Data Driven Innovation - Interoperable Genebanks (Tech Track Session)
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The document outlines a workshop focused on 'interoperable genetic diversity' and the concept of 'bring your own data' (BYOD) held on March 18-19, 2015, in Wageningen. It discusses the importance of integrating genomics data from various sources, the need for interoperability, and how newly published information can be automatically included in data inquiries. The outcome emphasizes a collaborative approach among genebanks, genomics providers, and data experts to facilitate effective data management and accessibility.
Data Driven Innovation - Interoperable Genebanks (Tech Track Session)
- 1. Data Driven Innovation Interoperability Tech Track (#agridata) 18 & 19 March 2015, Wageningen (@rfinkers)
- 2. Outline Introduction “Interoperable Genetic Diversity” Concept ”Bring Your Own Data” party Aim BYOD Green Genetics? Outcome BYOD Green Genetics Hands on 2
- 4. Climate change & Social disruption 4Photograph: AFP/Getty Images http://www.theguardian.com/commentisfree/2015/mar/08/guardian-view-climate-change-social-disruption#img-1
- 6. Select a genetically diverse collection 6 Legacy databases (e.g. Uniprot) Genome Sequence & Genome Annotation Genome Variation Data (re- sequencing collections) & SNP annotation Accession Passport Information Accession Phenotype Information
- 7. Web based aggregation of Information 7
- 8. Interoperable Genetic Diversity Genebanks should utilize genomics data ● But should not store them! Genomics studies should make variant data available ● But need access to passport and characterization & evaluation data. Breeders needs tools to access diversity Finkers, van Hintum et al. 2014 DOI: 10.1017/S1479262114000689 Genebank (s) Genomics provider(s)
- 9. Intermezzo: Linked Open Data Standardization makes the information interoperable • Controlled vocabularies • Machine readable • Can all be queried by a single question vs. visiting many websites
- 10. Interoperable Genetic Diversity (2) Implications: ● Data can be stored at many different locations, but can be found by computers ● Newly published information (in the correct format) will be included automatically. ● Tools can be written to dedicated questions, such as assessing allelic variation or utilize for collection management Finkers, van Hintum et al. 2014 DOI: 10.1017/S1479262114000689 Genebank (s) Genomics provider(s)
- 12. Interdisciplinary Approach Needed Need for Data Scientists & Domain Experts 12 Genebanks Genomics provider(s)
- 13. Format: Bring your own Data Workshop 1. Users define the question(s) 2. Users and Linked data experts define concepts and ontologies 3. Experts help to create linked data and formulate query
- 14. Bring Your Own Data Workshop More Info: http://www.dtls.nl/fair-data/byod/ 14 Data owners Domain Experts Trainers Linked Data Experts
- 15. Example: Solanaceae Trait Ontology
- 16. BYOD in action
- 17. Select a genetically diverse collection 17 Legacy databases (e.g. Uniprot) Genome Sequence & Genome Annotation Genome Variation Data (re- sequencing collections) & SNP annotation Accession Passport Information Accession Phenotype Information
- 18. Example Query 18 PREFIX rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> PREFIX taxon: <http://openlifedata.org/taxonomy_resource:> PREFIX tdwg: <http://rs.tdwg.org/dwc/terms/> SELECT ?acc ?label (str(?lat) as ?latitude) (str(?long) as ?longitude) GRAPH <http://cgngenis.wageningenur.nl> { ?acc taxon:species ?species . ?species rdfs:label ?label . ?acc tdwg:decimalLatitude ?lat . ?acc tdwg:decimalLongitude ?long } } order by ?label
- 20. FAIRport* in VLPB? *More on FAIRport in the presentation of Luiz Bonino, Thursday 10:30
- 21. Summary Blueprint “Interoperable Genetic Diversity Shown” BYOD resulted in interoperable data which could be queried ● Request your own BYOD? Public <-> Private integration possible
- 22. Select a genetically diverse collection 22 Legacy databases (e.g. Uniprot) Genome Sequence & Genome Annotation Genome Variation Data (re- sequencing collections) & SNP annotation Accession Passport Information Accession Phenotype Information
- 23. Select a genetically diverse collection 23 Legacy databases (e.g. Uniprot) Genome Sequence & Genome Annotation Genome Variation Data (re- sequencing collections) & SNP annotation Accession Passport Information Accession Phenotype Information
- 25. Questions? Acknowledgements: BYOD team Theo van Hinthum & Frank Menting (CGN) Denis Guryunov & Martijn van Kaauwen (prototype) et. all.
- 26. HaploSmasher Hands On Session HaploSmasher Prototype: ● genomic regions as input: SL2.40ch03:10000..10200 ● Solyc gene identifiers: Solyc10g085020 ● Filter SNPs on impact type ● HIGH, MODERATE, LOW, MODIFIER (SNPEff ) ● No input validation yet ● Use correct notation, existing Solyc gene ID’s
- 27. HaploSmasher
- 28. HaploSmasher Query CGN FAIRdata graph ● Prototype is only generating links to CGN passport data now ● Graph data of three CGN accessions is available in our testset
- 29. HaploSmasher examples: Haplotype Output
- 30. Example queries http://www.plantbreeding.wur.nl/hs/ Also, explore variation data & Linked resources ● http://www.tomatogenome.net Examples: ● Beta-tubulin: Solyc10g085020 ● HIGH & MODERATE vs. ALL effects ● Glutamate dehydrogenase Solyc05g052100 ● Uridine kinase Solyc02g067880 ● magnesium chelatase Solyc04g015750 30
- 31. HaploSmasher examples: Conserved housekeeping genes: ● Beta-tubulin Solyc10g085020 439 AA ● 1 SNP (HIGH & MODERATE effect) , two haplotypes
- 32. HaploSmasher examples: ● Beta-tubulin Solyc10g085020 439 AA ● 136 SNPs (all SNPEff impact types) ● Part of haplotype groups:
- 33. HaploSmasher examples: ● Glutamate dehydrogenase Solyc05g052100 ● 13 SNPs (HIGH, MODERATE)
- 34. HaploSmasher examples: ● Uridine kinase Solyc02g067880 ● 23 SNPs (HIGH, MODERATE) ● Example haplotype groups:
- 35. HaploSmasher examples: ● magnesium chelatase Solyc04g015750 ● 21 SNPs (HIGH, MODERATE) ● Example haplotype groups:
Editor's Notes
- #19: Query is difficult, but goal is to explain that we use “standardized terms” and that these resolve to actual (human readable) sites, with blocks of information which can be re-used
- #20: Example to show connectivity.
- #21: Emphasis on the fact that there is a distinction between public and private data. But, if agreed upon, data can be shared between companies.
- #23: Add Gift Wrapping
- #24: Add Gift Wrapping