AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data

Bibliographic Details
Main Author: Quinodoz, Mathieu
Publication Date: 2021
Other Authors: Peter, Virginie G, Bedoni, Nicola, Royer Bertrand, Béryl, Cisarova, Katarina, Salmaninejad, Arash, Sepahi, Neda, Rodrigues, Raquel, Piran, Mehran, Mojarrad, Majid, Pasdar, Alireza, Ghanbari Asad, Ali, Sousa, Ana Berta, Santos, Maria Luisa, Superti-Furga, Andrea, Rivolta, Carlo
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10451/46213
Summary: © The Author(s) 2021. Open AccessThis article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made. The images or other third partymaterial in this article are included in the article’s Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is not included in thearticle’s Creative Commons license and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directly fromthe copyright holder. To view a copy of this license, visithttp://creativecommons.org/licenses/by/4.0/.
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spelling AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data© The Author(s) 2021. Open AccessThis article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made. The images or other third partymaterial in this article are included in the article’s Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is not included in thearticle’s Creative Commons license and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directly fromthe copyright holder. To view a copy of this license, visithttp://creativecommons.org/licenses/by/4.0/.Homozygosity mapping is a powerful method for identifying mutations in patients with recessive conditions, especially in consanguineous families or isolated populations. Historically, it has been used in conjunction with genotypes from highly polymorphic markers, such as DNA microsatellites or common SNPs. Traditional software performs rather poorly with data from Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS), which are now extensively used in medical genetics. We develop AutoMap, a tool that is both web-based or downloadable, to allow performing homozygosity mapping directly on VCF (Variant Call Format) calls from WES or WGS projects. Following a training step on WES data from 26 consanguineous families and a validation procedure on a matched cohort, our method shows higher overall performances when compared with eight existing tools. Most importantly, when tested on real cases with negative molecular diagnosis from an internal set, AutoMap detects three gene-disease and multiple variant-disease associations that were previously unrecognized, projecting clear benefits for both molecular diagnosis and research activities in medical genetics.Springer NatureRepositório da Universidade de LisboaQuinodoz, MathieuPeter, Virginie GBedoni, NicolaRoyer Bertrand, BérylCisarova, KatarinaSalmaninejad, ArashSepahi, NedaRodrigues, RaquelPiran, MehranMojarrad, MajidPasdar, AlirezaGhanbari Asad, AliSousa, Ana BertaSantos, Maria LuisaSuperti-Furga, AndreaRivolta, Carlo2021-02-05T17:34:03Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/46213engNat Commun. 2021 Jan 22;12(1):51810.1038/s41467-020-20584-42041-1723info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T14:28:09Zoai:repositorio.ulisboa.pt:10451/46213Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:12:47.046281Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
title AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
spellingShingle AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
Quinodoz, Mathieu
title_short AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
title_full AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
title_fullStr AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
title_full_unstemmed AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
title_sort AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data
author Quinodoz, Mathieu
author_facet Quinodoz, Mathieu
Peter, Virginie G
Bedoni, Nicola
Royer Bertrand, Béryl
Cisarova, Katarina
Salmaninejad, Arash
Sepahi, Neda
Rodrigues, Raquel
Piran, Mehran
Mojarrad, Majid
Pasdar, Alireza
Ghanbari Asad, Ali
Sousa, Ana Berta
Santos, Maria Luisa
Superti-Furga, Andrea
Rivolta, Carlo
author_role author
author2 Peter, Virginie G
Bedoni, Nicola
Royer Bertrand, Béryl
Cisarova, Katarina
Salmaninejad, Arash
Sepahi, Neda
Rodrigues, Raquel
Piran, Mehran
Mojarrad, Majid
Pasdar, Alireza
Ghanbari Asad, Ali
Sousa, Ana Berta
Santos, Maria Luisa
Superti-Furga, Andrea
Rivolta, Carlo
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Quinodoz, Mathieu
Peter, Virginie G
Bedoni, Nicola
Royer Bertrand, Béryl
Cisarova, Katarina
Salmaninejad, Arash
Sepahi, Neda
Rodrigues, Raquel
Piran, Mehran
Mojarrad, Majid
Pasdar, Alireza
Ghanbari Asad, Ali
Sousa, Ana Berta
Santos, Maria Luisa
Superti-Furga, Andrea
Rivolta, Carlo
description © The Author(s) 2021. Open AccessThis article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made. The images or other third partymaterial in this article are included in the article’s Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is not included in thearticle’s Creative Commons license and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directly fromthe copyright holder. To view a copy of this license, visithttp://creativecommons.org/licenses/by/4.0/.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-05T17:34:03Z
2021
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dc.relation.none.fl_str_mv Nat Commun. 2021 Jan 22;12(1):518
10.1038/s41467-020-20584-4
2041-1723
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