scholarly journals The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting

2020 ◽  
Vol 139 (10) ◽  
pp. 1197-1207 ◽  
Author(s):  
Peter D. Stenson ◽  
Matthew Mort ◽  
Edward V. Ball ◽  
Molly Chapman ◽  
Katy Evans ◽  
...  

Abstract The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that are thought to underlie, or are closely associated with human inherited disease. At the time of writing (June 2020), the database contains in excess of 289,000 different gene lesions identified in over 11,100 genes manually curated from 72,987 articles published in over 3100 peer-reviewed journals. There are primarily two main groups of users who utilise HGMD on a regular basis; research scientists and clinical diagnosticians. This review aims to highlight how to make the most out of HGMD data in each setting.

2006 ◽  
pp. 99-104 ◽  
Author(s):  
Michael Krawczak ◽  
Edward V. Ball ◽  
Peter Stenson ◽  
David N. Cooper

2019 ◽  
Vol 64 (11) ◽  
pp. 1091-1095 ◽  
Author(s):  
Hui-Qi Qu ◽  
Xiang Wang ◽  
Lifeng Tian ◽  
Hakon Hakonarson

10.1186/gm13 ◽  
2009 ◽  
Vol 1 (1) ◽  
pp. 13 ◽  
Author(s):  
Peter D Stenson ◽  
Matthew Mort ◽  
Edward V Ball ◽  
Katy Howells ◽  
Andrew D Phillips ◽  
...  

2020 ◽  
Author(s):  
Kyoung-Jin Park ◽  
Woochang Lee ◽  
Sail Chun ◽  
Won-Ki Min

Abstract Objective Discordant variant classifications among public databases is one of the well-documented limitations when interpreting the pathogenicity of variants. The aim of this study is to investigate the level of germline variant misannotation from the Human Gene Mutation Database (HGMD) and the annotation concordance between databases. Methods We used a total of 188,106 classified variants (disease-causing mutations [n = 179,454] and polymorphisms [n = 8652]) in 6466 genes from the HGMD. All variants were reanalyzed based on the American College of Medical Genetics and Genomics (ACMG) guidelines and compared to ClinVar database variants. Results When variants were classified based on the ACMG guidelines, misclassification was observed in 3.47% (2289/65,896) of variants. The overall concordance between HGMD and ClinVar was 97.62% (52,499/53,780) of variants studied. Conclusion Variants in databases must be used with caution when variant pathogenicity is interpreted. This study reveals the frequency of misannotation of the HGMD variants and annotation concordance between databases in depth.


2003 ◽  
Vol 21 (6) ◽  
pp. 577-581 ◽  
Author(s):  
Peter D. Stenson ◽  
Edward V. Ball ◽  
Matthew Mort ◽  
Andrew D. Phillips ◽  
Jacqueline A. Shiel ◽  
...  

1996 ◽  
Vol 98 (5) ◽  
pp. 629-629 ◽  
Author(s):  
D. N. Cooper ◽  
Michael Krawczak

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