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 trainers from EMBL-EBI data resource and research teams. 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.

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 09:30-17:30 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:

For advanced-level training in using large-scale multiomics data and machine learning to infer biological models you may wish to consider our course on Systems Biology: From large datasets to biological insight.

What will I learn?

Learning outcomes

After this course you should be able to: 

  • Discuss motivations for working in an integrated manner 
  • Comprehend 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 visualistion: Cytoscape, InterMine, Multiomics factor analysis (MOFA), ReactomeGSA
  • Challenges and best practice for working in an integrated manner with biological data


Pablo Porras Millan
Ajay Mishra
Lee Larcombe
nexaSTEM, UK
Sandra Orchard
Tamás Korcsmáros
Earlham Institute, UK
Manik Garg
Andrew Hercules
Yasset Perez-Riverol
Rachel Lyne
University of Cambridge, UK
Magnus Øverlie Arntzen
Norwegian University of Life Sciences, Norway
Johannes Griss
Medical University of Vienna, Austria
Dezso Modos
Quandram Institute Bioscience, UK
Maria Zimmermann
EMBL, Heidelberg, Germany
Marton Olbei
Earlham Institute, UK
Danish Memon
Vy Nguyen
Medical University of Vienna, Austria
Samuel Collombet
EMBL, Heidelberg, Germany
Sergio Contrino
University of Cambridge


Day 1 – Monday 22 February 2021

09:30-10:00 Check-in Ajay Mishra & Jane Reynolds
10:00-10:30 Welcome and introductions Ajay Mishra
10:30-11:00 Promises and pitfalls Lee Larcombe
11:00-11:15 Break  
11:15-12:15 Quality issues - Data standards, curation, ontologies and metadata Sandra Orchard
12:15-13:15 Break  
13:15-14:15 Flash talks   
14:15-14:30 Break  
14:30-15:15 Keynote: Multiple ways to integrate multi-omics data - case studies from studying human diseases (Lecture recap and Q&A) Tamás Korcsmáros
15:15-15:30 Break  
15:30-16:30 Introduction to group projects  
16:30-17:00 Networking/social hour  
17:00 End of day  

Day 2 – Tuesday 23 February 2021

09:45-10:00 Morning challenge  
10:00-11:00 Multiomics comparative pathway analysis using ReactomeGSA Johannes Griss
11:00-11:15 Break  
11:15-12:00 Introductory lecture on stats methods Manik Garg
12:00-12:45 Break  
12:45-13:45 Multi-Omics Factor Analysis (MOFA) Manik Garg
13:45-14:00 Break  
14:00-15:00 Flash talks   
15:00-18:00 Group project  
18:00 End of day  

Day 3 – Wednesday 24 February 2021

09:45-10:00 Morning challenge  
10:00-11:00 Introduction to networks and pathways Pablo Porras Millan
11:00-11:15 Break  
11:15-11:45 ID mapping Pablo Porras Millan
11:45-12:15 Hands-on data integration with Cytoscape (Interactive session) Pablo Porras Millan
12:15-13:00 Break  
13:00-14:00 Hands-on data integration with Cytoscape (Interactive session) Pablo Porras Millan
14:00-14:15 Break  
14:15-15:15 Flash talks   
15:15-15:30 Break  
15:30-17:30 Group Project  
17:30-18:00 Networking/social hour All
18:00 End of day  

Day 4 – Thursday 25 February 2021

09:45-10:00 Morning challenge  
10:00-10:45 Open Targets platform: Integrating omics data for drug discovery Andrew Hercules
10:45-11:00 Break  
11:00-12:00 Keynote: Integrated meta-omics: Bringing uncultured microbes to “life” (Lecture recap and Q&A) Magnus Øverlie Arntzen
12:00-13:00 Break  
13:00-14:00 Flash talks   
14:00-14:15 Break  
14:15-14:45 Omics Discovery Index Yasset Perez-Riverol
14:45-15:00 Break  
15:00-16:00 Biological data analysis using InterMine Rachel Lyne and InterMine team
16:00-16:15 Break  
16:15-18:00 Project work  
18:00 End of day  

Day 5 – Friday 19 February 2021

09:45-10:00 Morning challenge  
10:00-12:00 Group project wrap up and preparation for short presentation  
12:00-13:00 Break  
13:00-14:30 Presentations and group discussion with the organisers  
14:30-15:00 Feedback and course wrap up Ajay Mishra
15:00 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 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 08th January 2021. 

Incomplete applications will not be considered.

All applicants will be informed of the status of their application (successful, waiting list, rejected) by Friday 22nd January 2021. If you have any questions regarding the application process please contact Jane Reynolds (

Participant flash talks

All participants will be asked to give a short presentation about their research work as part of the course. These provide an opportunity to share their research with the other participants and provide a forum for discussion. Further details will be provided following registration


This course has ended

22 - 26 February 2021
Jane Reynolds

  • Pablo Porras Millan
  • Evangelia Petsalaki
  • Ajay Mishra

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