Bioinformatics training course on Zebrafish

**EMBL-EBI Course: Bioinformatics and functional genomics in zebrafish. **
**27 - 30 September 2022. **
EMBL-EBI | Hinxton, Cambridge, UK

Search for the course title on the EMBL-EBI training website.

Applications close on 1 July 2022.

Course overview

Zebrafish are widely used to study development, toxicity and disease, and functional genomics is used throughout the field to identify new pathways and mechanisms, and for comparison to other model systems and humans. In this hands-on course, participants will learn how to design functional genomics experiments, manage and analyse RNA-seq datasets from zebrafish, and compare results to other species. The aim of the course is to equip researchers with tools to carry out functional analysis and data visualisation of RNA-seq data that has already been mapped to the genome and been analysed for differential gene expression. The course will be relevant to researchers working on a wide range of topics and will use real datasets from our lab for hands-on analysis.

Please note that this course will not teach the initial steps of RNA-seq analysis but instead start at the point that you have a list of differentially expressed genes. View other EMBL-EBI’s courses cover the initial stages extensively, for instance [Introduction to RNA-seq and functional interpretation].

In-person course

We plan to deliver this course in an in-person manner onsite at our training suite at EMBL-EBI, Hinxton. Please be aware that we are continually evaluating the ongoing pandemic situation and, as such, may need to change the format of courses at short notice. Your safety is paramount to us; you can read our COVID guidance policy for more information.

Who is this course for?

This course is aimed at researchers currently working with zebrafish and generating genomic and functional data. Graduate students, postdoctoral fellows, research scientists, and faculty are encouraged to apply.

The course starts at the point where the participant will have a list of differentially expressed genes, therefore little to no experience with RNA-seq analysis is required. However,

  • Applicants who have already generated an RNA-seq dataset from zebrafish samples relevant to their project will gain the most benefit from this course.
  • If you want to get familiar with the initial steps of RNA-seq analysis you can view the materials from other courses that cover them extensively, such as the [EMBL-EBI’s Introduction to RNA-seq and functional interpretation course]. The Bioinformatics and functional genomics in zebrafish course does not cover these stages.

Some experience with R is beneficial. During the course, some of the practicals will make use of a Linux-based command line interface, and R statistical packages. We recommend completing some basic tutorials on this topic in preparation for the upcoming course. There are many tutorials available online and here are some that may be of help:

Regardless of your current knowledge, we encourage successful participants to use these, and other materials, to prepare for attending the course and future work in this area.

What will I learn?

Learning outcomes

After this course you should be able to:

  • Design and implement RNA-seq experiments using zebrafish
  • Know and apply common approaches and tools used in the analysis of zebrafish expression data
  • Undertake basic data visualisation
  • Query RNA-seq datasets for gene signatures and patterns of gene expression
  • Undertake cross-species comparison of gene datasets
  • Have a working knowledge of web and R-based approaches for analysing gene expression.

Course content

During this course you will learn about:

  • [Ensembl]
  • [BioMart]
  • [Reactome]
  • [Gene Ontology]
  • Zebrafish anatomical term enrichment
  • Data and metadata submission
  • [Expression Atlas]
  • Basic tools for data visualisation using R


Elisabeth Busch-Nentwich, Queen Mary University of London
Silvie Korena Fexova, EMBL-EBI
Nancy George, EMBL-EBI
Benjamin Moore, EMBL-EBI
Gun Antonia Nilsson Lock, EMBL-EBI
Eliot Ragueneau, EMBL-EBI
Ian Sealy, Queen Mary University of London
Krishna Kumar Tiwari, EMBL-EBI
Richard White, Queen Mary University of London