Gain knowledge of the tools, processes and analysis approaches used in the field of metagenomics.

This course will cover the metagenomics data analysis workflow from the point of newly generated sequence data. Participants will explore the use of publicly available resources and tools to manage, share, analyse and interpret metagenomics data. The content will include issues of data quality control and how to submit to public repositories. While sessions will detail marker-gene and whole-genome shotgun (WGS) approaches; the primary focus will be on assembly-based approaches. Discussions will also explore considerations when assembling genome data, the analysis that can be carried out by MGnify on such datasets, and what downstream analysis options and tools are available.

Virtual course

The course content will involve participants learning via pre-recorded lectures, live presentations and trainer Q&A sessions. Practical experience will be developed through group activities and computational exercises. Sessions will be delivered over Zoom with additional text communication over Slack. Trainers will be available to assist, answer questions and further explain the analysis during these times. Computational practicals will be run in Docker containers operating on EMBL-EBI's virtual training infrastructure; this means there is no need to have a powerful computer to run exercises or a requirement to install complex software before the course.

Participants will need to be available between the hours of 09:00-17:00 GMT each day of the course.

Who is this course for?

This course is aimed at life scientists who are working in the field of metagenomics and are currently in the early stages of data analysis. Participants should have some prior experience of using bioinformatics in their research.

The practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. Participants should ensure that they complete these free tutorials before attending the course:

• Basic introduction to the Unix environment: www.ee.surrey.ac.uk/Teaching/Unix
• Basic R concept tutorials: www.r-tutor.com/r-introduction

What will I learn?

Learning outcomes

After this course participants should be able to:

• Conduct appropriate quality control and decontamination of metagenomic data and run simple assembly pipelines on short read data
• Utilise public datasets and resources to identify relevant data for analysis
• Apply appropriate tools in the analysis of metagenomic data
• Submit metagenomics data to online repositories for sharing and future analysis
• Apply relevant knowledge in strain resolution and comparative metagenome analysis to their own research

Course content

During this course participants will learn about:

• Microbiome data types: Amplicon approaches (ribosomal RNA), whole genome shotgun (WGS) approaches, assembly and metagenome assembled genomes (MAGs)
• Data analysis: MGnify, HMMER, InterPro, Gene Ontology (GO), FASTQC, and pathway analyses
• Data standards and submission:
  • European Nucleotide Archive (ENA)
  • Genomic Standards Consortium (GSC)
  • Sequence Read Archive (SRA)
  • Webin
• Metagenomics data analysis workflow

Trainers

Please read our page on application advice before starting your application. In order to be considered for a place on this course, you must do the following:

• Complete the online application form providing answers as directed
• Ensure you add relevant information to the "Application submission" section where you are asked to provide three 100-word paragraphs that cover your:
  • scientific biography
  • work history
  • current research interests
• Upload a letter of support from your supervisor or a senior colleague detailing reasons why you should be selected for the course

Please submit all documents during the application process by midnight on Friday 02 October 2020.

Incomplete applications will not be considered.

Participant flash talks

There will be an opportunity for all participants to give a short presentation as part of the course covering their work. These will offer a chance to share research with the other participants and an opportunity for them and trainers to ask questions. Further details will be provided following registration.