This repo demonstrates how to use the ipycytoscape widget to visualize a Neo4j subgraph with cytoscape.js in Jupyter Lab. It also demonstrates how to setup a local instance of the Neo4j graph database and launch Neo4j Browser from a Notebook.
Example subgraph rendered in Jupyter Notebook.
Colors and styles of nodes and relationships can be changed. By clicking on a node, a tooltip with the node properties is displayed. The layout can also be manually changed by dragging nodes to new positions.
| Notebook | Description |
|---|---|
| Neo4j_Example1 | Creates a small Neo4j graph locally and demonstrates how to display a Neo4j subgraph |
| Neo4j_Example2 | Accesses the COVID-19-Net Knowledge Graph server and demonstrates how to display a Neo4j subgraph |
Follow the steps below to setup and run the example notebooks on Mac, Linux, or Windows.
Prerequisites: Miniconda3 (light-weight, preferred) or Anaconda3 and Mamba (faster than Conda)
- Install Miniconda3
- Update an existing miniconda3 installation:
conda update conda - Install Mamba:
conda install mamba -n base -c conda-forge - Install Git (if not installed):
conda install git -n base -c anaconda
1. Clone this Git repository
git clone https://github.com/sbl-sdsc/neo4j-ipycytoscape.git
cd neo4j-ipycytoscape
2. Create a Conda environment
The file environment.yml specifies the Python version and all packages required by the tutorial.
mamba env create -f environment.yml
Activate the conda environment
conda activate neo4j-ipycytoscape
3. Launch Jupyter Lab
jupyter lab
Navigate to the notebooks directory to run the example Jupyter Notebooks.
4. Deactivate the Conda environment
When you are finished, deactivate the conda environment or close the terminal window.
conda deactivate
To remove the Conda environment, run
conda env remove -n neo4j-ipycytoscape
Expanse is an National Science Foundation (NSF)-funded supercomputer at the San Diego Supercomputer Center at UC San Diego. Free allocations are available for academic researchers. A trial allocation can be obtained by contacting consult@sdsc.edu or a full allocation by applying through the ACCESS progam.
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Log into the Expanse Portal with your ACCESS credentials.
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Open a Terminal Window ("Shell Access") through the Expanse Portal.
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Clone the Git repository neo4j-ipycytoscape
git clone https://github.com/sbl-sdsc/neo4j-ipycytoscape.git
- Change into the neo4j-ipycytoscape directory
cd neo4j-ipycytoscape
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Launch Jupyter Lab using the Galyleo
Fill in the your project account number in the command below. Galyleo will generate a URL for your Jupyter Lab session and create a Conda environment specified by the environment.yml file.
galyleo launch --account <account_number> --partition shared --cpus 1 --memory 8 --time-limit 00:30:00 --conda-env neo4j-ipycytoscape --conda-yml environment.yml --mamba
Note, before you use Galyleo the first time, append
export PATH="/cm/shared/apps/sdsc/galyleo:${PATH}"to the.bashrcfile in your home directory then and runsource ./.bashrc.
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Open a new tab in your web browser and paste the Jupyter Lab URL.
Wait until Jupyter Lab launches. This may take several minutes.
You should see the Satellite Reserver Proxy Servive page launch in your browser.
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Run the example notebooks
Navigate to the
notebooksdirectory to run the example Jupyter Notebooks. -
Shutdown Jupyter Lab
From the file menu select
Shutdownto terminate the process.
If you do not shutdown Jupyter Lab, the process will continue running and use up allocated resources.
Peter W. Rose, David Valentine, Ilya Zaslavsky, COVID-19-Net: Integrating Health, Pathogen and Environmental Data into a Knowledge Graph for Case Tracking, Analysis, and Forecasting. Available online: https://github.com/covid-19-net/covid-19-community (2020).
The Neo4j graph visualization for ipycytoscape was in part supported by the National Science Foundation under Award Numbers:
NSF Convergence Accelerator Phase I (RAISE): Knowledge Open Network Queries for Research (KONQUER) (1937136)
NSF RAPID: COVID-19-Net: Integrating Health, Pathogen and Environmental Data into a Knowledge Graph for Case Tracking, Analysis, and Forecasting (2028411)