The rapid evolution of next-generation sequencing (NGS)-based tumor genomic profile detection and the emergence of molecularly targeted therapies have enabled precision oncology. In NGS-based analysis, various types of databases have been developed to perform different functions. However, many problems still exist when using these public databases. Therefore, it is important to better understand the characteristics and limitations of each database and have them complement each other to provide useful clinical evidence for NGS testing. In this review, we elaborate on the important role of databases and their concrete applications in NGS-based somatic mutation detection. We introduce the typically used databases for sequence alignment, variant filtration, and variant interpretation, and compare the differences between the databases with similar functions. Subsequently, we determine the limitations of each database and provide the corresponding solutions. Furthermore, we present an overview diagram to clearly illustrate the database used in the entire NGS-based somatic mutation detection pipeline.

基于下一代测序（NGS）的肿瘤基因组概况检测的快速发展以及分子靶向疗法的出现使精确肿瘤学成为可能。在基于NGS的分析中，已经开发了各种类型的数据库来执行不同的功能。但是，使用这些公共数据库时仍然存在许多问题。因此，重要的是更好地了解每个数据库的特征和局限性，并使它们相互补充，以为NGS测试提供有用的临床证据。在这篇综述中，我们详细介绍了数据库及其在基于NGS的体细胞突变检测中的具体应用的重要作用。我们介绍了用于序列比对，变体过滤和变体解释的常用数据库，并比较具有相似功能的数据库之间的差异。随后，我们确定每个数据库的局限性并提供相应的解决方案。此外，我们提供了一个概览图，以清楚地说明整个基于NGS的体细胞突变检测流水线中使用的数据库。