Class Prediction with Microarray Datasets

  • Simon Rogers
  • Richard D. Williams
  • Colin Campbell
Chapter

Abstract

Microarray technology is having a significant impact in the biological and medical sciences and class prediction will play an increasingly important role in the use and interpretation of microarray data. For example, classifiers could be constructed indicating the detailed subtype of a disease, its expected progression and the best treatment strategy. In this chapter we outline the main stages involved in the development of a successful class predictor for microarray datasets, including data normalisation, the different classifiers which can be used, different feature selection strategies and a method for determining how much data is required for a classification task given an initial sample set. We illustrate this process with both public domain datasets and a new dataset for predicting relapse versus non-relapse for a paediatric tumour.

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Authors and Affiliations

  • Simon Rogers
    • 1
  • Richard D. Williams
    • 2
  • Colin Campbell
    • 1
  1. 1.Advanced Computing Research Centre, University of Bristol, BS8 1TRUnited Kingdom
  2. 2.Dept. of Paediatric Oncology, Institute of Cancer Research, Sutton, SM2 5NGUnited Kingdom

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