Chapter 1. Variation, Variability, Batches and Bias in Microarray Experiments: An Introduction

  1. Andreas Scherer Founder/CEO of Spheromics
  1. Andreas Scherer Founder/CEO of Spheromics

Published Online: 2 NOV 2009

DOI: 10.1002/9780470685983.ch1

Batch Effects and Noise in Microarray Experiments: Sources and Solutions

Batch Effects and Noise in Microarray Experiments: Sources and Solutions

How to Cite

Scherer, A. (2009) Variation, Variability, Batches and Bias in Microarray Experiments: An Introduction, in Batch Effects and Noise in Microarray Experiments: Sources and Solutions (ed A. Scherer), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470685983.ch1

Editor Information

  1. Spheromics, Kontiolahti, Finland

Author Information

  1. 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:

  • microarrays;
  • variability;
  • variation;
  • bias;
  • noise;
  • systematic;
  • random;
  • batch effect;
  • experimental design

Summary

Microarray-based measurement of gene expression levels is a widely used technology in biological and medical research. The discussion around the impact of variability on the reproducibility of microarray data has captured the imagination of researchers ever since the invention of microarray technology in the mid 1990s. Variability has many sources of the most diverse kinds, and depending on the experimental performance it can manifest itself as a random factor or as a systematic factor, termed bias. Knowledge of the biological/medical as well as the practical background of a planned microarray experiment helps alleviate the impact of systematic sources of variability, but can hardly address random effects.