Multivariate Analysis for -Omics Data Integration: Principles and Applications

29 November to 2 December 2021

Grégoire Rossier

Dr. Florence Mehl, SIB Lausanne
Dr. Anouk Berger, CIRC-OMS, France

Dr. Ricard Argelaguet, European Bioinformatics Institute, UK

Dr. Sébastien Déjean, Institut de Mathématique de Toulouse, France

Dr. Vivian Viallon, CIRC-OMS, France

Dr. Reza Salek, CIRC-OMS, France

Dr. Matthieu Foll, CIRC-OMS, France

Dr. Pietro Ferrari, CIRC-OMS, France

Dr. Florence Mehl, SIB / Vital-IT, Lausanne, Suisse

Dr. Thuong Van Du Tran, SIB / Vital-IT, Lausanne, Suisse

Researchers often have access or generate multiple -omics data within a single study. Although each –omics data has been traditionally analysed in isolation, combining possibly complementary data can yield a better understanding of the mechanisms involved in the biological processes. Several integrative approaches are now available to combine such data, which can be regarded as extensions of the standard Principal Component Analysis (PCA).

In this 3.5 day workshop, we will provide an overview of omics data structures, and present different statistical approaches, from simple PCA to more advanced multi-omics dimension reduction methods. For each method, we will cover both its principle and practical aspects. In particular, the course will include dedicated sessions covering the application of the MOFA and mixOmics packages by their respective developers. We plan to have an interactive course with substantial time allocated for discussions.

https://www.sib.swiss/training/course/20211129_DI

Day -7: Introduction of the attendees & lecturers. Ice-breaker discussion + technical/laptop setup check (~2 hours)

Day 1: Overview of omics data structures and standard dimension reduction techniques.

Day 2: MOFA (Multi-Omics Factor Analysis) - unsupervised multiomics data integration.

Day 3: MixOmics package - supervised multiomics data integration methods.

Day 4 (1/2 day): Downstream analyses and interpretation of the factors

Venue and Time

The course will be hosted in the International Agency for Research on Cancer (IARC-WHO), 150 Cours Albert Thomas 69008 Lyon, France. The participants will get detailed information about a selection of hotels and other arrangements before the course.

The course will start at 9:00 (exception: 10:00 on Monday) and end around 17:00. Precise information will be provided to the participants on due time.

Lyon, France

Audience

This course is addressed to biostatisticians, bioinformaticians and life scientists who analyze omics data from multiple platforms (e.g., metabolomics, proteomics, genomics, transcriptomics) and who want to combine these complementary data to investigate biological mechanisms and identify clusters of individuals

Learning Objectives

At the end of the course, the participants are expected to :

• Understand the principles of dimension reduction techniques for single and multi-omics data, including PCA, PLS, MOFA, DIABLO and MINT.
• Be able to apply these techniques to their data with R

Prerequisites

Knowledge / competencies

• Basic knowledge of some omics data of interest
• Basic knowledge or practice of the R software
• Basic knowledge of algebra (vectors, matrices) and statistics (random variable, variance, covariance, correlation)

In order to better evaluate if your profile & background match the requirements of this course, would you please take the following survey after application: https://forms.gle/eSmoQkr7eZ43gZgq9

Technical

Own laptop, with R and RStudio softwares installed and, if possible, the mixOmics and MOFA2 packages. Install can be checked & troubleshooted during a pre-workshop online session about 7 days before the start of the workshop.

Registration on: https://www.sib.swiss/training/course/20211129_DI

Additional information

Coordination: Sandrine Montigny (IARC), Grégoire Rossier (SIB).

COVID-19: Mandatory Health Pass necessary to attend the course. A health pass consists of presenting, in digital or paper format any of the following three types of proof, together with an ID:

• Proof of having completed a vaccination programme (two doses of an EU-approved vaccine: Pfizer, Moderna, AstraZeneca or Johnson & Johnson).
• A negative PCR or antigen test taken within the last 72 hours (which will need to be renewed at least once during the course dates)
• Proof of recovery from COVID-19 more than 11 days ago and less than 6 months ago."

A medical certificate attesting to a medical contraindication to receiving a dose of all the COVID-19 vaccines can be submitted instead of the 3 documents mentioned above.

For more information, please contact [email protected].

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For more information, please contact [email protected].