Data Analysis Using the PIC-SURE API
Once you have refined your queries and created a cohort of interest, you can begin analyzing data using other components of the BioData Catalyst ecosystem.
Last updated
Once you have refined your queries and created a cohort of interest, you can begin analyzing data using other components of the BioData Catalyst ecosystem.
Last updated
Databases exposed through the PIC-SURE API encompass a wide heterogeneity of architectures and data organizations underneath. PIC-SURE hides this complexity and exposes the different databases in the same format, allowing researchers to focus on the analysis and medical insights, thus easing the process of reproducible sciences. The API is available in two different programming languages, python and R, allowing investigators to query databases in the same way using either of those languages. The PIC-SURE API tutorial notebooks can be directly accessed on GitHub.
To access the PIC-SURE API, a user-specific token is needed. This is the way the API grants access to individual users to protected-access data. The user token is strictly personal; do not share it with anyone. You can copy your personalized access token by selecting the User Profile tab at the top of the screen.
Here, you can Copy your personalized access token, Reveal your token, and Refresh your token to retrieve a new token and deactivate the old token.
The PIC-SURE API can be accessed via tutorial notebooks on either BioData Catalyst Powered by Seven Bridges or Powered by Terra.
To launch one of the analysis platforms, go to the BioData Catalyst website. From the Resources menu, select Services. A list of platforms and services on the BioData Catalyst ecosystem will be displayed.
From the Analyze Data in Cloud-based Shared Workspaces section, select Launch for your preferred analysis platform.
Jupyter notebook examples in R and python can be found under the Public projects tab by selecting PIC-SURE API.
From the Data Studio tab, select an example that fits your research needs. Here, we will select PIC-SURE JupyterLab examples.
This will take you to the PIC-SURE API analysis workspace, where you can view the examples in python. Copy this workspace to your own project to edit or run the code yourself.
Note The project must have network access to run the PIC-SURE examples on Seven Bridges. To ensure this, go to the Settings tab and select “Allow network access”.
To access the Jupyter notebook examples in R and python for the PIC-SURE API, select View Workspaces from the Terra landing page.
Select the Public tab and search for “PIC-SURE”. Workspaces for both the python and R examples will be displayed. You must clone the workspaces to edit or run the code within them.
