The NGLY1 Deficiency Knowledge Graph
This is the repository for the NGLY1 Deficiency Knowledge Graph, the reasoning context to support hypothesis discovery for NGLY1 Deficiency-CDDG (DOID:0060728) research. The user can navigate the knowledge in the graph in the Neo4j Browser website. This knowledge graph is a structured review around the research question what is the mechanism underpinning the NGLY1-AQP1 regulation association and explaining the reduced transcriptomic expression of multiple Aquaporins in NGLY1 deficient cells?. The graph v3.2 is the first deployed in the Wikibase application for community contribution and curation.
We also provide the related projects on GitHub:
BioKnowledge reviewer: a Python library to build structured reviews around NGLY1 Deficiency research questions as knowledge graphs.
Neo4j Browser Guides: the asciidoc/html files and scripts for the creation of our Neo4j Browser Guides to assist the user on the exploration of the graph in Neo4j. Neo4j.
Krusty: a library to synchronize the NGLY1 Deficiency graph in the Knowledge Navigation (Neo4j) and Knowledge Contribution (Wikibase) components.
- Queralt-Rosinach et al. 2019: Manuscript describing the project.
Versions of the knowledge graph are in the
Workflow to create the graph v3.2
We first built structured reviews using this workflow. To reproduce the creation of the NGLY1 Deficiency knowledge graph v3.2 the user might run the following workflow. Note that the BioKnowledge reviewer library was prototyped using this workflow. We encourage the user to use the library to reproduce the creation of the graph.
- Python 3.
- Jupyter Notebooks framework and the IPython kernel.
decompress the mondo ontology at: ontologies/
The curated network was built in the fly during the execution of the notebook that builds the knowledge graph from all edges reviewed.
1. `get_monarch_connections.ipynb` 2. `add_connections_to_net.ipynb`
RNA expression network
This is a data-driven network built from the NGLY1 knock out transcriptome from fly.
Prepare individual expression datasets:
Increase graph connectivity
Each graph version is stored.