DNA测序
杠杆(统计)
计算生物学
数据科学
生物信息学
医学
计算机科学
人工智能
DNA
生物
遗传学
作者
Nicholas Bradley Larson,Ann L. Oberg,Alex A. Adjei,Liguo Wang
标识
DOI:10.1016/j.jtho.2022.11.006
摘要
Next-generation sequencing (NGS) technologies are high-throughput methods for DNA sequencing and have become a widely adopted tool in cancer research. The sheer amount and variety of data generated by NGS assays require sophisticated computational methods and bioinformatics expertise. In this review, we provide background details of NGS technology and basic bioinformatics concepts for the clinician investigator interested in cancer research applications, with a focus on DNA-based approaches. We introduce the general principles of presequencing library preparation, postsequencing alignment, and variant calling. We also highlight the common variant annotations and NGS applications for other molecular data types. Finally, we briefly discuss the revealed utility of NGS methods in NSCLC research and study design considerations for research studies that aim to leverage NGS technologies for clinical care.
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