This introductory course explores the complex interplay between genes and the environment in shaping human phenotypes. Participants will gain knowledge of cohort datasets, environmental readouts, and bioinformatics tools to investigate gene-environment interactions. Ethical and legal frameworks related to data privacy, consent, and genetic discrimination will be discussed. The course also covers computational modelling techniques for integrating genotype and environmental effects. By the end, attendees will be equipped to analyse cohort datasets, make use of computational resources, and interpret the results.
Please note that you will not analyse your own data as part of the course. There will, however, be ample opportunity to discuss your research and ideas with other course participants and trainers
Who is this course for?
This introductory course is aimed at MRes/PhD students, researchers, clinicians, and other professionals working in the fields of genomics, exposomics, epidemiology, or toxicology with an interest in understanding how interactions between genes and the environment underlie human phenotypes. The course will cover the underlying concepts, computational resources, and computational modelling methods available to investigate interactions between genes and the environment (including social, biological, and physical exposures). No prior bioinformatics skills are required although a basic understanding of statistics and Unix experience would be helpful.
Prerequisites
We recommend all successful applicants acquire/brush up on their basic command line skills before attending the course. R Studio experience is also required. There are many tutorials available online and here are some that may be of help.
To complete the following suggested tutorials you may want to install Ubuntu for Windows Users if you are using a computer with a Windows Operating System.
Basic introduction to the Unix environment
Hands-on programming with R
What will I learn?
Learning outcomes
After the course you should be able to:
Discuss the types, limitations, and advantages of human cohort datasets.
Discuss the types, limitations, and advantages of different environmental readouts, including proxies for exposures in human cohorts.
Explain the ethical and legal frameworks governing human data reuse and request access to datasets of interest in compliance with legal and ethical standards.
Use and explain the need for Federated/Trusted Research Environments.
Employ relevant computational methods and resources to investigate gene and environment interactions and interpret the results.
Understand how to apply techniques (GWAS and predictive modelling) to analyse cohort datasets and how to interpret these results.
Course content
During this course you will learn about:
How to predict gene and environment interactions in human cohort datasets: study design, analysis techniques and interpretation.
Tools and services available for investigating gene and environment interaction: GWAS catalogue, EGA, OpenTargets.
Computational modelling strategies to integrate Genotype * Environmental effects.
Ethical and legal frameworks relating to human cohorts considering: privacy and data security, informed consent, issues related to genetic discrimination, and ethical issues related to new technologies.
Trainers
Marc Jan Bonder, EMBL
Maria Cerezo, EMBL-EBI
Tomas Fitzgerald, EMBL-EBI
Amy Louise Foreman, EMBL-EBI
Mallory Freeberg, EMBL-EBI
Xiangyu Jack Ge, Wellcome Sanger Institute
Laura Harris, EMBL-EBI
Emily Jefferson, University of Dundee
Elliot Sollis, EMBL-EBI
Oliver Stegle, EMBL
Roel Vermeulen, Utrecht University
Natàlia Vilor-Tejedor, Barcelona Beta Brain Research Center
Lucia von Bredow, EMBL Bioethics Services
Pu Xia, University of Birmingham