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Related Experiment Video

Updated: Feb 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

Computational Methods for Human Microbiome Analysis.

Matthieu J Miossec¹, Sandro L Valenzuela¹, Katterinne N Mendez¹

¹Center for Bioinformatics and Integrative Biology, Faculty of Biological Sciences, Universidad Andrés Bello, Santiago, Chile.

Current Protocols in Microbiology

|November 10, 2017

Summary

This summary is machine-generated.

This study provides essential protocols for human microbiome research, simplifying computational tasks and integrating diverse data types for biological insight. These methods form the foundation for analyzing the human microbiome effectively.

Keywords:

alpha and beta diversity differential abundance testing human microbiome metagenome decontamination metagenome reads read mapping

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Last Updated: Feb 19, 2026

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

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Published on: October 15, 2019

A Method for Targeted 16S Sequencing of Human Milk Samples

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Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

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Published on: March 19, 2018

Area of Science:

Microbiology
Computational Biology
Genomics

Background:

The field of microbiomics is rapidly advancing, increasing computational demands for biological insight.
Human microbiome analyses increasingly integrate diverse high-throughput data types.
Core methodologies underpin most human microbiome studies.

Purpose of the Study:

To present detailed, step-by-step protocols for key stages in human microbiome research.
To provide a foundational set of methods for researchers in the field.
To enable researchers to adapt protocols for specific data characteristics.

Main Methods:

Detailed protocols for five core stages of human microbiome analysis.
Guidance on tailoring methods to specific experimental data.
Focus on foundational computational and analytical techniques.

Main Results:

A comprehensive unit detailing essential protocols for human microbiome research.
Standardized methods to manage increasing computational workload.
A framework for integrating multiple high-throughput data types.

Conclusions:

The presented protocols serve as a baseline for human microbiome analysis.
Researchers can utilize and adapt these methods for their specific studies.
This work supports the growing integration of diverse data in microbiome research.