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CellCycleTRACER accounts for cell cycle and volume in mass cytometry data.

Maria Anna RapsomanikiXiao-Kang LunStefan WoernerMarco LaumannsBernd BodenmillerMaría Rodríguez Martínez
Published in: Nature communications (2018)
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.
Keyphrases
  • cell cycle
  • single cell
  • cell proliferation
  • electronic health record
  • cell therapy
  • big data
  • rheumatoid arthritis
  • mesenchymal stem cells
  • data analysis
  • machine learning
  • cell death