Integrative analysis of multi-omics data

Overview

Funded by EMBO for excellence in the life sciences

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Course overview

Biological and biomedical research frequently employs multiple ‘omics methods (“multi-omics”) to investigate biological systems comprehensively. This approach simultaneously examines various molecular layers (DNA, RNAs, proteins, metabolites) and helps to overcome limitations inherent in individual technologies. Additionally, there is a growing interest towards performing such measurements at single-cell and/or spatial resolutions. Integrating and analysing these complex datasets poses significant challenges. How can we interpret perturbation effects, establish associations between molecular profiles and study variables, or detect latent variables representing key biological elements like cell types or states? Crucially, how can we achieve these goals with statistical robustness and scientific rigour, facilitating clear and convincing reporting?

This course addresses those essential questions, providing participants with foundational mathematical and conceptual understanding of integrative multi-modal data analysis methods. Through hands-on sessions using state-of-the-art datasets, attendees will explore different software tools, assess data quality and results, identify potential pitfalls, evaluate performance, optimise model parameters, interpret outcomes effectively, and embrace open-science practices. Methods covered include multi-table ordination and dimensionality reduction techniques, notably the widely utilised Multi-Omics Factor Analysis (MOFA), developed by the course organisers.

Audience

This course is aimed at PhD students and post-docs in computational biology aiming to improve their skills in multi-omics data integration methodologies.

Learning outcomes

The course will provide researchers with an overview and the theoretical foundations of state-of-the-art methods for multi-modal integration, with a focus on omics data. In practical sessions on relevant real-world examples from single-cell and bulk multi-omics studies, participants will gain familiarity with software implementations and learn about practical aspects, including quality assessment of inputs and outputs, method performance assessment, choice of tuning parameters, interpretation of the model fit and potential pitfalls.

What past participants say about the course

“The course was a fantastic overview of the state-of-the-art in multi-omics integration with exposure to the top methods and researchers in the field. Getting to discuss open problems with the speakers and other participants was invaluable and I’ve made some great connections with other attendees which I hope to continue to develop.” – Eleanor Williams, Wellcome-MRC Cambridge Stem Cell Institute, UK

“The course provides a comprehensive overview of different multiomics data integration techniques with real-life applications and an excellent opportunity to network with fellow participants, speakers, and method developers.” – Adhideb Ghosh, ETH Zurich, Switzerland

Sponsors

Sponsorship opportunities

We offer a variety of event sponsoring possibilities, with the flexibility to select a set sponsorship package or combine individual sponsorship options to suit your event budget. Discounts are available for companies sponsoring multiple events at EMBL Heidelberg. View other conferences, or contact sponsorship@embl.org. for further information.

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