Extract data from fhir-document-reference and create visualizations
The purpose of this repo is to extract metadata (gender, race, ethnicity, etc.) from the fhir-document-reference that is attached to each file in a CAVATICA project.
1 - use Implement.ipynb to extract data using Extract_Visualize_Data.py
2 - use Visualize.ipynb to visualize the data using Panels
These scripts were tested on a project that imported the HTP study from the INCLUDE portal into a project, but could be generalized to any project where each file has a fhir-document-reference.
The .py script to extract data using the FHIR api is Extract_Visualize_Data.py
Quick help:
usage: Extract_Visualize_Data.py [-h] --cavatica_token CAVATICA_TOKEN
--cavatica_project CAVATICA_PROJECT
--include_fhir_authentication_cookie
INCLUDE_FHIR_AUTHENTICATION_COOKIE
Retrieve metadata from the INCLUDE Server and updates the metadata on the
Cavatica Project
optional arguments:
-h, --help show this help message and exit
--cavatica_token CAVATICA_TOKEN
You can find your developer token at
https://cavatica.sbgenomics.com/developer/token
--cavatica_project CAVATICA_PROJECT
The Cavatica project where the files are already
imported from the INCLUDE Portal
--include_fhir_authentication_cookie INCLUDE_FHIR_AUTHENTICATION_COOKIE
The Authorization cookie from the INCLUDE FHIR Server
(https://include-api-fhir-service.includedcc.org/) To
obtain the cookie, open the Chorme or Firefox console,
go to the Application tab and copy the value contained
in `AWSELBAuthSessionCookie-0`.
The data extracted from the fhir-document-reference is saved as a dataframe. See Implement.ipynb for how to do this.
Once the data is saved as a dataframe, the visualization is created using Panels - see Visualize.ipynb for how this is done.
*To save time, the dataframe is saved as a .csv file, so the Visualization.ipynb can be run without re-running the Implement.ipynb.
Here is what the result will look like, without running any code.
