This pipeline creates a BioCypher knowledge graph from Hautaniemi lab pipeline outputs. It requires access to the data files to run.
git clone https://github.com/biocypher/decider-genetics.git
cd decider-genetics
poetry install
poetry run python create_knowledge_graph.py
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.