siera

Are you looking for a way to automate TFLs?

With siera, users ingest Analysis Results Standard - ARS (a CDISC Foundational standard) metadata and auto-generate R scripts that, when run in with provided ADaM datasets, provide Analysis Results Datasets (ARDs).

In order to use the readARS() function, users will need to provide the following:

1. A Functional JSON file, representing ARS Metadata for a Reporting Event (to get started, see TFL Designer)
2. An output directory where the R scripts will be placed
3. A folder containing the related ADaM datasets for the ARDs to be generated

Installation

The current version (0.1.0) of siera can be installed from GitHub with:

# install.packages("devtools")
Sys.unsetenv("GITHUB_PAT")
devtools::install_github("https://github.com/clymbclinical/siera")

Example

library(siera)

siera includes several example files, which we use throughout the documentation. These include a JSON ARS file, as well as some csv ADaMs (ADSL and ADAE) which can be run with the R scripts produced by readARS function. Use the helper ARS_example() with no arguments to list them or call it with an example filename to get the path.

ARS_example()
#> [1] "ADAE.csv"                           "ADSL.csv"                          
#> [3] "ARS_V1_Common_Safety_Displays.json"

ARS_example("ARS_V1_Common_Safety_Displays.json")
#> [1] "C:/Users/mbosm/AppData/Local/R/win-library/4.4/siera/extdata/ARS_V1_Common_Safety_Displays.json"

Using an example JSON ARS file, run readARS() function to produce the ARD programs.

In this example, the following is used: 1. JSON ARS file from CDISC Pilot Study

# the ARS JSON File. 
json_path <- ARS_example("ARS_V1_Common_Safety_Displays.json")

# store ARD scripts in this folder (we will use a temporary directory, 
# but you may set to desired path):
output_folder <- tempdir()

# this folder contains ADaM datasets to produce ARD (we will use temporary 
# directory, but to make it workable, download the ADaMs required and use the location 
# they are stored in):
ADaM_folder <- tempdir()

# run the readARS function with these 3 parameters.  This creates R scripts (1 for each output in output_folder)
readARS(json_path, output_folder, adam_path = ADaM_folder)

Once the R programs are created, they can be individually run, provided that the ADaM datasets are in the location as provided to the readARS function.