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. pre-process) the data
- record the operations used to create the data to enable reproducibility
# stable versions
install.packages('teal.data', repos = c('https://insightsengineering.r-universe.dev', getOption('repos')))
# install.packages("pak")
pak::pak("insightsengineering/teal.data@*release")
Alternatively, you might want to use the development version available on r-universe.
# beta versions
install.packages('teal.data', repos = c('https://pharmaverse.r-universe.dev', getOption('repos')))
# install.packages("pak")
pak::pak("insightsengineering/teal.data")
To understand how to use this package, please refer to the Introduction to teal.data article, which provides multiple examples of code implementation.
Below is the showcase of the example usage
library(teal.data)
# quick start for clinical trial data
adsl <- teal.data::example_cdisc_data("ADSL")
adtte <- teal.data::example_cdisc_data("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$check_reproducibility() : Reproducibility check failed.
# code extraction
iris2 <- iris[1:6, ]
iris2_data <- teal_data(dataset("iris2", iris2, code = "iris2 <- iris[1:6, ]"))
iris2_data$get_code()
#> "iris2 <- iris[1:6, ]"
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 "teal" channel in the pharmaverse
slack workspace.