Bioinformatics tools used for whole-genome sequencing analysis of Neisseria gonorrhoeae: a literature review

被引：5

作者：

Singh, Reema ^{[1
]}

Kusalik, Anthony ^{[2
,3
]}

Dillon, Jo-Anne R. ^{[1
,4
]}

机构：

[1] Univ Saskatchewan, Coll Med, Dept Biochem Microbiol & Immunol, Saskatoon, SK, Canada

[2] Univ Saskatchewan, Dept Comp Sci, Saskatoon, SK, Canada

[3] Univ Saskatchewan, Bioinformat Program, Saskatoon, SK, Canada

[4] Vaccine & Infect Dis Org, Saskatoon, SK, Canada

来源：

BRIEFINGS IN FUNCTIONAL GENOMICS | 2022年 / 21卷 / 02期

基金：

加拿大健康研究院;

关键词：

bioinformatics; Neisseria gonorrhoeae; whole genome sequencing; antimicrobial resistance; molecular epidemiology; strain typing; population structure; EXTENDED-SPECTRUM CEPHALOSPORINS; MOLECULAR RESISTANCE MECHANISMS; ANTIMICROBIAL RESISTANCE; ANTIBIOTIC-RESISTANCE; DECREASED SUSCEPTIBILITY; TRANSMISSION CLUSTERS; REVEALS TRANSMISSION; PHYLOGENETIC TREES; FC428; CLONE; SINGLE-CELL;

D O I：

10.1093/bfgp/elab028

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

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.

引用

页码：78 / 89

页数：12

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