pROC: an open-source package for R and S+ to analyze and compare ROC curves
Xavier Robin,Natacha Turck,Alexandre Hainard,Natalia Tiberti,Frédérique Lisacek,Jean-Charles Sanchez,Markus Müller +6 more
TLDR
pROC as mentioned in this paper is 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.Abstract:
Receiver 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. With 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. pROC 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.read more
Citations
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Journal ArticleDOI
Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 19-24 weeks' gestation.
TL;DR: The performance of screening for PE by maternal factors and biomarkers in the middle trimester is superior to taking a medical history.
Journal ArticleDOI
Diagnostic accuracy of non-invasive tests for advanced fibrosis in patients with NAFLD: an individual patient data meta-analysis
Ferenc E. Mózes,Jenny Lee,Emmanuel Selvaraj,Arjun Narayan Ajmer Jayaswal,Michael Trauner,Jérôme Boursier,Céline Fournier,Katharina Staufer,Rudolf E. Stauber,Elisabetta Bugianesi,Ramy Younes,Silvia Gaia,Monica Lupșor-Platon,Salvatore Petta,Toshihide Shima,Takeshi Okanoue,Sanjiv Mahadeva,Wah-Kheong Chan,Peter J Eddowes,Gideon M. Hirschfield,Philip N. Newsome,Vincent Wai-Sun Wong,Victor de Ledinghen,Jian-Gao Fan,Feng Shen,Jeremy Cobbold,Yoshio Sumida,Akira Okajima,Jörn M. Schattenberg,Christian Labenz,Won Kim,Myoung Seok Lee,Johannes Wiegand,Thomas Karlas,Yusuf Yilmaz,Guruprasad P. Aithal,Naaventhan Palaniyappan,Christophe Cassinotto,Sandeep Aggarwal,Harshit Garg,Geraldine J. Ooi,Atsushi Nakajima,Masato Yoneda,Marianne Ziol,Nathalie Barget,Andreas Geier,Theresa Tuthill,M. Julia Brosnan,Quentin M. Anstee,Stefan Neubauer,Stephen A. Harrison,Patrick M.M. Bossuyt,Michael Pavlides +52 more
TL;DR: In this article, the authors evaluated the individual diagnostic performance of liver stiffness measurement by vibration controlled transient elastography (LSM-VCTE), Fibrosis-4 Index (FIB-4) and NAFLD (non-alcoholic fatty liver disease) Fibrosis Score (NFS) and derived diagnostic strategies that could reduce the need for liver biopsies.
Journal ArticleDOI
Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer's disease patients from non-demented subjects.
Siranjeevi Nagaraj,Katarzyna Laskowska-Kaszub,Konrad J. Dębski,Joanna Wojsiat,Michał Dąbrowski,Tomasz Gabryelewicz,Jacek Kuźnicki,Urszula Wojda +7 more
TL;DR: 6 miRNAs were selected as the most promising biomarker candidates differentiating early AD from controls with the highest fold changes, consistent significance, specificities and sensitivities.
Journal ArticleDOI
The long-term genetic stability and individual specificity of the human gut microbiome.
Lianmin Chen,Daoming Wang,Sanzhima Garmaeva,Alexander Kurilshikov,Arnau Vich Vila,Ranko Gacesa,Trishla Sinha,Eran Segal,Rinse K. Weersma,Cisca Wijmenga,Alexandra Zhernakova,Jingyuan Fu +11 more
TL;DR: In this article, Wu et al. developed a microbial fingerprinting method that shows up to 85% accuracy in classifying metagenomic samples taken 4 years apart, using individual-specific and temporally stable microbial profiles, including bacterial SNPs and structural variations.
Journal ArticleDOI
Validation of Biomarkers That Complement CA19.9 in Detecting Early Pancreatic Cancer
Alison Chan,Ioannis Prassas,Apostolos Dimitromanolakis,Randall E. Brand,Stefano Serra,Eleftherios P. Diamandis,Ivan M. Blasutig +6 more
TL;DR: The data demonstrate that a serum protein biomarker panel consisting of CA125, CA19.9, and LAMC2 is able to significantly improve upon the performance of CA 19.9 alone in detecting PDAC.
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