2013
DOI: 10.1007/s00439-013-1358-4
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The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine

Abstract: The Human Gene Mutation Database (HGMD®) is a comprehensive collection of germline mutations in nuclear genes that underlie, or are associated with, human inherited disease. By June 2013, the database contained over 141,000 different lesions detected in over 5,700 different genes, with new mutation entries currently accumulating at a rate exceeding 10,000 per annum. HGMD was originally established in 1996 for the scientific study of mutational mechanisms in human genes. However, it has since acquired a much br… Show more

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Cited by 1,181 publications
(1,108 citation statements)
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“…Variant information was gathered from population databases (Exome Aggregation Consortium 14 , Exome Variant server 15 , 1000 Genomes 16 , dbSNP 17 and dbVAR 18 ), disease databases (humsavar.txt release 2016_05 19 , ClinVar 20 , HGMD-public 21 , OMIM 22 and OMIA 23 ) and sequence databases (RefSeqGene 24 , NCBI Genome 25 , UCSC Genome 26 and Ensembl Genome 27 ). I-Mutant2.0 28 was used as a predictor of protein stability changes upon variations.…”
Section: Bioinformatics Tools For Sequence Variant Interpretationmentioning
confidence: 99%
“…Variant information was gathered from population databases (Exome Aggregation Consortium 14 , Exome Variant server 15 , 1000 Genomes 16 , dbSNP 17 and dbVAR 18 ), disease databases (humsavar.txt release 2016_05 19 , ClinVar 20 , HGMD-public 21 , OMIM 22 and OMIA 23 ) and sequence databases (RefSeqGene 24 , NCBI Genome 25 , UCSC Genome 26 and Ensembl Genome 27 ). I-Mutant2.0 28 was used as a predictor of protein stability changes upon variations.…”
Section: Bioinformatics Tools For Sequence Variant Interpretationmentioning
confidence: 99%
“…20 This set of disease-causing variants is representative of data sets that have typically been employed in the training and evaluation of a number of different bioinformatic prediction tools to identify disease-causing AAS. In order to allow an unbiased evaluation of bioinformatic prediction tools, an unseen test set (not used for training) should always be used, otherwise the evaluation represents in-sample error rather than out-of-sample error and hence is likely to be overly optimistic in terms of prediction performance.…”
Section: Dm Setmentioning
confidence: 99%
“…In addition to the primary phenotypic categorization, all other symptoms were noted by selecting any applicable lowerlevel Human Phenotype Ontology terms and Human Gene Mutation Database (HGMD) disease terms. 12,13 Genomic DNA was extracted from whole blood obtained from the affected individual and any submitted family members. Clinicians were encouraged to provide blood or DNA specimens for both parents and all available affected family members whenever possible.…”
Section: Introductionmentioning
confidence: 99%