PIMS - UVictoria Distinguished Lecture: Raphael Gottardo

New single-cell technologies such as single-cell RNA-seq and high-dimensional flow cytometry enable the unprecedented interrogation of single-cell phenotypes (and functions) under various biological conditions. A common statistical problem is the discovery and characterization of such cell phenotypes from single-cell data and their relationship to clinical outcomes including response to cancer immunotherapy or protection after vaccination. During this talk, I will present some statistical methodology we have developed to analyze high-dimensional single-cell data. I will illustrate these novel approaches using several datasets that we have recently generated to characterize immune responses in the context of vaccination and immunotherapy.