Semantically enabling a genome-wide association study database

Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central – a free and open access resource for the advanced querying and compari...

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Vydáno v:	Journal of biomedical semantics Ročník 3; číslo 1; s. 9
Hlavní autoři:	Beck, Tim, Free, Robert C, Thorisson, Gudmundur A, Brookes, Anthony J
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 17.12.2012 Springer Nature B.V BMC
Témata:	Abnormalities Algorithms Annotations Automation Biocompatibility Bioinformatics Blood pressure Combinatorial Libraries Computational Biology/Bioinformatics Computer Appl. in Life Sciences Data Mining and Knowledge Discovery Disease Genome-wide association studies Genomes Genotype & phenotype Genotypes GWAS Integration Linked Data Mathematics Mathematics and Statistics Medical Subject Headings-MeSH Ontology Phenotype Phenotypes Principles RDF Resource Description Framework-RDF Semantic technologies in healthcare and life sciences 2012 Semantic web Semantics Signs and symptoms Species Studies Terminology Phenotype GWAS Ontology RDF
ISSN:	2041-1480, 2041-1480
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Abstract	Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central – a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data. Results A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications. Conclusions We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web.
AbstractList	Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central – a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data. Results A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications. Conclusions We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web. The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central - a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data.BACKGROUNDThe amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central - a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data.A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications.RESULTSA pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications.We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web.CONCLUSIONSWe present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web. Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central – a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data. Results A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications. Conclusions We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web. The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central - a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data. A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications. We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web. Abstract Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange have not kept pace. This impacts on the work of GWAS Central – a free and open access resource for the advanced querying and comparison of summary-level genetic association data. The benefits of employing ontologies for standardising and structuring data are widely accepted. The complex spectrum of observed human phenotypes (and traits), and the requirement for cross-species phenotype comparisons, calls for reflection on the most appropriate solution for the organisation of human phenotype data. The Semantic Web provides standards for the possibility of further integration of GWAS data and the ability to contribute to the web of Linked Data. Results A pragmatic consideration when applying phenotype ontologies to GWAS data is the ability to retrieve all data, at the most granular level possible, from querying a single ontology graph. We found the Medical Subject Headings (MeSH) terminology suitable for describing all traits (diseases and medical signs and symptoms) at various levels of granularity and the Human Phenotype Ontology (HPO) most suitable for describing phenotypic abnormalities (medical signs and symptoms) at the most granular level. Diseases within MeSH are mapped to HPO to infer the phenotypic abnormalities associated with diseases. Building on the rich semantic phenotype annotation layer, we are able to make cross-species phenotype comparisons and publish a core subset of GWAS data as RDF nanopublications. Conclusions We present a methodology for applying phenotype annotations to a comprehensive genome-wide association dataset and for ensuring compatibility with the Semantic Web. The annotations are used to assist with cross-species genotype and phenotype comparisons. However, further processing and deconstructions of terms may be required to facilitate automatic phenotype comparisons. The provision of GWAS nanopublications enables a new dimension for exploring GWAS data, by way of intrinsic links to related data resources within the Linked Data web. The value of such annotation and integration will grow as more biomedical resources adopt the standards of the Semantic Web.
