Using MOFA for integration of omics data, online
General context
This course consists of an online demo/hands-on session and an online Q&A session.
Participants of this course are encouraged to also attend Challenges in omics data integration
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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 https://helisacademy.com/nl/data-analysis-stewardship
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?
Familiarity with R and RStudio. If you have no experience with R you should follow the Basic statistics in R training first.
MOFA (Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets) - http://msb.embopress.org/content/14/6/e8124
Trainers
Ricard Argelaguet
Research Scientist, Altos Labs UK.