effect signature

Summary

Variation in microarray data can result from technical and biological sources. While the extent to which factors contribute to this variation has been largely investigated (Bakay et al. 2002; Boedigheimer et al. 2008; Eklund and Szallasi 2008; Fare et al. 2003; Han et al. 2004; Lusa et al. 2007; Novak et al. 2002; Zakharkin et al. 2005), the nature and extent of the signal intensity changes with which variation manifests itself in the data has not been a major focus of research. Using several real microarray data sets with known batch effects, we analyze and describe how technical variation is translated into gene expression changes.