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CellCycleTRACER accounts for cell cycle and volume in mass cytometry data

Author

Listed:
  • Maria Anna Rapsomaniki

    (IBM)

  • Xiao-Kang Lun

    (University of Zürich
    ETH Zürich and University of Zürich)

  • Stefan Woerner

    (IBM)

  • Marco Laumanns

    (IBM
    EPFL Innovation Park, Building D)

  • Bernd Bodenmiller

    (University of Zürich)

  • María Rodríguez Martínez

    (IBM)

Abstract

Recent studies have shown that cell cycle and cell volume are confounding factors when studying biological phenomena in single cells. Here we present a combined experimental and computational method, CellCycleTRACER, to account for these factors in mass cytometry data. CellCycleTRACER is applied to mass cytometry data collected on three different cell types during a TNFα stimulation time-course. CellCycleTRACER reveals signaling relationships and cell heterogeneity that were otherwise masked.

Suggested Citation

  • Maria Anna Rapsomaniki & Xiao-Kang Lun & Stefan Woerner & Marco Laumanns & Bernd Bodenmiller & María Rodríguez Martínez, 2018. "CellCycleTRACER accounts for cell cycle and volume in mass cytometry data," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-03005-5
    DOI: 10.1038/s41467-018-03005-5
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