TLGs (tables, listings, and graphs - also known as TLFs/TFLs with F for figures) refer to the packages that take data, and convert then into a human intepretable insight.
There are two relevant stages of TLGs - static TLGs, which as of today are the only type of evidence submitted to regulatory bodies, and interactive TLGs, which are predominantly, but not limited to, shiny apps.
For tables, we recommend the effort from R Consortium - Tables in Clinical Trials with R - as a useful read to compare examples from several of the below packages.
Tables
rtables
A framework for declaring complex multi-level tabulations and then applying them to data
chevron
Holds TLG template standards to create standard outputs for clinical trials reporting with limited parameterisation.
pharmaRTF
Enhanced RTF wrapper written in R for use with existing R tables packages such as huxtable or GT
Tplyr
To simplify the data manipulation necessary to create clinical reports
gtsummary
Creates tables from either an Analysis Results Dataset (ARD) or a data frame with an ARD by-product
cards
Construct CDISC Analysis Results Dataset (ARD) objects
cardx
Extra Analysis Results Data (ARD) summary objects supplementary to {cards}
tfrmt
A language for defining display-related metadata to automate the transformation from an Analysis Results Dataset (ARD) to a table
tfrmtbuilder
A Shiny app interface for the {tfrmt} package
tidytlg
Generate table, listings, and graphs (TLG) using the Tidyverse
Listings
rlistings
A framework for creating data listings
Plots
ggsurvfit
Eases the creation of time-to-event (aka survival) summary figures
While ggplot2 is a lower level, non-pharma specific plotting package. It is universally accepted as the package for graphics, so included here and as a non-pharma package.
ggplot2 An implementation of the Grammar of Graphics in R, and the most popular plotting package for static plots in R.
Interactive
tidyCDISC
A shiny app to easily create custom tables and figures from ADaM-ish data sets
rhino
Supports creating and extending enterprise Shiny applications using best practices
Frameworks
The following frameworks allow for the engine used to generate the output to be modified.
For example, they could be used with ggplot2, rtables, plotly, or Tplyr.
tern
Layers analytics from descriptive summaries to more complex statistics on top of the foundational table layouts, analytic and content controls
teal
Framework developed that leverages the R Shiny package to scale development of our shiny apps
Tables, Listings, and Graphs Catalogs with many examples are available here:
There are publicly available example Shiny applications created using these:
- The efficacy APP Efficacy
- The safety APP Safety
- The exploratory APP Exploratory
Upcoming packages for consideration
The following is being worked up towards CRAN submission to be considered for later inclusion into the pharmaverse - we felt important to share here in case others are working in a similar space and would be interested to collaborate with the respective developers.
cardinal
Implementation of table-generating functions to implement standard FDA Safety Tables according to the guidelines.