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SNP-HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC-centric analyses in genomics

dc.contributor.authorVince, Nicolas
dc.contributor.authorDouillard, Venceslas
dc.contributor.authorGeffard, Estelle
dc.contributor.authorMeyer, Diogo
dc.contributor.authorCastelli, Erick C. [UNESP]
dc.contributor.authorMack, Steven J.
dc.contributor.authorLimou, Sophie
dc.contributor.authorGourraud, Pierre-Antoine
dc.contributor.institutionInserm
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUCSF Benioff Children's Hospital Oakland
dc.contributor.institutionEcole Centrale de Nantes
dc.date.accessioned2020-12-12T01:31:03Z
dc.date.available2020-12-12T01:31:03Z
dc.date.issued2020-10-01
dc.description.abstractGenome-wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of associations by focusing directly on human leukocyte antigen (HLA) polymorphisms and their combination as haplotypes. To circumvent the effort and high costs of HLA typing, statistical solutions have been developed to infer HLA alleles from single-nucleotide polymorphism (SNP) genotyping data. Though HLA imputation methods have been developed, no unified effort has yet been undertaken to share large and diverse imputation models, or to improve methods. By training the HIBAG software on SNP + HLA data generated by the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) to create reference panels, we highlighted the importance of (a) the number of individuals in reference panels, with a twofold increase in accuracy (from 10 to 100 individuals) and (b) the number of SNPs, with a 1.5-fold increase in accuracy (from 500 to 24,504 SNPs). Results showed improved accuracy with CAAPA compared to the African American models available in HIBAG, highlighting the need for precise population-matching. The SNP-HLA Reference Consortium is an international endeavor to gather data, enhance HLA imputation and broaden access to highly accurate imputation models for the immunogenomics community.en
dc.description.affiliationCentre de Recherche en Transplantation et Immunologie ITUN UMR 1064 Université de Nantes CHU Nantes Inserm
dc.description.affiliationUniversity of São Paulo
dc.description.affiliationUNESP—Universidade Estadual Paulista
dc.description.affiliationDepartment of Pediatrics University of California San Francisco UCSF Benioff Children's Hospital Oakland
dc.description.affiliationEcole Centrale de Nantes
dc.description.affiliationUnespUNESP—Universidade Estadual Paulista
dc.format.extent733-740
dc.identifierhttp://dx.doi.org/10.1002/gepi.22334
dc.identifier.citationGenetic Epidemiology, v. 44, n. 7, p. 733-740, 2020.
dc.identifier.doi10.1002/gepi.22334
dc.identifier.issn1098-2272
dc.identifier.issn0741-0395
dc.identifier.scopus2-s2.0-85088090725
dc.identifier.urihttp://hdl.handle.net/11449/199112
dc.language.isoeng
dc.relation.ispartofGenetic Epidemiology
dc.sourceScopus
dc.subjectconsortium
dc.subjectHLA
dc.subjectimputation
dc.subjectSNP
dc.titleSNP-HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC-centric analyses in genomicsen
dc.typeArtigo
dspace.entity.typePublication
unesp.author.orcid0000-0002-3767-6210[1]
unesp.author.orcid0000-0002-6762-4083[2]

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