The Baiyang Research Group of Protein & Cell Institute of Genetics and Development publishes an important review of "Microbiome Data Analysis Method"

In recent years, the development of high-throughput sequencing technology has promoted the development of a series of technologies suitable for microbiome research, and has also accumulated massive amounts of data
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However, the complicated process of microbiome data analysis and the wide variety of analysis tools restrict the majority of researchers from entering this field
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Bai Yang's research group at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences was invited by the Protein & Cell (IF: 14.
87) editorial department to write a review of microbiome data analysis methods
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This review summarizes the advantages and disadvantages of commonly used microbiome sequencing technologies-amplicons and metagenomics, and recommends commonly used software, analysis procedures, and databases so that researchers can choose suitable analysis tools and methods
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In addition, the statistics and visualization methods for downstream analysis of the microbiome are introduced, including methods such as diversity, species composition, difference comparison, correlation, networking, machine learning, evolution, and source tracing (Figure)
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Finally, it introduces the recommended scheme of repeatable analysis.
I hope that this article will help fellow researchers choose suitable analysis tools, efficiently analyze the data, and effectively explore the biological meaning behind the data
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 Figure: Common visualization schemes for microbiome data analysis.
The research results were officially published in Protein & Cell magazine (DOI:10.
1007/s13238-020-00724-8) in May 2021
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Senior Engineer Liu Yongxin and PhD student Qin Yuan of the Institute of Genetics and Development and Assistant Researcher Chen Tong of the China Academy of Chinese Medical Sciences are the co-first authors of the paper.
Senior Engineer Liu Yongxin and Researcher Bai Yang are the co-corresponding authors of the paper.
Professor Lu Meiping, Zhejiang University School of Medicine, Dr.
Qian Xubo and Guo Xiaoxuan from the Baiyang Group participated in this project
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Related work is supported by the Chinese Academy of Sciences' Strategic Leading Science and Technology Special Project, Frontier Science Key Research Project, and National Natural Science Foundation of China
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