This course is hosted by the EMBL European Bioinformatics Institute (EMBL-EBI).

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 the researcher’s own work and inform experimental design.

This introductory course will highlight the challenges that researchers face in integrating multi-omics 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 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, allowing wider discussion on the benefits and challenges of integrating data.

Who is this course for?

This course is aimed at biologists who are beginning to work on multi-omics data integration projects and beginner 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 programming language.

After this course you should be able to:

- Discuss motivations for working in an integrated manner
- Identify challenges for bringing different data types together
- Use a range of bioinformatics tools to analyse and visualise biological data

During this course you will learn about:

-Data curation and ID mapping
-Quality control for data integration
-Analysis and visualisation: Cytoscape, Multi-omics factor analysis (MOFA), COSMOS
-Challenges and best practices for working in an integrated manner with biological data