Lau K Vestergaard, Joanna Lopacinska-Jørgensen, Estrid V Høgdall
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However, these existing annotation tools may lack access to the latest ClinVar data, necessitating manual variant inspection.</p><p><strong>Aims: </strong>To address this gap in developing a tool providing the latest ClinVar data for variant annotation in clinical and research settings.</p><p><strong>Materials and methods: </strong>We introduce CANVAR, a Python-based script that efficiently annotates variants identified from next-generation sequencing in a clinical or research context, offering comprehensive information from the latest ClinVar database.</p><p><strong>Results: </strong>CANVAR provides accurate, up-to-date variant annotations, streamlining variant analysis.</p><p><strong>Discussion: </strong>The rise in genomic data requires accurate variant annotation for clinical decision-making. 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引用次数: 0
摘要
背景:基因组医学利用高通量测序技术分析与疾病相关的基因变异,从而改变了临床遗传学。准确的变异分类对诊断和治疗决策至关重要,临床上经常使用的各种工具和软件,如 Ion Reporter 软件和 Illumina Nirvana 软件,都利用 ClinVar 数据库/档案中的信息来帮助进行变异解读。然而,这些现有的注释工具可能无法访问最新的 ClinVar 数据,因此需要人工进行变异检查。目的:针对这一空白,开发一种工具,提供最新的 ClinVar 数据,用于临床和研究环境中的变异注释:我们介绍了基于 Python 的脚本 CANVAR,它能在临床或研究环境中有效地注释从下一代测序中发现的变异,并提供来自最新 ClinVar 数据库的全面信息:CANVAR提供了准确、最新的变异注释,简化了变异分析:讨论:随着基因组数据的增加,临床决策需要准确的变异注释。错误分类会带来风险,而且目前的工具可能并不总是能获取最新数据,这给变异解释带来了挑战:CANVAR通过提供来自最新ClinVar数据库的全面信息,对通过下一代测序确定的基因变异进行注释,从而为加强变异注释做出了贡献。
CANVAR: A Tool for Clinical Annotation of Variants Using ClinVar Databases.
Background: Genomic medicine has transformed clinical genetics by utilizing high-throughput sequencing technologies to analyze genetic variants associated with diseases. Accurate variant classification is crucial for diagnosis and treatment decisions, and various tools and software such as the Ion Reporter Software and the Illumina Nirvana Software often used in a clinical setting utilize information from the ClinVar database/archive to aid in variant interpretation. However, these existing annotation tools may lack access to the latest ClinVar data, necessitating manual variant inspection.
Aims: To address this gap in developing a tool providing the latest ClinVar data for variant annotation in clinical and research settings.
Materials and methods: We introduce CANVAR, a Python-based script that efficiently annotates variants identified from next-generation sequencing in a clinical or research context, offering comprehensive information from the latest ClinVar database.
Discussion: The rise in genomic data requires accurate variant annotation for clinical decision-making. Misclassification poses risks, and current tools may not always access the latest data, challenging variant interpretation.
Conclusion: CANVAR contributes to enhancing variant annotation by offering comprehensive information from the latest ClinVar database for genetic variants identified through next-generation sequencing.
期刊介绍:
Molecular Genetics & Genomic Medicine is a peer-reviewed journal for rapid dissemination of quality research related to the dynamically developing areas of human, molecular and medical genetics. The journal publishes original research articles covering findings in phenotypic, molecular, biological, and genomic aspects of genomic variation, inherited disorders and birth defects. The broad publishing spectrum of Molecular Genetics & Genomic Medicine includes rare and common disorders from diagnosis to treatment. Examples of appropriate articles include reports of novel disease genes, functional studies of genetic variants, in-depth genotype-phenotype studies, genomic analysis of inherited disorders, molecular diagnostic methods, medical bioinformatics, ethical, legal, and social implications (ELSI), and approaches to clinical diagnosis. Molecular Genetics & Genomic Medicine provides a scientific home for next generation sequencing studies of rare and common disorders, which will make research in this fascinating area easily and rapidly accessible to the scientific community. This will serve as the basis for translating next generation sequencing studies into individualized diagnostics and therapeutics, for day-to-day medical care.
Molecular Genetics & Genomic Medicine publishes original research articles, reviews, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented.