Mass Cytometry pp 281-294 | Cite as

Analysis of High-Dimensional Phenotype Data Generated by Mass Cytometry or High-Dimensional Flow Cytometry

  • Branko Cirovic
  • Natalie Katzmarski
  • Andreas SchlitzerEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1989)


Recent advances in single cell multi-omics methodologies significantly expand our understanding of cellular heterogeneity, particularly in the field of immunology. Today’s state-of-the-art flow and mass cytometers can detect up to 50 parameters to comprehensively characterize the identity and function of individual cells within a heterogeneous population. As a consequence, the increasing number of parameters that can be detected simultaneously also introduces substantial complexity for the experimental setup and downstream data processing. However, this challenge in data analysis fostered the development of novel bioinformatic tools to fully exploit the high-dimensional data. These tools will eventually replace cumbersome serial, manual gating in the two-dimensional space driven by a priori knowledge, which still represents the gold standard in flow cytometric analysis, to meet the needs of the today’s immunologist. To this end, we provide guidelines for a high-dimensional cytometry workflow including experimental setup, panel design, fluorescent spillover compensation, and data analysis.

Key words

Mass cytometry Flow cytometry High-dimensional cytometry Data analysis 


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Branko Cirovic
    • 1
  • Natalie Katzmarski
    • 1
  • Andreas Schlitzer
    • 1
    Email author
  1. 1.Myeloid Cell Biology, Life and Medical Sciences InstituteUniversity of BonnBonnGermany

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