College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China.
Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, 300308, Tianjin, China.
BMC Genomics. 2021 Oct 6;22(1):721. doi: 10.1186/s12864-021-08011-4.
The American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen) presented technical standards for interpretation and reporting of constitutional copy-number variants in 2019 (the standards). Although ClinGen developed a web-based CNV classification calculator based on scoring metrics, it can only track and tally points that have been assigned based on observed evidence. Here, we developed AutoCNV (a semiautomatic automated CNV interpretation system) based on the standards, which can automatically generate predictions on 18 and 16 criteria for copy number loss and gain, respectively.
We assessed the performance of AutoCNV using 72 CNVs evaluated by external independent reviewers and 20 illustrative case examples. Using AutoCNV, it showed that 100 % (72/72) and 95 % (19/20) of CNVs were consistent with the reviewers' and ClinGen-verified classifications, respectively. AutoCNV only required an average of less than 5 milliseconds to obtain the result for one CNV with automated scoring. We also applied AutoCNV for the interpretation of CNVs from the ClinVar database and the dbVar database. We also developed a web-based version of AutoCNV (wAutoCNV).
AutoCNV may serve to assist users in conducting in-depth CNV interpretation, to accelerate and facilitate the interpretation process of CNVs and to improve the consistency and reliability of CNV interpretation.
美国医学遗传学与基因组学学院（ACMG）和临床基因组资源（ClinGen）于 2019 年提出了用于解读和报告常染色体拷贝数变异的技术标准（以下简称标准）。虽然 ClinGen 基于评分指标开发了一个基于网络的 CNV 分类计算器，但它只能跟踪和统计基于观察证据分配的分数。在此，我们基于标准开发了 AutoCNV（一种半自动的自动 CNV 解读系统），它可以分别自动生成关于拷贝数缺失和增益的 18 项和 16 项标准的预测。
我们使用 72 个经外部独立评审员评估的 CNV 和 20 个说明性案例评估了 AutoCNV 的性能。使用 AutoCNV，它表明 100%（72/72）和 95%（19/20）的 CNV 与评审员和 ClinGen 验证的分类分别一致。AutoCNV 仅需平均不到 5 毫秒的时间即可获得一个 CNV 的自动评分结果。我们还将 AutoCNV 应用于 ClinVar 数据库和 dbVar 数据库中的 CNV 解读。我们还开发了 AutoCNV 的网络版本（wAutoCNV）。
AutoCNV 可以帮助用户进行深入的 CNV 解读，加速和简化 CNV 解读过程，并提高 CNV 解读的一致性和可靠性。
