Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy.
cardiomyopathy
clinical genetics
genetics
Journal
Journal of medical genetics
ISSN: 1468-6244
Titre abrégé: J Med Genet
Pays: England
ID NLM: 2985087R
Informations de publication
Date de publication:
08 2021
08 2021
Historique:
received:
18
02
2020
revised:
17
06
2020
accepted:
20
06
2020
pubmed:
1
8
2020
medline:
16
2
2022
entrez:
1
8
2020
Statut:
ppublish
Résumé
Although rare missense variants in Mendelian disease genes often cluster in specific regions of proteins, it is unclear how to consider this when evaluating the pathogenicity of a gene or variant. Here we introduce methods for gene association and variant interpretation that use this powerful signal. We present statistical methods to detect missense variant clustering ( In simulations, the GAMs represent a unified statistical modelling framework to combine burden, clustering and functional information.
Sections du résumé
BACKGROUND
Although rare missense variants in Mendelian disease genes often cluster in specific regions of proteins, it is unclear how to consider this when evaluating the pathogenicity of a gene or variant. Here we introduce methods for gene association and variant interpretation that use this powerful signal.
METHODS
We present statistical methods to detect missense variant clustering (
RESULTS
In simulations, the
CONCLUSION
GAMs represent a unified statistical modelling framework to combine burden, clustering and functional information.
Identifiants
pubmed: 32732227
pii: jmedgenet-2020-106922
doi: 10.1136/jmedgenet-2020-106922
pmc: PMC8327322
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
556-564Subventions
Organisme : British Heart Foundation
ID : RG/12/16/29939
Pays : United Kingdom
Organisme : British Heart Foundation
ID : CH/1992001/6764
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RG/07/012/24110
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203834/Z/16/Z
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 203141/Z/16/Z
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RE/13/1/30181
Pays : United Kingdom
Organisme : NHLBI NIH HHS
ID : U01 HL117006
Pays : United States
Organisme : Wellcome Trust
Pays : United Kingdom
Informations de copyright
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.
Déclaration de conflit d'intérêts
Competing interests: None declared.
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