AutoCNV: a semiautomatic CNV interpretation system based on the 2019 ACMG/ClinGen Technical Standards for CNVs

• Main Authors: Chunna Fan, Zhonghua Wang, Yan Sun, Jun Sun, Xi Liu, Licheng Kang, Yingshuo Xu, Manqiu Yang, Wentao Dai, Lijie Song, Xiaoming Wei, Jiale Xiang, Hui Huang, Meizhen Zhou, Fanwei Zeng, Lin Huang, Zhengfeng Xu, Zhiyu Peng
• Format: Article
• Language: English
• Published: BMC 2021-10-01
• Series: BMC Genomics
• Subjects: AutoCNV; CNV interpretation; Scoring; CNV classification
• Online Access: https://doi.org/10.1186/s12864-021-08011-4

Abstract Background 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. Results 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). Conclusions 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.