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GitHub commit activityGitHub contributorsGitHub last commitGitHub pull requestsGitHub repo sizeGitHub language countProject Status: Active โ€“ The project has reached a stable, usable state and is being actively developed. Current Version Open Issues

This package is used to create the data needed for teal applications. This data can be:

  • Independent data frames
  • CDISC data (for clinical trial reporting)
  • Relational data
  • MultiAssayExperiment objects

This package provides:

  • the mechanism for pulling data from existing systems
  • the ability to mutate (i.e.ย pre-process) the data
  • record the operations used to create the data to enable reproducibility


# stable versions
install.packages('', repos = c('', getOption('repos')))

# install.packages("pak")

Alternatively, you might want to use the development version available on r-universe.

# beta versions
install.packages('', repos = c('', getOption('repos')))

# install.packages("pak")


To understand how to use this package, please refer to the Introduction to article, which provides multiple examples of code implementation.

Below is the showcase of the example usage

# quick start for clinical trial data
adsl <-"ADSL")
adtte <-"ADTTE")

my_data <- cdisc_data(
  cdisc_dataset("ADSL", adsl),
  cdisc_dataset("ADTTE", adtte)
# quick start for general data
my_general_data <- teal_data(
  dataset("iris", iris),
  dataset("mtcars", mtcars)
# reproducibility check
data <- teal_data(dataset("iris", iris, code = "iris <- mtcars"), check = TRUE)
#> Error in x$check_reproducibility() : Reproducibility check failed.
# code extraction
iris2 <- iris[1:6, ]
iris2_data <- teal_data(dataset("iris2", iris2, code = "iris2 <- iris[1:6, ]"))
#> "iris2 <- iris[1:6, ]"

Getting help

If you encounter a bug or you have a feature request - please file an issue. For questions, discussions and staying up to date, please use the โ€œtealโ€ channel in the pharmaverse slack workspace.

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