Abstract
Dissecting responses to immunotherapy using high-dimensional single-cell analysis
New single-cell technologies such as single-cell RNA-seq, CITE-seq, and spectral 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 endpoints (e.g., response rate or vaccine efficacy). During this talk, I will present new computational tools we have developed for high-dimensional single-cell data analysis. I will illustrate these novel approaches using several datasets that we have recently analyzed to characterize immune responses in the context of cancer immunotherapy.
