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1.
Hum Mutat. 2008 Jan;29(1):6-13.

Improving sequence variant descriptions in mutation databases and literature using the Mutalyzer sequence variation nomenclature checker.

Author information

  • 1Department of Human Genetics, Center of Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands.

Abstract

Unambiguous and correct sequence variant descriptions are of utmost importance, not in the least since mistakes and uncertainties may lead to undesired errors in clinical diagnosis. We developed the Mutation Analyzer (Mutalyzer) sequence variation nomenclature checker (www.lovd.nl/mutalyzer; last accessed 13 September 2007) for automated analysis and correction of sequence variant descriptions using reference sequences from any organism. Mutalyzer handles most variation types: substitution, deletion, duplication, insertion, indel, and splice-site changes following current recommendations of the Human Genome Variation Society (HGVS). Input is a GenBank accession number or an uploaded reference sequence file in GenBank format with user-modified annotation, an HGNC gene symbol, and the variant (single or in a batch file). Mutalyzer generates variant descriptions at DNA level, the level of all annotated transcripts and the deduced outcome at protein level. To validate Mutalyzer's performance and to investigate the sequence variant description quality in locus-specific mutation databases (LSDBs), more than 11,000 variants in the PAH, BIC BRCA2, and HbVar databases were analyzed, showing that 87%, 25%, and 38%, respectively, were error-free and following the recommendations. Low recognition rates in BIC and HbVar (38% and 51%, respectively) were due to lack of a well-annotated genomic reference sequence (HbVar) or noncompliance to the guidelines (BRCA2). Provided with well-annotated genomic reference sequences, Mutalyzer is very effective for the curation of newly discovered sequence variation descriptions and existing LSDB data. Mutalyzer will be linked to the Leiden Open source Variation Database (LOVD) (www.LOVD.nl; last accessed 13 September 2007) and is the first module of a sequence variant effect prediction package.

(c) 2007 Wiley-Liss, Inc.

PMID:
18000842
[PubMed - indexed for MEDLINE]
Icon for John Wiley & Sons, Inc.
2.
BMC Bioinformatics. 2011;12 Suppl 4:S5. doi: 10.1186/1471-2105-12-S4-S5. Epub 2011 Jul 5.

A formalized description of the standard human variant nomenclature in Extended Backus-Naur Form.

Author information

  • 1Department of Human Genetics, Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands.

Abstract

BACKGROUND:

The use of a standard human sequence variant nomenclature is advocated by the Human Genome Variation Society in order to unambiguously describe genetic variants in databases and literature. There is a clear need for tools that allow the mining of data about human sequence variants and their functional consequences from databases and literature. Existing text mining focuses on the recognition of protein variants and their effects. The recognition of variants at the DNA and RNA levels is essential for dissemination of variant data for diagnostic purposes. Development of new tools is hampered by the complexity of the current nomenclature, which requires processing at the character level to recognize the specific syntactic constructs used in variant descriptions.

RESULTS:

We approached the gene variant nomenclature as a scientific sublanguage and created two formal descriptions of the syntax in Extended Backus-Naur Form: one at the DNA-RNA level and one at the protein level. To ensure compatibility to older versions of the human sequence variant nomenclature, previously recommended variant description formats have been included. The first grammar versions were designed to help build variant description handling in the Alamut mutation interpretation software. The DNA and RNA level descriptions were then updated and used to construct the context-free parser of the Mutalyzer 2 sequence variant nomenclature checker, which has already been used to check more than one million variant descriptions.

CONCLUSIONS:

The Extended Backus-Naur Form provided an overview of the full complexity of the syntax of the sequence variant nomenclature, which remained hidden in the textual format and the division of the recommendations across the DNA, RNA and protein sections of the Human Genome Variation Society nomenclature website (http://www.hgvs.org/mutnomen/). This insight into the syntax of the nomenclature could be used to design detailed and clear rules for software development. The Mutalyzer 2 parser demonstrated that it facilitated decomposition of complex variant descriptions into their individual parts. The Extended Backus-Naur Form or parts of it can be used or modified by adding rules, allowing the development of specific sequence variant text mining tools and other programs, which can generate or handle sequence variant descriptions.

PMID:
21992071
[PubMed - indexed for MEDLINE]
PMCID:
PMC3194197
Free PMC Article
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