Author	Thorisson, Gudmundur A Brookes, Anthony J Free, Robert C Beck, Tim
AuthorAffiliation	1 Department of Genetics, University of Leicester, University Road, Leicester, UK
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Cites_doi	10.1186/2041-1480-2-S2-S2 10.1093/bfgp/elm004 10.1002/humu.22079 10.1186/1471-2164-10-22 10.1038/ng.785 10.1186/gb-2012-13-1-r5 10.1073/pnas.0903103106 10.1016/j.jbi.2008.03.004 10.1186/1471-2164-11-S4-S24 10.1016/j.ajhg.2008.09.017 10.1186/1471-2164-10-S1-S6 10.2527/jas.2008-0930 10.1186/1471-2105-12-32 10.1186/2041-1480-2-8 10.2217/14622416.10.2.171 10.1186/gb-2010-11-1-r2 10.1038/75556 10.1111/j.1399-0004.2010.01436.x 10.1038/ng.361 10.1016/j.ymeth.2010.12.017 10.1038/nbt1346 10.1186/1471-2105-12-S4-S6 10.1186/1471-2105-11-S12-S12 10.1016/j.websem.2009.07.002 10.1007/s00335-009-9208-3 10.1056/NEJMp0808934 10.1186/1471-2105-13-S4-S7 10.1186/1471-2105-10-S5-S2 10.1186/2041-1480-1-S1-S7 10.1001/archneurol.2007.3 10.1093/bioinformatics/btp249
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References_xml	– ident: 10.1186/2041-1480-3-9-B15 doi: 10.1186/2041-1480-2-S2-S2 – ident: 10.1186/2041-1480-3-9-B6 doi: 10.1093/bfgp/elm004 – ident: 10.1186/2041-1480-3-9-B22 doi: 10.1002/humu.22079 – ident: 10.1186/2041-1480-3-9-B65 doi: 10.1186/1471-2164-10-22 – ident: 10.1186/2041-1480-3-9-B36 doi: 10.1038/ng.785 – ident: 10.1186/2041-1480-3-9-B25 doi: 10.1186/gb-2012-13-1-r5 – ident: 10.1186/2041-1480-3-9-B4 doi: 10.1073/pnas.0903103106 – ident: 10.1186/2041-1480-3-9-B33 doi: 10.1016/j.jbi.2008.03.004 – ident: 10.1186/2041-1480-3-9-B31 doi: 10.1186/1471-2164-11-S4-S24 – ident: 10.1186/2041-1480-3-9-B42 doi: 10.1016/j.ajhg.2008.09.017 – ident: 10.1186/2041-1480-3-9-B40 doi: 10.1186/1471-2164-10-S1-S6 – ident: 10.1186/2041-1480-3-9-B16 doi: 10.2527/jas.2008-0930 – ident: 10.1186/2041-1480-3-9-B7 doi: 10.1186/1471-2105-12-32 – ident: 10.1186/2041-1480-3-9-B29 doi: 10.1186/2041-1480-2-8 – ident: 10.1186/2041-1480-3-9-B20 doi: 10.2217/14622416.10.2.171 – ident: 10.1186/2041-1480-3-9-B26 doi: 10.1186/gb-2010-11-1-r2 – ident: 10.1186/2041-1480-3-9-B5 doi: 10.1038/75556 – ident: 10.1186/2041-1480-3-9-B11 doi: 10.1111/j.1399-0004.2010.01436.x – ident: 10.1186/2041-1480-3-9-B17 doi: 10.1038/ng.361 – ident: 10.1186/2041-1480-3-9-B50 doi: 10.1016/j.ymeth.2010.12.017 – ident: 10.1186/2041-1480-3-9-B9 doi: 10.1038/nbt1346 – ident: 10.1186/2041-1480-3-9-B32 doi: 10.1186/1471-2105-12-S4-S6 – ident: 10.1186/2041-1480-3-9-B63 doi: 10.1186/1471-2105-11-S12-S12 – ident: - doi: 10.1016/j.websem.2009.07.002 – ident: 10.1186/2041-1480-3-9-B27 doi: 10.1007/s00335-009-9208-3 – ident: 10.1186/2041-1480-3-9-B1 doi: 10.1056/NEJMp0808934 – ident: 10.1186/2041-1480-3-9-B30 doi: 10.1186/1471-2105-13-S4-S7 – ident: 10.1186/2041-1480-3-9-B8 doi: 10.1186/1471-2105-10-S5-S2 – ident: 10.1186/2041-1480-3-9-B69 doi: 10.1186/2041-1480-1-S1-S7 – ident: 10.1186/2041-1480-3-9-B19 doi: 10.1001/archneurol.2007.3 – ident: 10.1186/2041-1480-3-9-B53 doi: 10.1093/bioinformatics/btp249 – reference: 20501605 - Nucleic Acids Res. 2010 Jul;38(Web Server issue):W677-82 – reference: 11825149 - Proc AMIA Symp. 2001;:17-21 – reference: 20626927 - J Biomed Semantics. 2010;1 Suppl 1:S7 – reference: 19594883 - BMC Genomics. 2009;10 Suppl 1:S6 – reference: 17998437 - Arch Neurol. 2008 Jan;65(1):45-53 – reference: 18950739 - Am J Hum Genet. 2008 Nov;83(5):610-5 – reference: 22536974 - BMC Bioinformatics. 2012;13 Suppl 4:S7 – reference: 21261995 - BMC Bioinformatics. 2011;12:32 – reference: 18948288 - Nucleic Acids Res. 2009 Jan;37(Database issue):D797-802 – reference: 21210979 - BMC Bioinformatics. 2010;11 Suppl 12:S12 – reference: 10802651 - Nat Genet. 2000 May;25(1):25-9 – reference: 18472304 - J Biomed Inform. 2008 Oct;41(5):706-16 – reference: 19898446 - Nat Biotechnol. 