GraphConnect Europe 2016 - Building a Repository of Biomedical Ontologies with Neo4j - Simon Jupp
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This document discusses building a repository of biomedical ontologies using Neo4j. It describes loading over 140 ontologies with over 4.5 million terms and 11 million relations into Neo4j. This allows complex ontology queries and navigation of relationships. The repository is accessed through a REST API and is being used by over 2000 users for tasks like exploring disease relationships and taxonomic classification. Maintaining and improving the system is an ongoing effort.
![What are the sub types of “colorblindess”?
MATCH (n:Class {obo_id: 'HP:0007641'})<-[r*]-(types:Class)
RETURN n, r, types](https://image.slidesharecdn.com/emblgraph-connect-160504091609/85/GraphConnect-Europe-2016-Building-a-Repository-of-Biomedical-Ontologies-with-Neo4j-Simon-Jupp-13-320.jpg)
![What parts of the eye are related to
diseases?MATCH
(eye:Class {obo_id: 'UBERON:0000970'})<-[r:Related
{label : "part_of"}]-(eye_part:Class)<-[r1:Related
{label : "has_disease_location"}]-(disease:Class)
RETURN eye, r,r1, eye_part, disease](https://image.slidesharecdn.com/emblgraph-connect-160504091609/85/GraphConnect-Europe-2016-Building-a-Repository-of-Biomedical-Ontologies-with-Neo4j-Simon-Jupp-14-320.jpg)
![Finding common ancestors via shortest path
Match p=shortestPath( (a:Class)-[r:SUBCLASSOF*]-(b:Class) )
Return nodes(p)
What is the common taxonomic
superfamily of Gibbons and Chimpanzees?
(or Hylobatidae and Pan troglodytes!)
https://commons.wikimedia.org/wiki/File:Hylobates_lar_pair_of_white_and_black_01.jpg](https://image.slidesharecdn.com/emblgraph-connect-160504091609/85/GraphConnect-Europe-2016-Building-a-Repository-of-Biomedical-Ontologies-with-Neo4j-Simon-Jupp-15-320.jpg)
![OLS visualisations
• Partonomy for heart from the UBERON anatomy ontology
MATCH path = (n:Class)-[r:SUBCLASSOF|PartOf*]->(ancestor)](https://image.slidesharecdn.com/emblgraph-connect-160504091609/85/GraphConnect-Europe-2016-Building-a-Repository-of-Biomedical-Ontologies-with-Neo4j-Simon-Jupp-16-320.jpg)
GraphConnect Europe 2016 - Building a Repository of Biomedical Ontologies with Neo4j - Simon Jupp
- 1. Building a repository of biomedical ontologies with Neo4j Simon Jupp jupp@ebi.ac.uk, @simonjupp Samples, Phenotypes and Ontologies Team European Bioinformatics Institute Cambridge, UK.
- 2. Biological data heavily interlinked Proteome Metabolome Genome tissue CE-MS antibody array LC-MS/MS m/z 600 800 1000 1200 1400 1600 10 20 30 40 50 60 70 80 90 100 Intensity 609.256 b6 755.422 y8 882.357 b9 852.476 y9 995.435 b10 1092.506 b11 1181.252 y12 1318.578 b13 1587.759 b16 1715.817 b18 858.408 b18 ++ 794.380 b16 ++ 0 miRNA array mRNA array PathwaysProtein Interaction Drug targets
- 3. We need terminology standards Dyschromatopsia
- 4. Search PubMed for “color blindness”
- 5. Search PubMed for “Dyschromatopsia”
- 6. Search PubMed for "abnormality of the eye"
- 7. The ontology of color blindness HP:0011518 (Dichromacy )HP:0011518 (Eye) HP:0000551 (Abnormality of color vision ) HP:0007641 (Dyschromatopsia) Is-a Is-a Disease-location
- 8. The ontology of color blindness HP:0011518 (Dichromacy )HP:0011518 (Eye) HP:0000551 (Abnormality of color vision ) HP:0007641 (Dyschromatopsia) Is-a Is-a Disease-location “Colorblindness” “A form of colorblindness in which only two of the three fundamental colors can be distinguished due to a lack of one of the retinal cone pigments.” synonym definition
- 9. 9 Genotype Phenotype Sequence Proteins Gene products Transcript Pathways Cell type BRENDA tissue / enzyme source Development Anatomy Phenotype Plasmodium life cycle -Sequence types and features -Genetic Context - Molecule role - Molecular Function - Biological process - Cellular component -Protein covalent bond -Protein domain -UniProt taxonomy -Pathway ontology -Event (INOH pathway ontology) -Systems Biology -Protein-protein interaction -Arabidopsis development -Cereal plant development -Plant growth and developmental stage -C. elegans development -Drosophila development FBdv fly development.obo OBO yes yes -Human developmental anatomy, abstract version -Human developmental anatomy, timed version -Mosquito gross anatomy -Mouse adult gross anatomy -Mouse gross anatomy and development -C. elegans gross anatomy -Arabidopsis gross anatomy -Cereal plant gross anatomy -Drosophila gross anatomy -Dictyostelium discoideum anatomy -Fungal gross anatomy FAO -Plant structure -Maize gross anatomy -Medaka fish anatomy and development -Zebrafish anatomy and development -NCI Thesaurus -Mouse pathology -Human disease -Cereal plant trait -PATO PATO attribute and value.obo -Mammalian phenotype - Human phenotype -Habronattus courtship -Loggerhead nesting -Animal natural history and life history eVOC (Expressed Sequence Annotation for Humans) Ontologies for life sciences
- 10. Ontology Lookup Service • Ontology search engine (Solr) • Graph database of terms (Neo4j) • Powerful RESTful API (Built with Spring data neo4j / rest) • Open source project • Generic infrastructure (can load any ontology represented in OWL) https://github.com/EBISPOT/OLS Repository of over 140 biomedical ontologies (4.5 million terms, 11 million relations) http://www.ebi.ac.uk/ols/beta
- 11. Web Ontology Language – (OWL) • W3C standard vocabulary for describing ontologies • Powerful knowledge representation However • OWL ontologies aren’t graphs, but… … can be represented as an RDF graph … people want to use them as graphs • Plenty of RDF databases around • But incomplete w.r.t. OWL semantics • SPARQL is an acquired taste
- 12. OWL to Neo4j schema • Each node label one of {Class, Property, Individuals} AND {Ontology name} • All OWL annotations become properties (labels, id, descriptions etc) • Superclass of (named and simple existentials) become edges in Neo4j • E.g. In OWL “heart” subclassOf (part-of some “cardiovascular system”) In Neo4j “heart” part-of “cardiovascular system”
- 13. What are the sub types of “colorblindess”? MATCH (n:Class {obo_id: 'HP:0007641'})<-[r*]-(types:Class) RETURN n, r, types
- 14. What parts of the eye are related to diseases?MATCH (eye:Class {obo_id: 'UBERON:0000970'})<-[r:Related {label : "part_of"}]-(eye_part:Class)<-[r1:Related {label : "has_disease_location"}]-(disease:Class) RETURN eye, r,r1, eye_part, disease
- 15. Finding common ancestors via shortest path Match p=shortestPath( (a:Class)-[r:SUBCLASSOF*]-(b:Class) ) Return nodes(p) What is the common taxonomic superfamily of Gibbons and Chimpanzees? (or Hylobatidae and Pan troglodytes!) https://commons.wikimedia.org/wiki/File:Hylobates_lar_pair_of_white_and_black_01.jpg
- 16. OLS visualisations • Partonomy for heart from the UBERON anatomy ontology MATCH path = (n:Class)-[r:SUBCLASSOF|PartOf*]->(ancestor)
- 17. REST API (Spring Data REST + Neo4j) • Crawlable API - Hypermedia drivel (HAL) • Get ontology and term meta data • /ontologies • /ontologies/{name} • /ontologies/{name}/terms • /ontologies/{name}/terms/{termid} • Get related terms and navigate ontology structure • /ontologies/{name}/terms/{termid}/parent • /ontologies/{name}/terms/{termid}/children • /ontologies/{name}/terms/{termid}/descendants • /ontologies/{name}/terms/{termid}/ancestors • /ontologies/{name}/terms/{termid}/{relation} e.g. part_of http://www.ebi.ac.uk/ols/beta/api
- 18. Building the index • We check all 140 external ontology files nightly for changes • We have a master build index • When ontology updates we remove the old version and reload using the Neo4j BatchInserter (Potentially fragile) • We push master index to various production data centers • Provides load balancing Nightly crawl of all >140 registered ontologies
- 19. Conclusion • We’ve built a scalable repository of biomedical ontologies with Neo4j • Generic OWL indexer (simplified OWL) • Powerful REST API built with Spring • Acts as standalone OWL ontology server • Now being deployed externally • Beta ~2000 users / 10 Million requests per month • Would like to discuss • Batch Inserter • Migrating to Spring Data Neo4j 4
- 20. Acknowledgements • Sample Phenotypes and Ontologies Team - Tony Burdett, James Malone, Dani Welter, Catherine Leroy, Sira Sarntivijai, Ilinca Tudose, Helen Parkinson • Matt Pearce – Flax (BioSOLR project) • Michal Bachman and GraphAware team (Neo4j training) • Funding • European Molecular Biology Laboratory (EMBL) • European Union projects: DIACHRON, BioMedBridges and CORBEL