Tongsima Sissades, Assawamakin Anunchai, Piriyapongsa Jittima, Shaw Philip J
National Center for Genetic Engineering and Biotechnology (BIOTEC), 113 Thailand Science Park, Pahonyothin Road, Klong 1, Klong Luang, 12120, Pathum Thani, Thailand.
Methods Mol Biol. 2011;760:207-21. doi: 10.1007/978-1-61779-176-5_13.
DNA sequencing is an important tool for discovery of genetic variants. The task of detecting single-nucleotide variants is complicated by noise and sequencing artifacts in sequencing data. Several in silico tools have been developed to assist this process. These tools interpret the raw chromatogram data and perform a specialized base-calling and quality-control assessment procedure to identify variants. The approach used to identify variants differs between the tools, with some specific to SNPs and other for Indels. The choice of a tool is guided by the design of the sequencing project and the nature of the variant to be discovered. In this chapter, these tools are compared to facilitate the choice of a tool used for variant discovery.
DNA测序是发现基因变异的重要工具。测序数据中的噪声和测序假象使检测单核苷酸变异的任务变得复杂。已经开发了几种计算机工具来辅助这一过程。这些工具解读原始色谱图数据，并执行专门的碱基识别和质量控制评估程序以识别变异。不同工具用于识别变异的方法有所不同，有些特定于单核苷酸多态性（SNP），有些则用于插入缺失（Indel）。工具的选择取决于测序项目的设计和要发现的变异的性质。在本章中，将对这些工具进行比较，以方便选择用于变异发现的工具。
