This course material is part of the "Multiomics Data Analysis and Integration" two-day course of SIB-training and is addressed to beginners wanting to become familiar with the multiomics data analysis and integration.
Researchers often have access or generate multiple omics data (RNAseq, metabolomics, lipidomics, proteomics…) 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 2 days workshop, we will provide an overview of omics data structures, and present different statistical approaches unsupervised and supervised, from simple PCA/PLS to more advanced multi-omics dimension reduction methods (Common Component and Specific Weights Analysis, Multiblock Partial Least Squares). For each method, we will cover both its principle and practical aspects.
Julien Boccard Julien.Boccard@unige.ch (Trainer)
Florence Mehl Florence.Mehl@sib.swiss (Trainer)
Van Du Tran thuong.tran@sib.swiss (Trainer)
Monique Zahn monique.zahn@sib.swiss (Technical Coordinator, SIB training group)
This course is designed for beginner users with the following pre-requisites:
- having performed analyses with at least one type of data (RNAseq, metabolomics…).
- basic R
- basic statistics
- Evaluate your R skills with the
following self-assesment.
You are required to bring your own laptop and have the following installed:
- R and RStudio
- R packages to install before the training:
packages_installation.R
The course will take place at:
CMU, Ctre Médical Universitaire
1 rue Michel-Servet
9 av, de Champel
CH-1211 GENEVE
Wednesday 13 March room: S3
Thursday 14 March 9h - 15h room: D02.1549.a
Thursday 14 March 15h - 17h room: A04.3018
- 9h-10h general introduction
- 10h-17h PCA/PLS theory and exercise
- 9h-17h multiblock analyses theory and exercise