Introduction to multiomics data integration and visualisation

With the increase in the volume of data across the whole spectrum of biology, more opportunities as well as challenges have been created to identify novel perspectives and answer questions in life sciences. This may also include public domain data, which can provide added value to data derived through researcher’s own work and inform experimental design. This introductory course will highlight the challenges that researchers face in integrating multiomics data sets using biological examples. The course will focus on the use of public data resources and open access tools for enabling integrated working, with an emphasis on data visualisation. This course will not include systems biology modelling or machine learning.

A major element of this course is a group project, where participants will be placed in small groups to work together on a challenge set by trainers from EMBL-EBI data resource and research teams. This allows people 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.

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 knowledge of the biological challenges 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), iCluster
  • Challenges and best practice for working in an integrated manner with biological data 


Ricard Argelaguet
Sandra Orchard
Rachel Lyne
University of Cambridge, UK
Melissa Burke
Pablo Porras Millan
Ajay Mishra
Asier Gonzalez
Yasset Perez Riverol
Lee Larcombe
Tamas Korcsmáros
Earlham Insititute, UK
Manik Garg
Gosia Trynka
Wellcome Trust Sanger Institute, UK
Francesca Ciccarelli
The Fancis Crick Institute, UK
Alejandro Brenes Murillo
University of Dundee, UK
Swee Hoe Ong
Wellcome Trust Sanger Institute, UK
Jacques Serizay
Gurdon Institute, Cambridge, UK
Denise Carvalho-Silva


Day 1 – Monday 02 March 2020
Issues and data types
09:00-09:30 Arrival and tea/coffee  
09:30-10:00 Welcome and introductions Ajay Mishra
10:00-10:30 Promises and pitfalls Lee Larcombe
10:30-10:45 Tea/coffee break  
10:45-11:30 Introduction to data resources Lee Larcombe, Melissa Burke and Ajay Mishra
11:30-12:30 ID Mapping Pablo Porras Millan
12:30-13:30 Lunch  
13:30-14:30 Quality issues - Data standards, curation, ontologies and metadata Sandra Orchard
14:30-15:30 Multiple ways to integrate multi-omics data - case studies from studying human diseases Tamás Korcsmáros
15:30-16:00 Tea/coffee break  
16:00-17:30 Introduction to group projects Jacques Serizay and Manik Garg
17:30 End of the day  
17:45 Check-in to accommodation  
18:30 Evening meal Hinxton Hall Restaurant
Day 2 – Tuesday 03 March 2020
MOFA + Stats methods
08:45 Arrival  
09:00-09:30 5 minute project check-in All
09:30-10:30 Keynote: Integrating GWAS variants with functional genomics data to identify disease causal cell types and genes Gosia Trynka
10:30-11:00 Tea/coffee break  
11:00-12:00 Introductory lecture on stats methods Ricard Argelaguet
12:00-12:45 Lunch  
12:45-13:30 Poster session All
13:30-15:30 Multi-Omics Factor Analysis (MOFA) Ricard Argelaguet
15:30-15:45 Tea/coffee break  
15:45-17:45 Project work continued All
17:45 End of the day  
18:30 Evening meal Hinxton Hall Restaurant
Day 3 – Wednesday 04 March 2020
Network analysis
09:00 Arrival  
09:15-10:30 Introduction to networks and pathways Pablo Porras Millan
10:30-11:00 Tea/coffee break  
11:00-12:30 Hands-on data integration with Cytoscape Pablo Porras Millan
12:30-13:30 Lunch  
13:30-14:30 Keynote: Multi-omic characterisation reveals proteome specific trans effects in autosomal chromosomes correlating with erosion of X chromosome inactivation Alejandro Brenes Murillo
14:30-15:30 Project work All
15:30-16:00 Tea/coffee break  
16:00-17:30 Project work continued All
17:30 End of the day  
18:30 Evening meal Hinxton Hall Restaurant
Day 4 – Thursday 05 March 2020
08:45 Arrival  
09:00-10:00 Open Targets Platform: Integrated resource for drug discovery Denise Carvalho-Silva and Asier Gonzalez
10:00-10:30 Tea/coffee break  
10:30-11:00 Omics Discovery Index Yasset Perez-Riverol
11:00-12:30 Open tools for data integration - hands on example with InterMine Rachel Lyne and InterMine team
12:30-13:30 Lunch  
13:30-14:30 Keynote: Data integration to predict cancer drivers Francesca Ciccarelli
14:30-15:30 Project work All
15:30-16:00 Tea/coffee break  
16:00-17:30 Project work continued All
17:30 End of the day  
18:30 Evening meal The Red Lion, Hinxton
Day 5 – Friday 06 March 2020
Data analysis and presentations
08:45 Arrival  
09:00-10:00 Finalise presentations All
10:00-10:30 Tea/coffee break  
10:30-12:30 Presentations All
12:30-12:45 Feedback and course wrap up All
12:45-13:30 Lunch  
13:30 Shuttle to Station Road, Cambridge  

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:

  1. Complete the online application form
  2. Submit a Microsoft Word (.docx) document containing three short paragraphs with a biography, work history and description of your current research interests; each paragraph should be no more than 100 words
  3. Provide a letter of support from a supervisor or a senior co-worker explaining why you should be selected for this course

Please submit all documents to Meredith Willmott ( by 12:00 GMT on Friday 22 November, 2019

Incomplete applications will not be considered.

All participants are expected to present a poster that will be displayed during the course outside the training room. Please send your poster in PDF format to Meredith Willmott ( and we will print it on campus. 
All posters should:

  • be A2 in size - 420mm x 594 mm 
  • be in a portrait orientation
  • include your photograph and contact information

We cannot display posters of a different size or orientation.

We expect the posters to act as a talking point between you, other participants and the trainers on the course. The posters will be displayed throughout the week so people can view them during breaks and lunch. They should give the reader an idea of the work you are engaged in, what you are planning to do next, and anything of interest that might be useful for sharing with the gathered participants.

Accommodation will be provided in the Wellcome Genome Campus Conference Centre Monday-Friday inclusive. Please contact the Conference Centre directly if you wish to arrange to stay additional nights. The course fee includes breakfast and evening meals at Hinxton Hall and the Red Lion Pub in nearby Hinxton village, as well as breaks and lunches outside the EMBL-EBI training rooms.

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02 - 06 March 2020
European Bioinformatics Institute United Kingdom
Meredith Willmott

  • Ajay Mishra
  • Melissa Burke
  • Pablo Porras Millan
  • Evangelia Petsalaki

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