Exploring neXtProt data and beyond: A SPARQLing solution
- 1. www.sib.swiss Exploring neXtProt data and beyond: A SPARQLing solution Biocuration 2019, Cambridge, UK Monique Zahn
- 2. Overview Exploring neXtProt data using SPARQL Biocuration and quality control Summary and future perspectives Introduction01 02 03 04
- 3. neXtProt – the SIB knowledgebase on human proteins https://www.nextprot.org/
- 5. A resource • ENTRIES have a globally unique and persistent ID • Use controlled vocabularies and ontologies • SPARQL end-point • Detailed provenance • Data license CC BY 4.0 • All data since 2011 on FTP • Code on GitHub • Web: human readable • API: machine parsable • FTP: XML, PEFF, RDF/ttl FINDABLE ACCESSIBLE INTEROPERABLE REUSABLE
- 6. Overview Exploring neXtProt data using SPARQL Biocuration and quality control Summary and future perspectives Introduction01 02 03 04
- 7. neXtProt Advanced Search Complex queries to retrieve entries matching criteria i.e. queries that cannot be performed using the simple search
- 8. Advanced Search results NXQ_00022 Proteins with no function annotated
- 9. neXtProt SNORQL Search Queries to retrieve entries and other information matching criteria
- 10. SNORQL Search results NXQ_00125 Domains that are entirely covered by 3D structures
- 11. Data visualization Use javascript to see SPARQL query results using Highcharts.com SPARQL query Retrieve results Plot results
- 12. Visualizing SPARQL query results Automatically updated at each data release
- 13. Overview Exploring neXtProt data using SPARQL Biocuration and quality control Summary and future perspectives Introduction01 02 03 04
- 14. SPARQL for biocuration Routine maintenance Updating controlled vocabularies Finding potential annotation targets NXQ_00022 Proteins with no function annotated NXQ_00125 Domains that are NOT entirely covered by 3D structures Tracking progress Number of entries with a GO molecular function Number of GO molecular function terms annotated
- 15. Updating controlled vocabularies SPARQL query to find protein domains relevant to no entry returns domains to be deleted
- 16. SPARQL for quality control Examples for spot checks Entry with the most isoforms (CACNA1C NX_Q13936 37 isoforms) Entry with the most variants (TTN NX_Q8WZ42 24,240 variants) Global checks Find data which is: • missing • incorrect • incomplete
- 17. Automated quality control (1)
- 18. Automated quality control (2) SPARQL queries must return 0 (rows) if there is no error Execute a batch of queries either on the test or production server There are 4 protein domains with no associated entry to be deleted.
- 19. Automated quality control (3) There are 10 sequence conflict annotations for which the quality has been incorrectly assigned.
- 20. Overview Exploring neXtProt data using SPARQL Biocuration and quality control Summary and future perspectives Introduction01 02 03 04
- 21. Summary and future perspectives Exploration Execute complex queries Query several database endpoints (federated queries) Biocuration Quality control User guide to using SPARQL in neXtProt Dashboard Visual detection of anomalies
- 22. Acknowledgements neXtProt Directors Amos Bairoch, Lydie Lane Biocurators Pascale Gaudet, Paula Duek Developers Pierre-André Michel, Alain Gateau, Frédéric Nikitin Researcher Mathieu Schaeffer (poster 80), Kasun Samarasinghe Quality assurance Monique Zahn (poster 92) Web: https://www.nextprot.org/ Twitter: @neXtProt_news ResearchGate: neXtProt project Photograph taken by Chris James