MEPHAS: an interactive graphical user interface for medical and pharmaceutical statistical analysis with R and Shiny

Even though R is one of the most commonly used statistical computing environments, it lacks a graphical user interface (GUI) that appeals to students, researchers, lecturers, and practitioners in medicine and pharmacy for conducting standard data analytics. Current GUIs built on top of R, such as EZR and R-Commander, aim to facilitate R coding and visualization, but most of the functionalities are still accessed through a command-line interface (CLI). To assist practitioners of medicine and pharmacy and researchers to run most routines in fundamental statistical analysis, we developed an interactive GUI; i.e., MEPHAS, to support various web-based systems that are accessible from laptops, workstations, or tablets, under Windows, macOS (and IOS), or Linux. In addition to fundamental statistical analysis, advanced statistics such as the extended Cox regression and dimensional analyses including partial least squares regression (PLS-R) and sparse partial least squares regression (SPLS-R), are also available in MEPHAS. MEPHAS is a web-based GUI (https://alain003.phs.osaka-u.ac.jp/mephas/) that is based on a shiny framework. We also created the corresponding R package mephas (https://mephas.github.io/). Thus far, MEPHAS has supported four categories of statistics, including probability, hypothesis testing, regression models, and dimensional analyses. Instructions and help menus were accessible during the entire analytical process via the web-based GUI, particularly advanced dimensional data analysis that required much explanation. The GUI was designed to be intuitive for non-technical users to perform various statistical functions, e.g., managing data, customizing plots, setting parameters, and monitoring real-time results, without any R coding from users. All generated graphs can be saved to local machines, and tables can be downloaded as CSV files. MEPHAS is a free and open-source web-interactive GUI that was designed to support statistical data analyses and prediction for medical and pharmaceutical practitioners and researchers. It enables various medical and pharmaceutical statistical analyses through interactive parameter settings and dynamic visualization of the results.

[1]  Jj Allaire,et al.  Web Application Framework for R , 2016 .

[2]  Peter P. Wakker,et al.  MF Calculator: A Web-Based Application for Analyzing Similarity , 2015 .

[3]  R B D'Agostino,et al.  Frailty models: Applications to biomedical and genetic studies , 2011, Statistics in medicine.

[4]  John Fox,et al.  GETTING STARTED WITH THE R COMMANDER: A BASIC-STATISTICS GRAPHICAL USER INTERFACE TO R , 2005 .

[5]  Sy Han Chiou,et al.  Fitting Accelerated Failure Time Models in Routine Survival Analysis with R Package aftgee , 2014 .

[6]  Florian Detsch,et al.  remote: Empirical Orthogonal Teleconnections in R , 2015 .

[7]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[8]  D. Kleinbaum,et al.  Applied regression analysis and other multivariable methods, 3rd ed. , 1998 .

[9]  D. Kleinbaum,et al.  Applied Regression Analysis and Other Multivariate Methods , 1978 .

[10]  S. Keleş,et al.  Sparse partial least squares regression for simultaneous dimension reduction and variable selection , 2010, Journal of the Royal Statistical Society. Series B, Statistical methodology.

[11]  Y. Kanda,et al.  Investigation of the freely available easy-to-use software ‘EZR' for medical statistics , 2012, Bone Marrow Transplantation.

[12]  Matthias Schmid,et al.  A Robust Alternative to the Schemper–Henderson Estimator of Prediction Error , 2011, Biometrics.

[13]  Lee-Jen Wei,et al.  The accelerated failure time model: a useful alternative to the Cox regression model in survival analysis. , 1992, Statistics in medicine.

[14]  A. Berger.  FUNDAMENTALS OF BIOSTATISTICS , 1969 .

[15]  R. Gray.  Modeling Survival Data: Extending the Cox Model , 2002 .

[16]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..