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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:
#> β’ 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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.