/decider-genetics

Primary LanguagePythonMIT LicenseMIT

DECIDER genetics knowledge graph

This pipeline creates a BioCypher knowledge graph from Hautaniemi lab pipeline outputs. It requires access to the data files to run.

⚙️ Installation (local, for docker see below)

git clone https://github.com/biocypher/decider-genetics.git
cd decider-genetics
poetry install
poetry run 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 neo4j (the default DB), which you can connect to and browse at localhost:7474. Authentication is deactivated by default and can be modified in the docker_variables.env file (in which case you need to provide the .env file to the deploy stage of the docker-compose.yml).

Regarding the BioCypher build procedure, the biocypher_docker_config.yaml file is used instead of the biocypher_config.yaml (configured in scripts/build.sh). Everything else is the same as in the local setup. The first container (build) installs and runs the BioCypher pipeline, the second container (import) installs Neo4j and runs the import, and the third container (deploy) deploys the Neo4j instance on localhost. The files are shared using a Docker Volume. This three-stage setup strictly is not necessary for the mounting of a read-write instance of Neo4j, but is required if the purpose is to provide a read-only instance (e.g. for a web app) that is updated regularly; for an example, see the meta graph repository. The read-only setting is configured in the docker-compose.yml file (NEO4J_dbms_databases_default__to__read__only: "false") and is deactivated by default.