easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment

ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls. There are a number of analysis tools which are used to guide researchers through their analysis. Some of these tools are commercial and provide basic methods for ROC curve analysis while others offer advanced analysis techniques and a command-based user interface, such as the R environment. The R environmentg includes comprehensive tools for ROC curve analysis; however, using a command-based interface might be challenging and time consuming when a quick evaluation is desired; especially for non-R users, physicians etc. Hence, a quick, comprehensive, free and easy-to-use analysis tool is required. For this purpose, we developed a user-friendly web tool based on the R language. This tool provides ROC statistics, graphical tools, optimal cutpoint calculation, comparison of several markers, and sample size estimation to support researchers in their decisions without writing R codes. easyROC can be used via any device with an internet connection independently of the operating system. The web interface of easyROC is constructed with the R package shiny. This tool is freely available through www.biosoft.hacettepe.edu.tr/easyROC.

Dincer Goksuluk , Selcuk Korkmaz , Gokmen Zararsiz , A. Ergun Karaagaoglu
2016-12-23

CRAN packages used

ROCR, pROC, OptimalCutpoints, shiny, plotROC, plyr

CRAN Task Views implied by cited packages

MachineLearning, Multivariate, WebTechnologies

Bioconductor packages used

ROC

Reuse

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Citation

For attribution, please cite this work as

Goksuluk, et al., "easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment", The R Journal, 2016

BibTeX citation

@article{RJ-2016-042,
  author = {Goksuluk, Dincer and Korkmaz, Selcuk and Zararsiz, Gokmen and Karaagaoglu, A. Ergun},
  title = {easyROC: An Interactive Web-tool for ROC Curve Analysis Using R Language Environment},
  journal = {The R Journal},
  year = {2016},
  note = {https://doi.org/10.32614/RJ-2016-042},
  doi = {10.32614/RJ-2016-042},
  volume = {8},
  issue = {2},
  issn = {2073-4859},
  pages = {213-230}
}