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Nat Commun. 2018 Feb 12;9(1):632. doi: 10.1038/s41467-018-03005-5.

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

Author information

1
Zürich Research Lab, IBM, Säumerstrasse 4, 8803, Rüschlikon, Switzerland.
2
Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland.
3
Molecular Life Science Ph.D. Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, 8057 Zürich, Switzerland.
4
BestMile SA, EPFL Innovation Park, Building D, 1015 Lausanne, Switzerland.
5
Institute of Molecular Life Sciences, University of Zürich, Winterthurerstrasse 190, 8057, Zürich, Switzerland. bernd.bodenmiller@imls.uzh.ch.
6
Zürich Research Lab, IBM, Säumerstrasse 4, 8803, Rüschlikon, Switzerland. mrm@zurich.ibm.com.

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.

PMID:
29434325
PMCID:
PMC5809393
DOI:
10.1038/s41467-018-03005-5
[Indexed for MEDLINE]
Free PMC Article

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