- Exploring large data sets.
- Selecting features with methods implementing LASSO-based penalisations.
- Using graphical techniques to better visualise data.
- Understanding and/or applying multivariate projection methodologies to large data sets.
- Understand fundamental principles of multivariate projection-based dimension reduction technique.
- Perform statistical integration and feature selection using recently developed multivariate methodologies.
- Apply those methods to high throughput biological studies, including their own studies.
Summer School on Multivariate data analysis methods
for biological data using the R package mixOmics (passed)
The course is intended for data analysts in the fields of bioinformatics, computational biology and applied
statistics with a good statistical knowledge and a good working knowledge in R. It will be particularly
useful to those interested in:
Results
After completion of this workshop, participants will be able to
