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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/metagenomics
课程评论：没有评论
课程名称：应用于病原体与抗生素耐药监测的宏基因组学 课程概述：宏基因组学和全社区测序是揭示微生物群落及其与人类疾病和抗生素耐药性关系的重要领域。生物信息学工具在解析宏基因组数据中至关重要，能够估算复杂样品中病原体和抗生素耐药性决定因素的存在。结合相关的解释性数据，宏基因组学成为监测的强大工具。本课程将探讨宏基因组学用于监测的潜力，并为学习者提供宏基因组研究的步骤和考虑因素概述。完成本课程后，学习者将了解： - 宏基因组学与其他微生物基因组学概念之间的区别 - 在宏基因组研究各步骤中使用对照的必要性 - 宏基因组学在抗生素耐药监测中的优势 - 采样设计、样品大小、样品材料和样品处理如何影响宏基因组研究的结果 - 细菌和病毒宏基因组样品处理 - 不同测序平台及其在宏基因组学中的应用 - 一般宏基因组研究的步骤，包括质量控制、映射到不同数据库和读取计数分析 - 分析宏基因组数据的各种工具的原理 - 如何解读读取分类结果 - 监测中流行病学的必要性 - 全球与综合监测的概念 - 在监测中使用宏基因组学面临的挑战 - 宏基因组学在监测中的潜力 我们期待您的参与！ 课程大纲： 第一部分：从采样到测序 描述：本模块将介绍宏基因组学、在宏基因组研究中需要考虑的事项和对照，以及抗生素耐药性话题。 第二部分：从读取到结果 描述：本模块将介绍宏基因组数据生物信息学分析的基础，包括不同类型的分析和可用的不同算法。然后学习质量控制、MGmapper和KRAKEN（两个免费提供的生物信息学分析管道）和ResFinder（抗生素耐药基因数据库）。通过真实研究的示例演示生物信息学分析的一些挑战。 第三部分：结果解读与宏基因组学监测潜力 描述：本模块将学习两种分析和解读序列读取的方法——分类和组装。将展示可视化读取计数和将宏基因组学与解释性数据结合分析的方法的示例。最后，学习宏基因组学在未来全球与综合监测中的潜力，以及在此过程中可能遇到的挑战。
Part: 1
Title:From sampling to sequencing
Description:In this module, you will be introduced to metagenomics, some of the considerations and controls that need to be in place in a metagenomics study, and to the topic of antimicrobial resistance.
Part: 2
Title:FROM READS TO RESULTS
Description:In this module, you will be introduced to the basics of bioinformatics analysis of metagenomics data, including the different types of analysis possible and the different algorithms available. You will then learn about quality control, MGmapper and KRAKEN (two freely available bioinformatics pipelines), and ResFinder (a database of antimicrobial resistance genes). An example from a real study will demonstrate some of the challenges of a bioinformatics analysis.
Part: 3
Title:Interpretation of results and potential of metagenomics for surveillance
Description:In this module you will learn about two different approaches to analyse and interpret sequence reads - classification and assembly. You will see examples of methods to vizualize read counts and to analyze metagenomics together with explanatory data. Last, you will learn the potential of metagenomics for the development of a future global and integrated surveillance, and the challenges you may encounter during that process
The field of metagenomics and whole community sequencing is a promising area to unravel the content of microbial communities and their relationship to disease and antimicrobial resistance in the human population. Bioinformatic tools are extremely important for making sense out of metagenomics data, by estimating the presence of pathogens and antimicrobial resistance determinants in complex samples. Combined with relevant explanatory data, metagenomics is a powerful tool for surveillance. In this course, we teach about the potential of metagenomics for surveillance and give the learners an overview of the steps and considerations in a metagenomics study. After this course, the learners will know: - the difference between the concepts of metagenomics and other microbial genomics - the need to use controls in different steps of a metagenomics study - the advantages of metagenomics for the surveillance of antimicrobial resistance - how sampling design, sample size, sample material and sample handling influence the outcome of a metagenomics study - sample processing for bacterial and viral metagenomics - different sequencing platforms and their possibilities regarding metagenomics - the steps involved in a general metagenomics study, including quality control, mapping to different databases, and read count analysis - the principles behind various tools available for analysis of metagenomics data - how to interpret read classification results - the need for epidemiology in surveillance - the concept of global and integrated surveillance - the challenges for the use of metagenomics in surveillance - the potential of metagenomics for surveillance We look forward to welcoming you !
