pROC: an open-source package for R and S+ to analyze and compare ROC curves

BMC Bioinformatics

Software

Natalia Tiberti¹  Alexandre Hainard¹  Xavier Robin¹  Jean-Charles Sanchez¹  Natacha Turck¹  Frédérique Lisacek²  Markus Müller² 

[1] Biomedical Proteomics Research Group, Department of Structural Biology and Bioinformatics, Medical University Centre, Geneva, Switzerland;Swiss Institute of Bioinformatics, Medical University Centre, Geneva, Switzerland;

关键词: Receiver Operating Characteristic;    Receiver Operating Characteristic Curve;    Receiver Operating Characteristic Analysis;    Receiver Operating Characteristic Plot;    Empirical Receiver Operating Characteristic Curve;   

DOI  :  10.1186/1471-2105-12-77

 received in 2010-09-10, accepted in 2011-03-17,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundReceiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface.ResultsWith data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC.ConclusionspROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

【 授权许可】

CC BY   
© Robin et al; licensee BioMed Central Ltd. 2011