生物
假基因
计算生物学
人口
基因检测
多重连接依赖探针扩增
人类遗传学
生物信息学
遗传学
基因
基因组
医学
外显子
环境卫生
作者
Che-yu Lee,Hai-Yun Yen,Alan Zhong,Hanlin Gao
出处
期刊:Human Genetics
[Springer Nature]
日期:2020-09-11
卷期号:140 (3): 477-492
被引量:23
标识
DOI:10.1007/s00439-020-02216-5
摘要
Next-generation sequencing (NGS) is an incredibly useful tool for genetic disease diagnosis. However, the most commonly used bioinformatics methods for analyzing sequence reads insufficiently discriminate genomic regions with extensive sequence identity, such as gene families and pseudogenes, complicating diagnostics. This problem has been recognized for specific genes, including many involved in human disease, and diagnostic labs must perform additional costly steps to guarantee accurate diagnosis in these cases. Here we report a new data analysis method based on the comparison of read depth between highly homologous regions to identify misalignment. Analyzing six clinically important genes-CYP21A2, GBA, HBA1/2, PMS2, and SMN1-each exhibiting misalignment issues related to homology, we show that our technique can correctly identify potential misalignment events and be used to make appropriate calls. Combined with long-range PCR and/or MLPA orthogonal testing, our clinical laboratory can improve variant calling with minimal additional cost. We propose an accurate and cost-efficient NGS testing procedure that will benefit disease diagnostics, carrier screening, and research-based population studies.
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