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    Cytosplore: Interactive Immune Cell Phenotyping for Large Single-Cell Datasets

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    Date
    2016
    Author
    Höllt, Thomas
    Pezzotti, Nicola
    Unen, Vincent van
    Koning, Frits
    Eisemann, Elmar ORCID
    Lelieveldt, Boudewijn P. F.
    Vilanova, Anna
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    Abstract
    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.
    BibTeX
    @article {10.1111:cgf.12893,
    journal = {Computer Graphics Forum},
    title = {{Cytosplore: Interactive Immune Cell Phenotyping for Large Single-Cell Datasets}},
    author = {Höllt, Thomas and Pezzotti, Nicola and Unen, Vincent van and Koning, Frits and Eisemann, Elmar and Lelieveldt, Boudewijn P. F. and Vilanova, Anna},
    year = {2016},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.12893}
    }
    URI
    http://dx.doi.org/10.1111/cgf.12893
    https://diglib.eg.org:443/handle/10
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    • 35-Issue 3
    • EuroVis16: Eurographics Conference on Visualization

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