Metagenomics: Data Analysis and Interpretation

This course will provide an overview of the main aspects involved in metagenomics data analysis and discussion around the interpretation and actual examples of the impact and applications of metagenomics derived research. A substantial part of the course will be devoted to hands-on experience with bioinformatics resources and tools relevant in metagenomics data analysis.

Participants will start with an overview of NGS technologies, then proceed to look at experimental approaches and emerging technologies. The remainder of the course will be spent in front of the computers learning how to produce metagenomic assemblies, and taking participants from data to publication-ready figures.

What will I learn?

• An overview of NGS for metagenomics including current projects and emerging technologies
• A practical understanding of the instrumentation and methods used to generate and sequence metagenomics libraries
• An overview of software for analysis and interpretation of metagenomics datasets and some basic analytical workflows
• Hands-on experience of a case study dataset including FastQC, trimming and host removal
• Understanding assembly principles and the latest metagenomics assembly tools
• Hands on experience in metagenomics assembly
• Using MEGAN to explore metagenomic including taxonomic and functional annotation, multiple comparison methods and production of publication quality images
• An overview and hands on experience in public data resources for metagenomics e.g. IMG/M, EBI Metagenomics, MG-RAS

Course prerequisites

You are expected to be familiar and competent with a range of laboratory equipment and follow GLP.

Some basic knowledge and experience in LINUX is desirable. If no previous experience, it is recommended that you follow a tutorial such as the one here prior to attending the course.

Target audience

This course is aimed at advanced PhD students and post-doctoral researchers who are currently undertaking, or are in the planning stages of, a metagenomics project.