visualization-quantification-high-dimensional-cytometry-data-using

Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

The complexity of data generated by mass cytometry has necessitated new tools to rapidly visualize analytic outcomes. Clustering methods like Cytosplore ...

Leiden University Medical Center

Multi-parametric flow and mass cytometry allows exceptional high-resolution exploration of the cellular composition of the immune system. A large panel of computational tools have been developed to analyze the high-dimensional landscape of the data generated. Analysis frameworks such as FlowSOM or Cytosplore incorporate clustering and dimensionality reduction techniques and include algorithms allowing visualization of multi-parametric cytometric analysis. To additionally provide means to quantify specific cell clusters and correlations between samples, we developed an R-package, called , for further downstream analysis. Specifically,  enables the visualization and quantification of cell clusters for an efficient discovery of cell populations associated with diseases or physiology. We used  on mass and flow cytometry datasets based on the modulation of the immune system upon immunotherapy. With  we rapidly generated visual representations of group-related immune cell clusters and showed correlations with the immune system composition. We discovered macrophage subsets that significantly decrease upon cancer immunotherapy and distinct prime-boost effects of prophylactic vaccines on the myeloid compartment.  is a time-efficient tool for comprehensive cytometric analysis to reveal immune signatures and correlations.  is available at Bioconductor.

Koen Stam

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