用于淋病奈瑟菌全基因组测序分析的生物信息学工具：文献综述。
Bioinformatics tools used for whole-genome sequencing analysis of Neisseria gonorrhoeae: a literature review.
机构信息
Department of Biochemistry, Microbiology and Immunology.
Department of Computer Science at the University of Saskatchewan.
出版信息
Brief Funct Genomics. 2022 Apr 11;21(2):78-89. doi: 10.1093/bfgp/elab028.
Abstract
Whole-genome sequencing (WGS) data are well established for the investigation of gonococcal transmission, antimicrobial resistance prediction, population structure determination and population dynamics. A variety of bioinformatics tools, repositories, services and platforms have been applied to manage and analyze Neisseria gonorrhoeae WGS datasets. This review provides an overview of the various bioinformatics approaches and resources used in 105 published studies (as of 30 April 2021). The challenges in the analysis of N. gonorrhoeae WGS datasets, as well as future bioinformatics requirements, are also discussed.
摘要
全基因组测序（WGS）数据在淋球菌传播研究、抗菌药物耐药性预测、种群结构确定和种群动态监测方面得到了广泛应用。目前已经开发出多种生物信息学工具、数据库、服务和平台，用于管理和分析淋病奈瑟菌 WGS 数据集。本综述概述了截至 2021 年 4 月 30 日 105 篇已发表研究中使用的各种生物信息学方法和资源。文中还讨论了分析淋病奈瑟菌 WGS 数据集所面临的挑战，以及未来的生物信息学需求。
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