利用肿瘤检测的真实下一代测序数据,比较多种变异注释软件解决方案的分类方法

Roy Khalife, Tara M. Love, Lara Sucheston-Campbell, Michael J. Clark, Helle Sorensen, Shuba Krishna, Anthony Magliocco
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引用次数: 0

摘要

变异注释是解读基因组变异的功能影响及其与疾病关系的重要一步。在这项研究中,我们分析了 80 例进行了全面基因组检测的泛癌症病例,并比较了罗氏、SOPHiA GENETICS、QIAGEN 和 Genoox 四种全球通用的变异解读软件解决方案的自动分类变异层级。结果表明,不同软件的变异等级分类存在显著差异,这被认为是多种因素共同作用的结果,其中包括 AMP/ASCO/CAP 指南的主观性、变异等位基因频率和群体等位基因频率的阈值设置以及疾病本体论的差异。尽管本文介绍的软件工具为解读基因组数据提供了省时、可重复的流程,但了解这些解决方案的细微差别和各种设置至关重要,因为它们会对变异层级分类和下游管理产生重大影响。
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Comparing Classifications from Multiple Variant Annotation Software Solutions Using Real-World Next Generation Sequencing Data from Oncology Testing
Variant annotation is an important step in deciphering the functional impact of genomic variants and their association with diseases. In this study, we analyzed 80 pan-cancer cases that underwent comprehensive genomic testing and compared the auto-classified variant tiers among four globally-available software solutions for variant interpretation from Roche, SOPHiA GENETICS, QIAGEN, and Genoox. The results revealed striking differences in tier classifications, which are believed to be a result of several factors, including subjectivity in the AMP/ASCO/CAP guidelines, threshold settings for variant allele frequencies and population allele frequencies, as well as variation in disease ontologies. Although the software tools described here provide a time-saving and repeatable process for interpretation of genomic data, it is crucial to understand the nuances and various settings for these solutions, as they can strongly influence variant tier classifications and downstream management.
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