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Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets
Author(s) -
Höllt T.,
Pezzotti N.,
van Unen V.,
Koning F.,
Eisemann E.,
Lelieveldt B.,
Vilanova A.
Publication year - 2016
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12893
Subject(s) - workflow , mass cytometry , computer science , point (geometry) , data mining , database , biology , mathematics , biochemistry , geometry , gene , phenotype
To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation.