Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis

Detalhes bibliográficos
Autor(a) principal: Borges,Murilo G.
Data de Publicação: 2020
Outros Autores: Rocha,Cristiane S., Carvalho,Benilton S., Lopes-Cendes,Iscia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Genetics and Molecular Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572020000400804
Resumo: Abstract For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.
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spelling Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosisWhole exome sequencingdepthClinVarcomputational biologyclinical genomicsAbstract For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.Sociedade Brasileira de Genética2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572020000400804Genetics and Molecular Biology v.43 n.2 2020reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/1678-4685-gmb-2019-0270info:eu-repo/semantics/openAccessBorges,Murilo G.Rocha,Cristiane S.Carvalho,Benilton S.Lopes-Cendes,Isciaeng2020-04-27T00:00:00Zoai:scielo:S1415-47572020000400804Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2020-04-27T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false
dc.title.none.fl_str_mv Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
title Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
spellingShingle Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
Borges,Murilo G.
Whole exome sequencing
depth
ClinVar
computational biology
clinical genomics
title_short Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
title_full Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
title_fullStr Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
title_full_unstemmed Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
title_sort Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis
author Borges,Murilo G.
author_facet Borges,Murilo G.
Rocha,Cristiane S.
Carvalho,Benilton S.
Lopes-Cendes,Iscia
author_role author
author2 Rocha,Cristiane S.
Carvalho,Benilton S.
Lopes-Cendes,Iscia
author2_role author
author
author
dc.contributor.author.fl_str_mv Borges,Murilo G.
Rocha,Cristiane S.
Carvalho,Benilton S.
Lopes-Cendes,Iscia
dc.subject.por.fl_str_mv Whole exome sequencing
depth
ClinVar
computational biology
clinical genomics
topic Whole exome sequencing
depth
ClinVar
computational biology
clinical genomics
description Abstract For a better interpretation of variants, evidence-based databases, such as ClinVar, compile data on the presumed relationships between variants and phenotypes. In this study, we aimed to analyze the pattern of sequencing depth in variants from whole-exome sequencing data in the 1000 Genomes project phase 3, focusing on the variants present in the ClinVar database that were predicted to affect protein-coding regions. We demonstrate that the distribution of the sequencing depth varies across different sequencing centers (pair-wise comparison, p < 0.001). Most importantly, we found that the distribution pattern of sequencing depth is specific to each facility, making it possible to correctly assign 96.9% of the samples to their sequencing center. Thus, indicating the presence of a systematic bias, related to the methods used in the different facilities, which generates significant variations in breadth and depth in whole-exome sequencing data in clinically relevant regions. Our results show that methodological differences, leading to significant heterogeneity in sequencing depth, may potentially influence the accuracy of genetic diagnosis. Furthermore, our findings highlight how it is still challenging to integrate results from different sequencing centers, which may also have an impact on genomic research.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572020000400804
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-4685-gmb-2019-0270
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dc.publisher.none.fl_str_mv Sociedade Brasileira de Genética
publisher.none.fl_str_mv Sociedade Brasileira de Genética
dc.source.none.fl_str_mv Genetics and Molecular Biology v.43 n.2 2020
reponame:Genetics and Molecular Biology
instname:Sociedade Brasileira de Genética (SBG)
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instname_str Sociedade Brasileira de Genética (SBG)
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reponame_str Genetics and Molecular Biology
collection Genetics and Molecular Biology
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