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With Shiny 1.3.0, and 0.8.1, you can now add a server function to your R script to provide your interactive app with comprehensive reports, charts and graphics. Introduction {#sec1-1} ============ In many scientific settings, users need to create both static reports and interactive visualisations to analyse and explore their data. For this, Shiny web application framework offers a simple, interactive, graphics interface to create dashboards, plots, and visualisations ([@ref1], [@ref2]). With the promotion of dashboards and dashboards-based visualisation systems, data exploration and reporting have become more powerful and effective in analysing data. RStudio for Windows provides a graphical user interface to R (version 3.3.2) and it is the only RStudio that provides a comprehensive platform for statistical analysis and data exploration. RStudio, as a cross-platform solution, provides users with an environment that is tightly integrated with both the R language and RStudio. The back-end of the RStudio Server is an R service. It can be used to execute R scripts and to be integrated with any other R and Shiny app (through the 'repo:' function) ([@ref3]). It contains the flexibility to add users, groups and permissions and to make RStudio accessible to more than one user. In this regard, it was designed to run multiple Shiny Apps (using the 'runApp()' function), is automatically refreshed after running a Shiny app and can be shared among multiple users. RStudio Server also provides users with a rich set of available services that can be used to create data visualisations, dashboards, reports, server functions, etc. ([@ref4]). An RStudio Server is integrated with R in terms of flexibility and performance ([@ref4]). Here, we use the RStudio Server to present a step-by-step tutorial on how to use RStudio Server to develop a Shiny app for analysis. 1) Set up the RStudio Server and install R packages {#sec2-1} --------------------------------------------------- All services of RStudio Server are integrated with R and can be installed from within RStudio Server by clicking the 'Tools' menu bar (**Fig. 1**). ![RStudio server and R


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