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

Genome‐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) polymorphis...

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Autores principales: Vince, Nicolas, Douillard, Venceslas, Geffard, Estelle, Meyer, Diogo, Castelli, Erick C., Mack, Steven J., Limou, Sophie, Gourraud, Pierre‐Antoine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540691/
https://www.ncbi.nlm.nih.gov/pubmed/32681667
http://dx.doi.org/10.1002/gepi.22334
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author Vince, Nicolas
Douillard, Venceslas
Geffard, Estelle
Meyer, Diogo
Castelli, Erick C.
Mack, Steven J.
Limou, Sophie
Gourraud, Pierre‐Antoine
author_facet Vince, Nicolas
Douillard, Venceslas
Geffard, Estelle
Meyer, Diogo
Castelli, Erick C.
Mack, Steven J.
Limou, Sophie
Gourraud, Pierre‐Antoine
author_sort Vince, Nicolas
collection PubMed
description Genome‐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.
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spelling pubmed-75406912020-10-15 SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics Vince, Nicolas Douillard, Venceslas Geffard, Estelle Meyer, Diogo Castelli, Erick C. Mack, Steven J. Limou, Sophie Gourraud, Pierre‐Antoine Genet Epidemiol Research Articles Genome‐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. John Wiley and Sons Inc. 2020-07-18 2020-10 /pmc/articles/PMC7540691/ /pubmed/32681667 http://dx.doi.org/10.1002/gepi.22334 Text en © 2020 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Vince, Nicolas
Douillard, Venceslas
Geffard, Estelle
Meyer, Diogo
Castelli, Erick C.
Mack, Steven J.
Limou, Sophie
Gourraud, Pierre‐Antoine
SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics
title SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics
title_full SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics
title_fullStr SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics
title_full_unstemmed SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics
title_short SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics
title_sort snp‐hla reference consortium (shlarc): hla and snp data sharing for promoting mhc‐centric analyses in genomics
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540691/
https://www.ncbi.nlm.nih.gov/pubmed/32681667
http://dx.doi.org/10.1002/gepi.22334
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