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Genomic GPS: using genetic distance from individuals to public data for genomic analysis without disclosing personal genomes

DC Field Value Language
dc.contributor.authorKim, Kunhee-
dc.contributor.authorBaik, Hyungryul-
dc.contributor.authorJang, Chloe Soohyun-
dc.contributor.authorRoh, Jin Kyung-
dc.contributor.authorEskin, Eleazer-
dc.contributor.authorHan, Buhm-
dc.date.accessioned2023-04-25T07:31:34Z-
dc.date.available2023-04-25T07:31:34Z-
dc.date.created2020-02-03-
dc.date.created2020-02-03-
dc.date.issued2019-08-27-
dc.identifier.citationGenome Biology, Vol.20 No.1, p. 175-
dc.identifier.issn1474-760X-
dc.identifier.urihttps://hdl.handle.net/10371/191500-
dc.description.abstractGenomic global positioning system (GPS) applies the multilateration technique commonly used in the GPS to genomic data. In the framework we present here, investigators calculate genetic distances from their samples to reference samples, which are from data held in the public domain, and share this information with others. This sharing enables certain types of genomic analysis, such as identifying sample overlaps and close relatives, decomposing ancestry, and mapping of geographical origin without disclosing personal genomes. Thus, our method can be seen as a balance between open data sharing and privacy protection.-
dc.language영어-
dc.publisherBIOMED CENTRAL LTD-
dc.titleGenomic GPS: using genetic distance from individuals to public data for genomic analysis without disclosing personal genomes-
dc.typeArticle-
dc.identifier.doi10.1186/s13059-019-1792-2-
dc.citation.journaltitleGenome Biology-
dc.identifier.wosid000482896200001-
dc.identifier.scopusid2-s2.0-85071613047-
dc.citation.number1-
dc.citation.startpage175-
dc.citation.volume20-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorHan, Buhm-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordAuthorMultilateration-
dc.subject.keywordAuthorGenetic distance-
dc.subject.keywordAuthorPersonal genome-
dc.subject.keywordAuthorData sharing-
dc.subject.keywordAuthorPrivacy protection-
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  • College of Medicine
  • Department of Medicine
Research Area Bioinformatics, Genomics, Statistical Genetics

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