Single Cell to Cell Ontology - a BioCypher Knowledge Graph

A BioCypher-driven knowledge graph pipeline for mapping and harmonising single cell experiments.

⚙️ Installation (local, for docker see below)

1. Clone this repository and install the dependencies using Poetry. (Or feel free to use your own dependency management system. We provide a pyproject.toml to define dependencies.)

git clone https://github.com/biocypher/sc2cl.git
cd sc2cl
poetry install

2. You are ready to go!

poetry shell
python create_knowledge_graph.py

🐳 Docker

This repo also contains a docker compose workflow to create the example database using BioCypher and load it into a dockerised Neo4j instance automatically. To run it, simply execute docker compose up -d in the root directory of the project. This will start up a single (detached) docker container with a Neo4j instance that contains the knowledge graph built by BioCypher as the DB docker, which you can connect to and browse at localhost:7474 (don't forget to switch the DB to docker instead of the standard neo4j). Authentication is set to neo4j/neo4jpassword by default and can be modified in the docker_variables.env file.

By using the BIOCYPHER_CONFIG environment variable in the Dockerfile, the biocypher_docker_config.yaml file is used instead of the biocypher_config.yaml. Everything else is the same as in the local setup. The first container installs and runs the BioCypher pipeline, and the second container installs and runs Neo4j. The files created by BioCypher in the first container are copied and automatically imported into the DB in the second container.