2009 Nov;27(11):984-5 – reference: 20064205 - Genome Biol. 2010;11(1):R2 – reference: 18272850 - J Anim Sci. 2008 Jun;86(6):1485-91 – reference: 19376821 - Bioinformatics. 2009 Jun 1;25(11):1412-8 – reference: 19964203 - Conf Proc IEEE Eng Med Biol Soc. 2009;2009:7069-72 – reference: 21992079 - BMC Bioinformatics. 2011;12 Suppl 4:S6 – reference: 22024447 - J Biomed Semantics. 2011;2(1):8 – reference: 19649761 - Mamm Genome. 2009 Aug;20(8):457-61 – reference: 20412080 - Clin Genet. 2010 Jun;77(6):525-34 – reference: 21423179 - Nat Genet. 2011 Apr;43(4):295-301 – reference: 19910364 - Nucleic Acids Res. 2010 Jan;38(Database issue):D5-16 – reference: 20507906 - Nucleic Acids Res. 2010 Jul;38(Web Server issue):W165-74 – reference: 18842627 - Nucleic Acids Res. 2009 Jan;37(Database issue):D793-6 – reference: 20427557 - Dis Model Mech. 2010 May-Jun;3(5-6):281-9 – reference: 21624157 - J Biomed Semantics. 2011;2 Suppl 2:S2 – reference: 21051359 - Nucleic Acids Res. 2011 Jan;39(Database issue):D842-8 – reference: 19207018 - Pharmacogenomics. 2009 Feb;10(2):171-9 – reference: 21347171 - Summit on Translat Bioinforma. 2009;2009:56-60 – reference: 22139925 - Nucleic Acids Res. 2012 Jan;40(Database issue):D1047-54 – reference: 17989687 - Nat Biotechnol. 2007 Nov;25(11):1251-5 – reference: 17401136 - Brief Funct Genomic Proteomic. 2007 Mar;6(1):3-7 – reference: 21185382 - Methods. 2011 Apr;53(4):394-404 – reference: 19161620 - BMC Med Genet. 2009;10:6 – reference: 19474294 - Proc Natl Acad Sci U S A. 2009 Jun 9;106(23):9362-7 – reference: 22415892 - Hum Mutat. 2012 May;33(5):813-6 – reference: 21672956 - Nucleic Acids Res. 2011 Jul;39(Web Server issue):W541-5 – reference: 22058129 - Nucleic Acids Res. 2012 Jan;40(Database issue):D1036-40 – reference: 22293552 - Genome Biol. 2012;13(1):R5 – reference: 19369661 - N Engl J Med. 2009 Apr 23;360(17):1699-701 – reference: 18753767 - Genome Dyn. 2006;2:33-45 – reference: 19430483 - Nat Genet. 2009 Jun;41(6):666-76 – reference: 21143808 - BMC Genomics. 2010;11 Suppl 4:S24 – reference: 22118330 - Inform Prim Care. 2011;19(1):3-5 – reference: 22102590 - Nucleic Acids Res. 2012 Jan;40(Database issue):D71-5 – reference: 15642099 - Genome Biol. 2005;6(1):R7 – reference: 16845108 - Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W729-32 – reference: 19426459 - BMC Bioinformatics. 2009;10 Suppl 5:S2 – reference: 19144180 - BMC Genomics. 2009;10:22 – reference: 19933761 - Nucleic Acids Res. 2010 Jan;38(Database issue):D577-85
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Snippet	Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and... The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and interchange... Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data reuse and... Abstract Background The amount of data generated from genome-wide association studies (GWAS) has grown rapidly, but considerations for GWAS phenotype data...
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SubjectTerms	Abnormalities Algorithms Annotations Automation Biocompatibility Bioinformatics Blood pressure Combinatorial Libraries Computational Biology/Bioinformatics Computer Appl. in Life Sciences Data Mining and Knowledge Discovery Disease Genome-wide association studies Genomes Genotype & phenotype Genotypes GWAS Integration Linked Data Mathematics Mathematics and Statistics Medical Subject Headings-MeSH Ontology Phenotype Phenotypes Principles RDF Resource Description Framework-RDF Semantic technologies in healthcare and life sciences 2012 Semantic web Semantics Signs and symptoms Species Studies Terminology
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Title	Semantically enabling a genome-wide association study database
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