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Semantic Variation Graphs: Ontologies for Pangenome Graphs

Yokoyama, Toshiyuki T.; Heumos, Simon; Seaman, Josiah; Trybushnyi, Dmytro; Pook, Torsten; Guarracino, Andrea; Garrison, Erik; Bolleman, Jerven T.

Abstract:
Background: Variation graphs are a novel way to describe genomic variation across a population. Variation graph tools present a significant improvement in mitigating reference bias compared to the linear reference ecosystem. Existing toolkits focus on algorithms processing pangenome graphs. Yet, they have limited capabilities in integrating various annotations of the biology and providing an interface for large scale visualizations.
Description: To interpret biological meaning in variation graphs by integrating various kinds of annotations for further analysis, FAIR data interchange formats are demanded. Borderless technology such as the Semantic Web allows variation graph toolkits and pangenome tools to focus on their core competence while allowing bioinformaticians to integrate, analyze, and visualize the data.
Result: We demonstrate how we can represent a graphical pangenome with pangenome ontologies using a standard declarative graph query language. Then we show how the vg RDF and Pantograph RDF can represent data ready for the Semantic Web and how we can combine existing data from INDSC and UniProt without conversions or loss of information into a single Variation and Knowledge Graph.



Zugehörige Institution(en) am KIT Institut für Thermische Energietechnik und Sicherheit (ITES)
Publikationstyp Poster
Publikationsdatum 15.07.2020
Sprache Englisch
Identifikator KITopen-ID: 1000127608
Veranstaltung International Conference on Intelligent Systems for Molecular Biology (2020), Online, 13.07.2020 – 16.07.2020
Bemerkung zur Veröffentlichung Die Veranstaltung fand wegen der Corona-Pandemie als Online-Event statt.
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