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.Β pre-process) the data
- record the operations used to create the data to enable reproducibility
Installation
# stable versions
install.packages('teal.data')
# 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")
Usage
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
# quick start for clinical trial data
my_data <- cdisc_data(
ADSL = example_cdisc_data("ADSL"),
ADTTE = example_cdisc_data("ADTTE"),
code = quote({
ADSL <- example_cdisc_data("ADSL")
ADTTE <- example_cdisc_data("ADTTE")
})
)
# or
my_data <- within(teal_data(), {
ADSL <- example_cdisc_data("ADSL")
ADTTE <- example_cdisc_data("ADTTE")
})
datanames <- c("ADSL", "ADTTE")
datanames(my_data) <- datanames
join_keys(my_data) <- default_cdisc_join_keys[datanames]
# quick start for general data
my_general_data <- within(teal_data(), {
iris <- iris
mtcars <- mtcars
})
Getting help
If you encounter a bug or 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.