Exploration of large single-cell data with Cytosplore and HSNE, Thomas Höllt

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Description

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.
Period20 Mar 2018
Event typeGuest talk
LocationAustriaShow on map

Fields of science

  • 102008 Computer graphics
  • 102 Computer Sciences
  • 102020 Medical informatics
  • 103021 Optics
  • 102015 Information systems
  • 102003 Image processing

JKU Focus areas

  • Engineering and Natural Sciences (in general)