Metagenomic data analysis

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21 & 22 January 2020

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CEH Wallingford, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxfordshire, OX10 8BB Location map & travel directions


£ 569 regular (Early Bird rate ends 15 June 2019, then £599)

£449 registered students (Early Bird rate ends 15 June, then £499)

Refreshments are included in the price. Accommodation is not included in the price.

Short Course Description:

This 2-day course will teach you how to perform metagenomics analysis with the software packages Qiime2 and R.

Day 1: Understanding the basics of work on the command line, followed by strategies to analyse different types of microbial data (amplicon and shotgun)

Day 2: In the morning, you will prepare sample datasets and analyse them in Qiime2 utilizing its different plug-ins. In the afternoon, you will analyse the same dataset in R with the Dada2 pipeline, followed by multivariate statistical analysis in R. You will then compare the results of the different pipelines.

Learning outcomes:

By the end of the course, participants will understand how to use Qiime 2 and R to prepare raw amplicon and shotgun metagenomic data for analysis, and run some of the statistical tools available in both software packages.


Accommodation is not included in the cost. More detail: see FAQ and our guide for accommodation near our  Wallingford site.





Undergraduate-level knowledge of microbial ecology and fieldwork design are required.

Some knowledge of programming would be an advantage, but not essential. Joining instructions will include information on how to access and use the free open source programming languages R and Qiime2.


Course Leader:

Dr Katja Lehmann, Microbial Ecologist and Bioinformatician,

Centre for Ecology & Hydrology. Dr Lehmann has been a member of the NERC Bioinformatics Analysis Facility Wallingford and has taught bioinformatics to early careers researchers.


Target Audience:

MSc and PhD students and early career researchers working on microbial sequencing datasets.

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Course delivery:

Blended learning, with lectures, discussions and independent learning times with elements of problem-based learning

Relevant links and key publications:

Lehmann, K. "Sampling of riverine or marine bacterial communities in remote locations: from field to publication." Marine Genomics: Methods and Protocols (2016): 1-11.