Using MOFA for integration of omics data, autumn session

Using MOFA for integration of omics data, autumn session



Start date:

31 August 2020


General context

This course consists of a live hands-on session. 

Depending on the status of COVID19, the hands-on session can be face to face or online.

Please register if you're interested in this training. One month after we reach 15 registrations we will try to organize the training. 


This training provides an introduction to Multi-Omics Factor Analysis (MOFA) for the integration of different omic data sets in an unsupervised fashion. It will enable you to run MOFA on multi-omic data, identify and explore the major drivers of variations across omics and use the inferred factors in various downstream analyses.

This training is organized in collaboration with the Helis Academy. More information see



Participants can analyze their own data in the course.

  • What kind of preprocessing of the data is required for MOFA?
  • How to train MOFA on a multi-omic data set?
  • How to interpret the MOFA factors by their loadings, using gene set enrichment or sample ordination?
  • How to use MOFA for downstream analyses including regression, classification or clustering?
  • How to impute missing values with MOFA?
  • How to select the number of factors and compare different MOFA fits?
Required skills

Familiarity with R and RStudio. If you have no experience with R you should follow the Basic statistics in R training first. 

Software demonstrated

MOFA (Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets) -


Ricard Argelaguet

Predoctoral Fellow in the Stegle  and Marioni research group of the European Bioinformatics Institute