Biogen-Inc
Write blog post about the differences between {teal} & {tidyCDISC}
Links
Teal doc: https://insightsengineering.github.io/teal/main/index.html Teal apps:
- https://genentech.shinyapps.io/teal_exploratory/
- https://genentech.shinyapps.io/teal_efficacy/
- https://genentech.shinyapps.io/teal_safety/
tidyCDISC doc: https://biogen-inc.github.io/tidyCDISC/ tidyCDISC app: https://rinpharma.shinyapps.io/tidyCDISC/
Talk metadata
Title: {teal} vs {tidyCDISC}
Short Description (choose one):
- How to choose a shiny app for clinical tables & EDA on ADaM-Ish datasets
- Comparing the only two open source shiny apps for table generation & EDA from ADaM
Abstract: R users now have options when it comes to freely available shiny apps that perform table generation and exploratory data analysis from ADaM. {tidyCDISC} was launched in 2020 and {teal}, part of the {nest} framework, was just recently open sourced in 2022. Both are a means by which to create self-service analytics around ADaM data sets for individual consumption, or even organization wide deployments. These shiny apps can save time for many contributors on your team: clinical heads, statisticians, and even statistical programmers. The two tools have vast differences, but also offer overlapping capabilities. This presentation seeks to compare and contrast the two R packages to help users understand which would best fit their individual and organizational needs.
Nate will be a moderator
Timeline
- Concrete outline with some drafted slides by Thurs, Oct 27th
- Oct 27th, divvy up segments we want to take
- Recordings finished by Nov 3
- Glue together, add tunes, export, upload to youtube,
- officially submit to R/pharma
- Share
Outline
Intro
- Assume nothing, introduce what both tools seek accomplish
- Want to be stress a subjective approach. One tool will certainly work better for you- we just want to help you choose!
- With that said, we are not {teal} experts, so we may have missed something
The meat of the talk
In no particular order, here are some pro's and con's of each tool. These are just ideas! We may use all of them or just some of them for the talk.
Similarities:
- Can produce tables
- Can generate plots
- Can perform statistical procedures
- Can apply dynamic filters
- Can generate reproducible R code
- Can download reports
Differences as of today 6/30:
- Repos: tidyCDISC is on CRAN & GitHub. Teal is just GitHub. GitHub stats (stars/forks)?
- tidyCDISC is a standalone shiny app that offers maximum functionality to all users - takes a "one size fits all" approach. Teal is a part of a framework that can launch very specific functionality to a subset of users.
- Table engines: tidyCDISC leverages the tidyverse (dplyr). Teal uses rtables, but has examples of using tplyr
- Teal has a logging framework
- with {teal}, the filtering module effects data/ tables/ visuals globally, not matter what tab your on