This event has ended. Visit the official site or create your own event on Sched.
Click here to return to main conference site. For a one page, printable overview of the schedule, see this.
View analytic
Tuesday, June 28 • 1:00pm - 1:18pm
Group and sparse group partial least squares approaches applied in a genomics context

Log in to save this to your schedule and see who's attending!

In this talk, I will concentrate on a class of multivariate statistical methods called Partial Least Squares (PLS). They are used for analysing the association between two blocks of ‘omics’ data, which bring challenging issues in computational biology due to their size and complexity. In this framework, we will exploit the knowledge on the grouping structure existing in the data, which is key to more accurate prediction and improved interpretability. For example, genes within the same pathway have similar functions and act together in regulating a biological system. In this context, we developed a group Partial Least Squares (gPLS) method and a sparse gPLS (sgPLS) method. Our methods available through our sgPLS R package are compared through an HIV therapeutic vaccine trial. Our approaches provide parsimonious models to reveal the relationship between gene abundance and the immunological response to the vaccine.


Torsten Hothorn

University of Zurich


Benoit Liquet

University Pau et Pays de L'Adour, ACEMS: Centre of Excellence for Mathematical and Statistical Frontiers, QUT, Australia

Attendees (68)