Building Production-Quality Shiny Applications

R/Pharma 2022 Workshop

🗓️ November 3, 2022 | 9:00am - 12:00pm EDT

🏨 Virtual

💥 FREE with conference registration

📝 To register for the workshop, visit https://rinpharma.com/workshop/2022conference/.

Overview

Shiny empowers R users to create innovative web applications, without requiring substantial expertise in web development frameworks to get up and running. The positive impact of Shiny in data science workflows across academia and a variety of industries such as life sciences is well-known and growing by the year. It is quite common for an early prototype of a Shiny app to generate tremendous excitement for key stakeholders and decision makers, often leading to requests for enhancements and ultimately be included in a production pipeline or process. The road to meeting this goal is challenging, especially for data scientists and statisticians not accustomed to software development! This workshop is for the Shiny developer who has entered this stage of their application development journey. The user is ready to learn how essential workflows, best practices, and the expanding community of Shiny-related packages can help them climb the ladder of Shiny development.

Setup & Configuration

Please view the information in the callouts below for step-by-step instructions on configuring your accounts and environments. While RStudio Cloud is the preferred development environment, you may utilize your local installation of R and RStudio if you prefer.

RStudio Cloud
  1. Join the RStudio Cloud Workspace dedicated to this workshop by visiting this customized invitation URL. If you already have an RStudio Cloud account, you are welcome to use it for the workshop. Otherwise, you can create a new account for free.
  2. You will see a project called simclindata.shiny. Open that project and create a saved copy. This process could take a couple of minutes depending on server load.
  3. After the project loads, you will see messages in the R console about restoring or repairing the package library. Execute renv::restore(prompt = FALSE) to install packages into the project. This process should complete in one or two minutes.

If you prefer to use a local installation of R and RStudio, ensure you setup meets the following requirements:

  • R version 4.1 or later
  • Latest released version of RStudio, v2022.07.0-548 or later
  • The {renv} package.
  • Clone the Shiny application repository used in the workshop: https://github.com/rpodcast/simclindata.shiny

Instructor

{{< var people.enantz.name >}} Eric Nantz is a director within the statistical innovation center at Eli Lilly and Company, creating analytical pipelines and capabilities of advanced statistical methodologies for clinical design used in multiple phases of development. Outside of his day job, Eric is passionate about connecting with and showcasing the brilliant R community in multiple ways. You may recognize his voice from the R-Podcast that he launched in 2012. Eric is also the creator of the Shiny Developer Series where he interviews authors of Shiny-related packages and practitioners developing applications, as well as sharing his own R and Shiny adventures via livestreams on his Twitch channel. In addition, Eric is a curator for the RWeekly project and co-host of the RWeekly Highlights podcast which accompanies every issue.