HUM calculator and HUM package for R: easy-to-use software tools for multicategory receiver operating characteristic analysis.

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Abstract

Receiver operating characteristic (ROC) analysis is usually applied in bioinformatics to evaluate the abilities of biological markers to differentiate between the presence or absence of a disease. It includes the derivation of the useful scalar performance measure area under the ROC curve for binary classification tasks. As real applications often deal with more than two classes, multicategory ROC analysis and the corresponding hypervolume under the manifold (HUM) measure have become a topic of growing interest. To support researchers in carrying out multicategory ROC analysis, we have developed two tools in different programming environments which feature user-friendly, object-oriented and flexible interfaces and enable the user to compute HUM values and plot 2D- and 3D-ROC curves.

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Author and article information

Journal

Journal ID (iso-abbrev): Bioinformatics

Title: Bioinformatics (Oxford, England)

Publisher: Oxford University Press (OUP)

ISSN (Electronic): 1367-4811

ISSN (Print): 1367-4803

Publication date (Electronic): Jun 01 2014

Volume: 30

Issue: 11

Affiliations

[1 ] Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbüttel, GermanyLaboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany.

[2 ] Laboratory of Bioinformatics, United Institute of Informatics Problems, National Academy of Sciences of Belarus, Surganova 6, 220012 Minsk, Belarus, Bioinformatics and Statistics, Helmholtz Centre for Infection Research, Braunschweig, Germany, Department of Statistics and Applied Probability, National University of Singapore, Singapore, TWINCORE Center for Experimental and Clinical Infection Research, Hannover and Department of Computer Science, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany.

Article

Publisher Item ID: btu086

DOI: 10.1093/bioinformatics/btu086

PubMed ID: 24519383

SO-VID: 8f9da907-66e4-4d95-b429-4c58e81a7092

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