Courses & Events

This two-day course will explain basic concepts in human genetics and cover some historical background, fundamental knowledge of molecular biology, an introduction to Mendelian and complex genetics, technical aspects and applications of sequencing and array technologies, and the use of DNA technologies in society. The section on Mendelian genetics will address different approaches for detecting mutations in families segregating hereditary diseases, while the section on complex genetics will discuss the history and applications of genome-wide association studies (GWAS) in populations.

The analysis of DNA variations, including Single Nucleotide Polymorphisms (SNPs), is a standard research approach for understanding the causes of disease - particularly complex diseases such as diabetes, osteoporosis, cancer and Alzheimer’s disease. Since the completion of the Human Genome Project, the field has evolved rapidly, driven by large-scale projects and databases such as the UK Biobank, TopMed, and the GWAS Catalog. New technologies continue to emerge, including Next Generation Sequencing, functional genomics, and the development of Polygenic Risk Scores.

The analysis of microbial communities has been greatly advanced by next-generation sequencing techniques over the past decade. Microbiota - particularly those of the gut - have now been linked to a variety of diseases and traits. Analytical approaches, such as alpha and beta diversity analyses and differential abundance analyses, are evolving rapidly. This course will cover how microbiota profiles are generated and how to analyze these profiles effectively.

This five-day introductory course provides an overview of the field of Genome-Wide Association Studies (GWAS). In the first half of the course, we focus on the biological background necessary to understand GWAS, the principles of study design, and the basic skills required to perform GWAS analyses. In the second half, you will conduct a GWAS and perform post-GWAS analyses to develop a comprehensive understanding of the field.

GWAS is a skill best learned through hands-on practice, which is why this course offers ample opportunities to apply what you’ve learned and build the skills needed to carry out your own GWAS projects.

With the advent of numerous large genetic databases and resources, opportunities to conduct Mendelian Randomization (MR) studies are rapidly increasing. The MR approach uses genetic variants as instrumental variables to test or estimate the potential causal effect of a (non-genetic) risk factor on a disease or health-related outcome. When its assumptions are met, MR can overcome many of the limitations of associations drawn from observational epidemiology and help prioritize potential targets for pharmaceutical and public health interventions.

This three-day course aims to equip participants with the tools needed to first understand the basic principles of causal inference underlying MR, and then to perform an MR study. The course will cover both simple and advanced statistical methods for causal inference within one-sample and two-sample Mendelian Randomization frameworks.

This course offers an introduction to working with Next-Generation Sequencing (NGS) data. It is designed for individuals who have access to NGS data and want to learn how to process, analyze, and interpret it, as well as understand the possibilities and limitations of NGS technologies. Lectures are complemented by practical sessions, providing participants with hands-on experience using a range of tools and techniques.

This course provides an introduction to the analysis of proteomics and metabolomics data - two emerging approaches that enhance our understanding of molecular pathways and hold promise for identifying novel biomarkers for complex diseases. It offers an excellent introduction to these ‘omic’ fields and gives participants the opportunity to analyze example datasets.

This course provides an introduction to the analysis and interpretation of epigenomics and transcriptomics data in the context of population-based studies. Participants will be introduced to both types of omics data, covering their technical background, quality control and normalization, analytical approaches, result interpretation, and follow-up analyses. The course includes short practical sessions, offering hands-on experience working with epigenomic and transcriptomic data using R.

Genome-wide association studies (GWAS) are a powerful approach for investigating the genetic basis of complex traits and disorders. This course combines lectures that provide a conceptual framework with practical sessions covering essential topics such as quality control, genotype imputation, methods to detect and correct for population stratification, meta-analysis, and genomic annotation of GWAS signals. An overview of the most widely used statistical tools will be complemented by hands-on computer exercises focusing on the analysis of quantitative traits and disease outcomes. Participants will learn state-of-the-art procedures for conducting GWAS.

Our understanding of the link between the human gut microbiome and health outcomes is rapidly expanding. The diverse microbial communities within the human body influence cellular responses and shape many aspects of human physiology, revealing critical roles in both health and disease processes. From an epidemiological perspective, microbiome data analysis aims to elucidate the composition of microbial communities, their variation in response to environmental factors, and their involvement in health outcomes at the population level. Thanks to advances in next-generation sequencing technology, microbiome profiling is now feasible in large epidemiological studies - introducing new challenges for the analysis and interpretation of microbiome data.