微生物组数据分析方法与应用

doi:10.16288/j.yczz.19-222

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Hereditas(Beijing) ›› 2019, Vol. 41 ›› Issue (9): 845-862.doi: 10.16288/j.yczz.19-222

• Review • Previous Articles Next Articles

Methods and applications for microbiome data analysis

Yongxin Liu^1,²,Yuan Qin^1,^2,³,Xiaoxuan Guo^1,²,Yang Bai^1,^2,³()

^1. State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, the Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China
^2. CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
^3. College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing 100101, China

Received:2019-07-30 Revised:2019-08-21 Online:2019-09-20 Published:2019-09-02
Contact: Bai Yang E-mail:ybai@genetics.ac.cn
Supported by:
Supported by the Key Research Program of Frontier Sciences of the Chinese Academy of Science No(QYZDB-SSW-SMC021);the National Natural Science Foundation of China No(31772400);the Key Research Program of the Chinese Academy of Sciences No(KFZD-SW-219)

Abstract

Abstract:

Development of high-throughput sequencing stimulates a series of microbiome technologies, such as amplicon sequencing, metagenome, metatranscriptome, which have rapidly promoted microbiome research. Microbiome data analysis involves a lot of basic knowledge, software and databases, and it is difficult for peers to learn and select proper methods. This review systematically outlines the basic ideas of microbiome data analysis and the basic knowledge required to conduct analysis. In addition, it summarizes the advantages and disadvantages of commonly used software and databases used in the comparison, visualization, network, evolution, machine learning and association analysis. This review aims to provide a convenient and flexible guide for selecting analytical tools and suitable databases for mining the biological significance of microbiome data.

Key words: microbiome, data analysis, amplicon, metagenome, pipeline

Yongxin Liu,Yuan Qin,Xiaoxuan Guo,Yang Bai. Methods and applications for microbiome data analysis[J]. Hereditas(Beijing), 2019, 41(9): 845-862.

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