外显子组测序
索引
一致性
多路复用
DNA测序
计算生物学
拷贝数变化
计算机科学
基因型
遗传学
生物
单核苷酸多态性
突变
基因组
基因
作者
Kuo Zhang,Lijia Yu,Guigao Lin,Jinming Li
标识
DOI:10.1016/j.cca.2022.08.008
摘要
Whole-exome sequencing (WES) technology has become an essential tool in the clinical diagnostic for rare genetic disorders, however, the issues that reduce testing precision, sensitivity, and concordance are not clear under routine testing conditions. The study is to systematically evaluate the comparability of clinical WES testing results in laboratories under routine conditions. We designed a multi-laboratory study across 24 participating laboratories in China. We assessed sequencing quality across capture methods and sequencing platforms, benchmarked the impact of coverage and callable regions on detecting single nucleotide variants (SNVs), small insertions and deletions (Indels) under the same computational approaches, and compared the sensitivity, precision and reproducibility on detecting mutations across laboratories. High inter-laboratory variability on variants detection were found across participating laboratories. Sample DNA concentration and sequencing evenness are two major variables that lead to the coverage variation. The difference in bioinformatics tools and computational settings affect the sensitivity and precision of the final output. Besides, copy-number variants (CNVs) identification is less reproducible than SNVs and Indels in the WES testing. We also compiled a list of 4441 low coverage ClinVar variants of 1176 genes from this study, which can be used as a source for creating in silico and synthetic DNA reference materials for clinical genetic disorder detection. The considerable inter-laboratory variability seen in both sequencing coverage evenness and variants detection highlights the urgent need to improve the precision, sensitivity and comparability of the results generated across different laboratories. The list of low coverage variants can have important implications for the development and validation of clinical genetic disorder tests by laboratories. This study also serves to best practice inform guidelines for detecting clinical genetic disorders by exome sequencing.
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