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Updated: Jan 19, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

[Methods and applications for microbiome data analysis].

Yongxin Liu^1,2, Yuan Qin^1,2,3, Xiao-Xuan Guo^1,2

¹State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, the Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing 100101, China.

Yi Chuan = Hereditas

|September 25, 2019

Summary

This summary is machine-generated.

This review guides researchers through microbiome data analysis, covering essential knowledge, software, and databases for microbiome research. It simplifies selecting analytical tools for biological significance discovery.

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Area of Science:

Microbiology
Bioinformatics
Genomics

Background:

High-throughput sequencing technologies have advanced microbiome research.
Microbiome data analysis requires specialized knowledge, software, and databases, posing challenges for researchers.
Existing analytical methods and tools are diverse and complex to navigate.

Purpose of the Study:

To provide a systematic overview of microbiome data analysis.
To outline the fundamental knowledge required for microbiome data analysis.
To offer a guide for selecting appropriate analytical tools and databases for microbiome research.

Main Methods:

Systematic review of microbiome data analysis concepts.
Summary of essential knowledge for microbiome data analysis.
Comparative analysis of commonly used software and databases for various analytical tasks (comparison, visualization, network, evolution, machine learning, association).

Main Results:

Key concepts and required knowledge for microbiome data analysis are outlined.
Advantages and disadvantages of popular software and databases are discussed.
Guidance is provided for selecting tools for specific analyses like comparison, visualization, and machine learning.

Conclusions:

This review serves as a practical guide for researchers in microbiome studies.
It facilitates the selection of suitable analytical tools and databases.
Aims to aid in mining the biological significance of microbiome data effectively.