初学者指南比较细菌基因组分析使用下一代序列数据。

David J Edwards, Kathryn E Holt
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引用次数: 124

摘要

高通量测序现在足够快速和便宜,被认为是研究细菌工具箱的一部分,并且在公共领域有成千上万的细菌基因组序列可供比较。细菌基因组分析越来越多地由不同的研究小组,临床和公共卫生实验室进行,他们对与细菌遗传学和进化相关的广泛主题感兴趣。例子包括疫情分析以及致病性和抗菌素耐药性研究。在这个初学者指南中,我们的目标是为具有生物学背景的个人提供一个切入点,他们想要对细菌基因组数据进行自己的生物信息学分析,使他们能够回答自己的研究问题。我们假设读者将熟悉遗传学和序列数据的基本性质,但不假设任何计算机编程技能。主要内容包括组合、序列排序、注释、基因组比较和提取共同分型信息。每个部分都包括使用公开可用的大肠杆菌数据和免费软件工具的工作示例,所有这些都可以在台式计算机上执行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Beginner's guide to comparative bacterial genome analysis using next-generation sequence data.

Beginner's guide to comparative bacterial genome analysis using next-generation sequence data.

Beginner's guide to comparative bacterial genome analysis using next-generation sequence data.

Beginner's guide to comparative bacterial genome analysis using next-generation sequence data.

High throughput sequencing is now fast and cheap enough to be considered part of the toolbox for investigating bacteria, and there are thousands of bacterial genome sequences available for comparison in the public domain. Bacterial genome analysis is increasingly being performed by diverse groups in research, clinical and public health labs alike, who are interested in a wide array of topics related to bacterial genetics and evolution. Examples include outbreak analysis and the study of pathogenicity and antimicrobial resistance. In this beginner's guide, we aim to provide an entry point for individuals with a biology background who want to perform their own bioinformatics analysis of bacterial genome data, to enable them to answer their own research questions. We assume readers will be familiar with genetics and the basic nature of sequence data, but do not assume any computer programming skills. The main topics covered are assembly, ordering of contigs, annotation, genome comparison and extracting common typing information. Each section includes worked examples using publicly available E. coli data and free software tools, all which can be performed on a desktop computer.

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