Metagenomics Data Analysis

About the course  |  Intended audience  |  Prerequisites  |  Content details

About the course

Metagenomics provides powerful approaches for investigating the composition and function of complex microbial communities without the need to culture individual organisms. This workshop introduces the theory and applications of metagenomics for studying microbiomes and microbial ecosystems.

Participants will learn about a range of metagenomic approaches, from simple and cost-effective amplicon-based methods to advanced Hi-C metagenomics techniques that provide detailed insights into complex microbial communities. The course also introduces bioinformatic tools and workflows for analysing metagenomic data, including quality control, assembly, post-processing, and interpretation of results.

By the end of the course, participants should be able to select appropriate metagenomics approaches for their research questions, identify suitable bioinformatics workflows, and critically interpret metagenomic analyses.

Teaching combines presentations and demonstrations with practical sessions applying commonly used metagenomics workflows and tools.

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Intended audience

This course is suitable for:

• biologists interested in microbiology and prokaryotic genomics
• researchers studying complex microbial communities and microbiomes
• participants interested in antimicrobial resistance and microbial ecology
• researchers seeking practical experience with metagenomics analysis workflows

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Prerequisites

Participants should have:

• a basic understanding of high-throughput sequencing technologies
• a working knowledge of the UNIX command line
• a working knowledge of R

For an overview of high-throughput sequencing technologies, we recommend watching this iBiology video.

The following experience is recommended:

• a basic knowledge of phylogenetic inference methods
• running analyses on High Performance Computing (HPC) clusters

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Content details

The course covers the following topics:

• Introduction to metagenomics
  Introduces the principles of metagenomics and the study of complex microbial communities using sequencing technologies.
• Amplicon-based metagenomics
  Covers amplicon sequencing approaches for characterising microbial communities, including their applications, strengths, limitations, and resource requirements.
• Shotgun metagenomics
  Introduces whole-metagenome shotgun sequencing approaches and discusses their applications for investigating microbial composition and functional potential.
• Hi-C metagenomics
  Covers Hi-C metagenomics methods and demonstrates how chromosome conformation information can be used to improve the reconstruction of microbial genomes from complex communities.
• Bioinformatics workflows for metagenomics
  Introduces commonly used bioinformatics workflows and software tools for analysing metagenomic datasets and discusses when different approaches are most appropriate.
• De novo metagenomic assembly
  Covers approaches for assembling metagenomic sequence data and introduces methods for reconstructing genomes from complex microbial communities.
• Metagenomics data post-processing
  Introduces downstream analyses and interpretation of metagenomic data, including methods for summarising, visualising, and exploring results.
• Contamination and quality control
  Covers approaches for assessing data quality, identifying contamination, and managing common issues encountered during metagenomic analyses.
• Planning metagenomics projects
  Discusses how to select appropriate metagenomic strategies and estimate the time and computational resources required for different types of metagenomics projects.

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