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Journal article

Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy

Abstract:

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 (BIN-test) combined with burden information (ClusterBurden). We in...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1136/jmedgenet-2020-106922

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
Doctoral Training Centre - MSD
Role:
Author
ORCID:
0000-0002-3590-2560
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Doctoral Training Centre - MSD
Role:
Author
ORCID:
0000-0001-5327-0328
More by this author
Role:
Author
ORCID:
0000-0003-2057-7731
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
RDM
Sub department:
RDM Cardiovascular Medicine
Role:
Author
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Publisher:
BMJ Publishing Group Publisher's website
Journal:
Journal of Medical Genetics Journal website
Volume:
58
Issue:
8
Pages:
556-564
Publication date:
2020-07-30
Acceptance date:
2020-06-20
DOI:
EISSN:
1468-6244
ISSN:
0022-2593
Language:
English
Keywords:
Pubs id:
1069962
Local pid:
pubs:1069962
Deposit date:
2020-03-18

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