This package is used to create the data needed for teal
applications. This data can be:
MultiAssayExperiment objectsThis package provides:
install.packages('teal.data')Alternatively, you might want to use the development version.
# 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
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
})# reproducibility check
data <- teal_data(iris = iris, code = "iris <- mtcars")
verify(data)
#> Error: Code verification failed.
#> Object(s) recreated with code that have different structure in data:
#> • iris# code extraction
iris2_data <- within(teal_data(), {iris2 <- iris[1:6, ]})
get_code(iris2_data)
#> "iris2 <- iris[1:6, ]"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.
