Simple interactive research sharing with R Shiny Compact Course: Simple interactive research sharing with R Shiny

• Date: 19.02.2026
• Time: 9am - 1pm
• Instructor: James Bowyer, Research Software Engineer, Scientific Software Center
• Venue: Mathematikon Bauteil A, Im Neuenheimer Feld 205, in the conference room 5/104 on the 5th floor

This is a half day course.

• Have R installed on a laptop/computer you bring
• Know basic R programming, including: how to open a data file with R, how to make a plot with R
• No knowledge of R specific tooling is used, RStudio will be used in explanations, but not required

Rather than just share pictures of your R research/graphs, R Shiny lets you turn your existing R analysis into an interactive web application that anyone can access through a link. With this live interface, your collaborators, grant reviewers, or other researchers can investigate the specific aspects they care about - like filtering by their genes of interest or adjusting parameters. We'll cover how to convert your current R files into Shiny apps, with practical information also relevant for Python Streamlit users on costs, maintenance time, and an overview of the process of hosting them online covered at the start so you can decide if this workshop is relevant for your purposes. This workshop is hands-on and works best when you send your R scripts to us one week in advance. You do not need to learn complicated web development - just the R you already know from the console and the process of deploying which works very similarly, and can all be completed inside of the “R studio” application. After this workshop, you will be able to share future projects the same way.

• Build and deploy a basic R-Shiny application that works with normal/existing R code without needing web-specific knowledge/experience
• Learn how to make plots interactive with basic user input, so that your R results and graphs can be interactive or show specific data according to specific user needs (e.g. lets users filter to view certain genes in one plot)
• Understand what the financial and technical maintenance workload is for your lab to run and share online R apps
• Optional extra: Make a screenshot of your data/graph/plots appear on a R webpage via your computer, deploy it to shinyapps.io, and then confirm you can access it from another device (e.g. your phone) to fully show the full process of produce a shareable R application as a website

Please register here to sign up for this course.