Metagenomics - a guide from sampling to data analysis.
Metagenomics - a guide from sampling to data analysis.
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DOI：
10.1186/2042-5783-2-3
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发表时间：
2012-02-09
期刊：
影响因子：
--
通讯作者：
Meyer F
中科院分区：
文献类型：
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作者：
Thomas T;Gilbert J;Meyer F
宏基因组学应用一套基因组技术和生物信息学工具直接访问整个生物群落的遗传内容。宏基因组学领域在过去的5到10年里为微生物生态学、进化和多样性的重大进展做出了贡献，许多研究实验室现在都在积极参与其中。随着活动数量的增加，也产生了大量的方法学知识和专门知识，这些知识和专门知识应能指导该领域的未来发展。本文综述了宏基因组学的研究现状，并对宏基因组学中的样品处理、测序技术、组装、分箱、注释、实验设计、统计分析、数据存储和数据共享等方面提供了实用的指导和建议。随着越来越多的宏基因组数据集的产生，标准化程序和共享数据存储和分析的可用性变得越来越重要，以确保可以评估和比较各个项目的产出。
Metagenomics applies a suite of genomic technologies and bioinformatics tools to directly access the genetic content of entire communities of organisms. The field of metagenomics has been responsible for substantial advances in microbial ecology, evolution, and diversity over the past 5 to 10 years, and many research laboratories are actively engaged in it now. With the growing numbers of activities also comes a plethora of methodological knowledge and expertise that should guide future developments in the field. This review summarizes the current opinions in metagenomics, and provides practical guidance and advice on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing. As more metagenomic datasets are generated, the availability of standardized procedures and shared data storage and analysis becomes increasingly important to ensure that output of individual projects can be assessed and compared.