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Overview

Interactive Data Visualization with R Shiny for Life Sciences

This repository houses the slides and training materials for a two-day R Shiny tutorial, conducted for the Zurich Ph.D. Program in Molecular Life Sciences (joint program of the University of Zurich and ETH Zurich) in April 2024. The content covers basic to advanced topics and is ideal for anyone looking to improve their data visualisation skills with R Shiny.

Tutorial description

Discover the versatility of R Shiny and explore real-world examples that show how it can be used to efficiently visualise and share scientific data. Learn the basic concepts of R Shiny and create your first R Shiny application from scratch, guided by step-by-step instructions, choosing from several flavours what best suits your needs. Create a dashboard and master interactive elements such as downloading plots, selecting points and zooming into plots. Complete a mini-project with peers to customise your app with advanced widgets, layouts or statistical functions. In addition we will briefly dive into the basics of web development to customise your application beyond the standard options, add a help function and explore methods for sharing and hosting your Shiny apps.

Course Dates: April 8 (1-4 pm) & 11 (2-5 pm) 2024
Site: Irchel campus (UZH)
Tutors: Michael Teske & Jonas Schmid, Institute of Experimental Immunology, University of Zurich

1 ECTS point will be awarded upon course completion.

Course outline

Day 1:

  • Introduction to R Shiny, first app
  • Quick review of ggplot2
  • Exploring Widgets
  • Creating a dashboard

Day 2:

  • Implementing interactive plot functions
  • Advanced R Shiny customization
  • Deploying Shiny apps

Assignment:

Mini-project, further customisation of the app with advanced elements and functions (completion of milestones, group work possible) - Workload: ca. 20 h

Requirements

  • Basic R skills
    • Basic understanding of R syntax
    • Familiarity with installing and loading packages
    • Working with data frames
    • Creating plots (ggplot2)
  • Laptop with recent version of R Studio and access to UZH/eduroam WiFi
  • Full participation in all sessions
  • Completion of mini-project assignment within 10 days after the tutorial

Further details will be provided to the participants shortly before the course starts, and additional information will be posted in the dedicated Slack channel.