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ROC Curves for the Statistical Analysis of Microarray Data

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Microarray Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1986))

Abstract

A receiver operating characteristic (ROC) curve is a graphical plot that illustrates the diagnostic ability of a binary classifier as a function of its discrimination threshold. This chapter is an overview on the use of ROC curves for microarray data. The notion of ROC curve and its motivation is introduced in Subheading 1. Relevant scientific contributions concerning the use of ROC curves for microarray data are briefly reviewed in Subheading 2. The special case with covariates is considered in Subheading 3. Two relevant aspects are reviewed in this section: the use of LASSO techniques for selecting and combining relevant markers and how to correct for multiple testing when a large number of markers are available. Finally, some conclusions are included.

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Author information

Authors and Affiliations

  1. Research Group MODES, Department of Mathematics, CITIC and ITMATI, Universidade da Coruña, A Coruña, Spain

    Ricardo Cao

  2. Research Group MODES, Department of Mathematics, Universidade da Coruña, Ferrol, Spain

    Ignacio López-de-Ullibarri

Authors
  1. Ricardo Cao
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  2. Ignacio López-de-Ullibarri
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Corresponding author

Correspondence to Ricardo Cao .

Editor information

Editors and Affiliations

  1. CITIC, Universidade da Coruña, A Coruña, Spain

    Verónica Bolón-Canedo

  2. CITIC, Universidade da Coruña, A Coruña, Spain

    Amparo Alonso-Betanzos

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Cao, R., López-de-Ullibarri, I. (2019). ROC Curves for the Statistical Analysis of Microarray Data. In: Bolón-Canedo, V., Alonso-Betanzos, A. (eds) Microarray Bioinformatics. Methods in Molecular Biology, vol 1986. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9442-7_11

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  • DOI: https://doi.org/10.1007/978-1-4939-9442-7_11

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9441-0

  • Online ISBN: 978-1-4939-9442-7

  • eBook Packages: Springer Protocols

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