
tidyCDISC is a shiny app to easily create custom tables
and figures from ADaM-ish data sets.
One of tidyCDISC’s goals is to develop clinical tables
that meet table standards leveraged for submission filings, called
“standard analyses”. However, this is secondary to the app’s primary
purpose: providing rich exploratory capabilities for clinical studies.
High-level features of the app allow users to produce customized tables
using a point-and-click interface, examine trends in patient populations
with dynamic figures, and supply visualizations that narrow in on a
single patient profile.
The beauty of the application: users don’t have to write a lick of
code to gather abundant insights from their study data. Thus,
tidyCDISC aims to serve a large population of clinical
personnel with varying levels of programming experience. For
example:
A clinical head, with presumably no programming experience (but the most domain expertise) can explore results without asking a statistician or programmer to build tables & figures.
A statistician can use the application to make tables / figures instantly, cutting down on excess statistical programming requests for tables that aren’t required, but are “nice to see”.

tidyCDISC to perform preliminary QC programming prior to
writing their own code in a validated process. Users who leverage
tidyCDISC for routine trial analysis report
significant time savings, about 95% on average, when
performing their programming duties.For a high-level overview of the app with brief 10-minute demo,
please review the following presentation on tidyCDISCat
Shiny Conf 2022:
As previously mentioned, tidyCDISC can only accept data
sets that conform to CDISC ADaM standards with some minor flexibility
(see upload
requirements for more details). At this time, the app is designed to
accept sas7bdat files only.
If you’re looking to regularly generate R code for tables, the
tidyCDISC app offers a handy feature to export an R script
for full reproducibility of analyses performed in the app.
You can start using the demo version of the app here: tidyCDISC. Note the
demo version disables the Data Upload feature and,
instead, uses CDISC pilot data. If you’d like to upload your own study
data, we recommend installing tidyCDISC from CRAN
(instructions below) to run the app locally or deploy it in your
preferred environment. Please review the “Get
Started” guide to follow an example use case with the app. However,
to optimize one’s use of tidyCDISC, we highly recommend
reading the following articles that take a deeper look into the topics
presented in the “Get Started” tutorial:
We’re confident the tidyCDISC application can save you
time. If there is some use case that tidyCDISC can’t solve,
we want to know about it. Please send the developers
a message with your question or request!
tidyCDISC R packageAs a reminder, you can start using the demo version of the app right
now: launch
tidyCDISC without any installation required. However, if you choose
to upload your own study data OR export & run R code from the Table
Generator, you will need the tidyCDISC package installed on
your machine. Execute the following code to install the package:
# Install from CRAN
install.packages("tidyCDISC")
# Or install the latest dev version
remotes::install_github("Biogen-Inc/tidyCDISC")With a simple library(tidyCDISC) you can access all the
exported functions from tidyCDISC that help users reproduce
analysis performed in the app. Or, you can run the application locally
(or deploy it in an app.R file) using:
# Launch the application
tidyCDISC::run_app()tidyCDISC is an actively developed project, so things
are frequently changing. As such, there are a number of ways to stay
current with the latest changes in any user workflows & methods for
new (or past) releases! First, our
blog covers all the new features and squashed bugs with detailed
visuals and explanations to help you get up to speed. In addition, we
have a YouTube
channel that posts explain-er videos for special how-to’s, tips, and
techniques. Last, the NEWS
file is a great resource for a recap on all the changes, with links
to issues and actual code changes available for your review.
Happy exploring!