Virtual course

Introduction to multiomics data integration and visualisation

Identify the challenges, strategies and resources for multiomics data integration using biological examples. 

The virtual course will focus on the use of public data resources and open access tools for enabling integrated working, with an emphasis on data visualisation. Working with public domain data can provide added value to data derived through a researcher’s own work and additionally  inform experimental design. This course is highly relevant in the current research scenario, where an increased volume of data across the whole spectrum of biology has created both more opportunities and challenges to identifying novel perspectives and answering questions in the life sciences. This course will focus on issues around data integration, but will not include systems biology modelling or machine learning approaches.

A major element of this course is a group project, where participants will be organised in small groups to work together on a challenge set by the project mentors. These will allow participants to explore the bioinformatics tools and resources introduced in the course and to apply these to a set problem, providing hands-on experience of relevance to their own research. The group work will culminate in a presentation session involving all participants on the final day of the course, giving an opportunity for wider discussion on the benefits and challenges of integrating data. You may refer to the previous group projects that were organised for this course in February 2021.

Virtual course

The course will involve participants learning via pre-recorded lectures, live presentations, and trainer Q&A sessions. The content will be delivered over Zoom, with additional text communication over Slack.

Computational practicals will be run 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. Trainers will be available to provide support, answer questions, and further explain the analysis during these practicals.

Participants will need to be available between the hours of 09:30 - 18:00 GMT each day of the course

Who is this course for?

This introductory course is aimed at biologists who are embarking on multiomics projects and computational biologists/bioinformaticians who wish to gain a better knowledge of the biological challenges presented when working with integrated datasets.

Some practical sessions in the course require a basic understanding of the Unix command line and the R statistics package. If you are not already familiar with these then please ensure that you complete these free tutorials before you attend the course:

What will I learn?

Learning outcomes

After this course you should be able to: 

  • Discuss motivations for working in an integrated manner 
  • Describe the importance of data standards and the collection of metadata 
  • Identify challenges for bringing different data types together 
  • Use a range of bioinformatics tools to organise and visualise biological data
Course content

During this course you will learn about:

  • Data standards, curation, and ID mapping
  • Quality control for data integration
  • Analysis and visualisation: Cytoscape, Multiomics factor analysis (MOFA), ReactomeGSA, COSMOS, OmicsDI
  • Challenges and best practice for working in an integrated manner with biological data


Ajay Mishra
Tamás Korcsmáros
Earlham Institute
Johannes Griss
Medical University of Vienna
Dezso Modos
Quadram Institute
Marton Olbei
Earlham Institute
Shila Ghazanfar
Sandra Orchard
Elena Lukyanova
Wellcome Sanger Institute
Britta Velten
DKFZ, Heidelberg
Aurelien Dugourd
University of Heidelberg
Helena Cornu
Konstantinos Tsirigos
Gaurhari Dass


The programme below is subject to minor changes.

Times in GMT

Time Topic Trainer
Day 1 – 21 March 2022
09:30 - 10:00 Check-in Ajay Mishra and Juanita Riveros Cuestas
10:00 - 10:30 Welcome and introductions Ajay Mishra
10:35 - 11:45 Keynote: Multiple ways to integrate multi-omics data - case studies from studying human diseases (Lecture recap and Q&A) Tamás Korcsmáros
11:45 - 12:00 Break  
12:00 - 12:45 Quality issues - Data standards, curation, ontologies, and metadata Sandra Orchard
12:45 - 13:45 Break  
13:45 - 14:45 Flash talks  
14:45 - 14:50 Break  
14:50 - 15:50 Introduction to multiomics integration using COSMOS Aurelien Dugourd
15:50 - 16:00 Break  
16:00 - 17:30 Group project introduction and discussion Project mentors
17:30 End of day  
Day 2 – 22 March 2022
09:45 - 10:00 Morning challenge  
10:00 - 11:15 Multiomics comparative pathway analysis using ReactomeGSA Johannes Griss
11:15 - 11:30 Break  
11:30 - 12:30 Introductory lecture on stats methods Britta Velten
12:30 - 13:30 Break  
13:30 - 14:30 Multi-Omics Factor Analysis (MOFA) Britta Velten
14:30 - 14:45 Break  
14:45 - 15:30 Flash talks  
15:30 - 18:00 Group project  
18:00 End of day  
Day 3 – 23 March 2022
09:45 - 10:00 Morning challenge  
10:00 - 11:00 Introduction to networks and pathways Marton Olbei
11:00 - 11:15 Break  
11:15 - 11:45 ID mapping Dezso Modos
11:45 - 12:15 Hands-on data integration with Cytoscape (Interactive session) Dezso Modos and Marton Olbei 
12:15 - 13:00 Break  
13:00 - 14:00 Hands-on data integration with Cytoscape (Interactive session) Dezso Modos and Marton Olbei 
14:00 - 14:15 Break  
14:15 - 15:15 Flash talks  
15:15 - 15:30 Break  
15:30 -18:00 Group project  
18:00 End of day  
Day 4 – 24 March 2022
09:45 - 10:00 Morning challenge  
10:00 - 10:50 Open Targets platform: integrating omics data for drug discovery Helena Cornu and Kostas Tsirigos
10:50 - 11:00 Break  
11:00 - 12:30 Keynote: about single-cell data integration Shila Ghazanfar
12:30 - 13:30 Break  
13:30 - 14:30 Flash talks  
14:30 - 14:45 Break  
14:45 - 15:30 Omics Discovery Index Gaurhari Dass
15:30 - 15:40 Break  
15:40 - 18:00 Project work  
18:00 End of day  
Day 5 – 25 March 2022
09:45 - 10:00 Morning challenge  
10:00 - 12:30 Group project wrap up and preparation for short presentation  
12:30 - 13:30 Break  
13:30 - 15:00 Presentations and group discussion with the organisers  
15:00 - 15:30 Feedback and course wrap up Ajay Mishra
15:30 End of course  

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 experience
    • 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 3rd December.

Incomplete applications will not be considered.

All applicants will be informed of the status of their application (successful, waiting list, rejected) by 20th December.

This course has ended

21 - 25 March 2022
Juanita Riveros

  • Isidro Cortes-Ciriano
  • Tamás Korcsmáros
    Earlham Institute
  • Ajay Mishra
  • Evangelia Petsalaki

Share this event with: