TY - JOUR
T1 - CellCycleTRACER accounts for cell cycle and volume in mass cytometry data
AU - Rapsomaniki, Maria Anna
AU - Lun, Xiao Kang
AU - Woerner, Stefan
AU - Laumanns, Marco
AU - Bodenmiller, Bernd
AU - Martínez, María Rodríguez
N1 - Publisher Copyright:
© 2018 The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85042045208&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85042045208&partnerID=8YFLogxK
U2 - 10.1038/s41467-018-03005-5
DO - 10.1038/s41467-018-03005-5
M3 - Article
C2 - 29434325
AN - SCOPUS:85042045208
SN - 2041-1723
VL - 9
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 632
ER -