注释工具之间临床变异命名法的差异。
Variations in Nomenclature of Clinical Variants between Annotation Tools.
作者信息
Park Kyoung-Jin, Park Jong-Ho
机构信息
Department of Laboratory Medicine & Genetics, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea.
Department of Laboratory Medicine & Genetics, Samsung Medical Center, Seoul, South Korea.
出版信息
Lab Med. 2022 May 5;53(3):242-245. doi: 10.1093/labmed/lmab074.
BACKGROUND
Accurate nomenclature of variants is an essential element for genetic diagnosis and patient care.
OBJECTIVE
To investigate annotation differences of clinical variants between annotation tools.
METHODS
We analyzed 218,156 clinical variants from the Human Gene Mutation Database. Multiple nomenclatures based on RefSeq transcripts were provided using ANNOVAR and snpEff.
RESULTS
The concordance rate between ANNOVAR and snpEff was approximately 85%. Based on the Human Genome Variation Society (HGVS) nomenclature, snpEff was more accurate than ANNOVAR (coding variants, 99.3% vs 84.9%; protein variants, 94.3% vs 79.8%). When annotating each variant with ANNOVAR and snpEff, the accuracy of nomenclature was 99.5%.
CONCLUSIONS
There were substantial differences between ANNOVAR and snpEff annotations. The findings of this study suggest that simultaneous use of multiple annotation tools could decrease nomenclature errors and contribute to providing standardized clinical reporting.
背景
变异的准确命名是基因诊断和患者护理的重要要素。
目的
研究注释工具之间临床变异的注释差异。
方法
我们分析了来自人类基因突变数据库的218,156个临床变异。使用ANNOVAR和snpEff提供了基于RefSeq转录本的多种命名法。
结果
ANNOVAR和snpEff之间的一致性率约为85%。基于人类基因组变异协会（HGVS）命名法，snpEff比ANNOVAR更准确（编码变异，99.3%对84.9%；蛋白质变异，94.3%对79.8%）。当用ANNOVAR和snpEff注释每个变异时，命名法的准确性为99.5%。
结论
ANNOVAR和snpEff注释之间存在显著差异。本研究结果表明，同时使用多种注释工具可以减少命名错误，并有助于提供标准化的临床报告。
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