Thomas Höllt, Delft University of Technology
Exploration of large single-cell data with Cytosplore and HSNE
March 20th, 2018, 10:00am CET,
Room: Science Park Building 3, Room 063
Single-cell analysis through mass cytometry has become an increasingly important tool for immunologists to study the immune system in health and disease. Mass cytometry creates a high-dimensional description vector for single cells by time-of-flight measurement. In this talk we will discuss several hierarchical approaches to the interactive exploration of large single cell data using a combination clustering and t-Distributed Stochastic Neighborhood Embedding (t-SNE) as well as the recently introduced Hierarchical Stochastic Neighborhood Embedding (HSNE). Based on the application to a study on gastrointestinal disorders we show hat HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed. Finally we will discuss CyteGuide, a tool to guide the exploration of HSNE hierarchies.
About the Speaker:
Thomas Höllt received the Diplom (MSc) in computational visualistics from the University of Koblenz-Landau, Germany, in 2008, and the PhD in computer science from the King Abdullah University of Science and Technology, Saudi Arabia, in 2013. He holds positions as an Assistant Professor in the Computational Biology Center (https://www.lcbc.nl) at the Leiden University Medical Center and as a research fellow at Delft University of Technology.