Dipper includes subpackages and modules to create graphical models of this data, including:
- Models package for generating common sets of triples, including common OWL axioms, complex genotypes, associations, evidence and provenance models.
- Graph package for building graphs with RDFLib or streaming n-triples
- Source package containing fetchers and parsers that interface with remote databases and web services
2 Jupyter Notebooks proposed by the Dipper documentation can be easily deploy in Jupyterlab:
- Work with the Dipper Model API: see the documentation
- Query associations from IMPC, including evidence and provenance modeled with SEPIO
workspace/notebooks, install requirements and start the Notebooks:
Access at http://localhost:8888
See the documentation to work with graphs
Or run Jupyterlab it directly using Docker:
Monarch Initiative data generated from Dipper can be accessed through multiple interfaces. The dipper output is quality checked and released on a regular basis.
The data model: OBO
Python scripts to transform the sources: https://github.com/monarch-initiative/dipper/tree/master/dipper/sources
New sources ingestion can be wrote following this documentation.