GFVO: the Genomic Feature and Variation Ontology

Handle URI:
http://hdl.handle.net/10754/552560
Title:
GFVO: the Genomic Feature and Variation Ontology
Authors:
Baran, Joachim; Durgahee, Bibi Sehnaaz Begum; Eilbeck, Karen; Antezana, Erick; Hoehndorf, Robert ( 0000-0001-8149-5890 ) ; Dumontier, Michel
Abstract:
Falling costs in genomic laboratory experiments have led to a steady increase of genomic feature and variation data. Multiple genomic data formats exist for sharing these data, and whilst they are similar, they are addressing slightly different data viewpoints and are consequently not fully compatible with each other. The fragmentation of data format specifications makes it hard to integrate and interpret data for further analysis with information from multiple data providers. As a solution, a new ontology is presented here for annotating and representing genomic feature and variation dataset contents. The Genomic Feature and Variation Ontology (GFVO) specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations. Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
GFVO: the Genomic Feature and Variation Ontology 2015, 3:e933 PeerJ
Journal:
PeerJ
Issue Date:
5-May-2015
DOI:
10.7717/peerj.933
PubMed ID:
26019997
PubMed Central ID:
PMC4435477
Type:
Article
ISSN:
2167-8359
Additional Links:
https://peerj.com/articles/933
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBaran, Joachimen
dc.contributor.authorDurgahee, Bibi Sehnaaz Begumen
dc.contributor.authorEilbeck, Karenen
dc.contributor.authorAntezana, Ericken
dc.contributor.authorHoehndorf, Roberten
dc.contributor.authorDumontier, Michelen
dc.date.accessioned2015-05-10T14:35:30Zen
dc.date.available2015-05-10T14:35:30Zen
dc.date.issued2015-05-05en
dc.identifier.citationGFVO: the Genomic Feature and Variation Ontology 2015, 3:e933 PeerJen
dc.identifier.issn2167-8359en
dc.identifier.pmid26019997en
dc.identifier.doi10.7717/peerj.933en
dc.identifier.urihttp://hdl.handle.net/10754/552560en
dc.description.abstractFalling costs in genomic laboratory experiments have led to a steady increase of genomic feature and variation data. Multiple genomic data formats exist for sharing these data, and whilst they are similar, they are addressing slightly different data viewpoints and are consequently not fully compatible with each other. The fragmentation of data format specifications makes it hard to integrate and interpret data for further analysis with information from multiple data providers. As a solution, a new ontology is presented here for annotating and representing genomic feature and variation dataset contents. The Genomic Feature and Variation Ontology (GFVO) specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations. Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.en
dc.relation.urlhttps://peerj.com/articles/933en
dc.rightsThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.en
dc.subjectBioinformaticsen
dc.subjectGenomicsen
dc.subjectOntologyen
dc.titleGFVO: the Genomic Feature and Variation Ontologyen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalPeerJen
dc.identifier.pmcidPMC4435477en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionStanford Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA, USAen
dc.contributor.institutionDepartment of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USAen
dc.contributor.institutionDepartment of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USAen
dc.contributor.institutionDepartment of Biology, Norwegian University of Science and Technology, Trondheim, Norwayen
dc.contributor.institutionStanford Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA, USAen
kaust.authorHoehndorf, Roberten

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