Publication

Critical assessment of automated flow cytometry data analysis techniques

Aghaeepour, N., Finak, G., Hoos, H., Mosmann, T. R., Brinkman, R., Gottardo, R., Scheuermann, R. H., FlowCAP Consortium & DREAM Consortium, Mar-2013, In : Nature Methods. 10, 3, p. 228-238 11 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Aghaeepour, N., Finak, G., Hoos, H., Mosmann, T. R., Brinkman, R., Gottardo, R., ... DREAM Consortium (2013). Critical assessment of automated flow cytometry data analysis techniques. Nature Methods, 10(3), 228-238. https://doi.org/10.1038/NMETH.2365

Author

Aghaeepour, Nima ; Finak, Greg ; Hoos, Holger ; Mosmann, Tim R. ; Brinkman, Ryan ; Gottardo, Raphael ; Scheuermann, Richard H. ; FlowCAP Consortium ; DREAM Consortium. / Critical assessment of automated flow cytometry data analysis techniques. In: Nature Methods. 2013 ; Vol. 10, No. 3. pp. 228-238.

Harvard

Aghaeepour, N, Finak, G, Hoos, H, Mosmann, TR, Brinkman, R, Gottardo, R, Scheuermann, RH, FlowCAP Consortium & DREAM Consortium 2013, 'Critical assessment of automated flow cytometry data analysis techniques', Nature Methods, vol. 10, no. 3, pp. 228-238. https://doi.org/10.1038/NMETH.2365

Standard

Critical assessment of automated flow cytometry data analysis techniques. / Aghaeepour, Nima; Finak, Greg; Hoos, Holger; Mosmann, Tim R.; Brinkman, Ryan; Gottardo, Raphael; Scheuermann, Richard H.; FlowCAP Consortium; DREAM Consortium.

In: Nature Methods, Vol. 10, No. 3, 03.2013, p. 228-238.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Aghaeepour N, Finak G, Hoos H, Mosmann TR, Brinkman R, Gottardo R et al. Critical assessment of automated flow cytometry data analysis techniques. Nature Methods. 2013 Mar;10(3):228-238. https://doi.org/10.1038/NMETH.2365


BibTeX

@article{c19047c71d644dcf889d82d6a6492725,
title = "Critical assessment of automated flow cytometry data analysis techniques",
abstract = "Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.",
keywords = "SYSTEMS BIOLOGY, CELLULAR HIERARCHY, ACUTE-LEUKEMIA, STANDARDIZATION, IDENTIFICATION, CHALLENGES, CONTINUUM, CELLS",
author = "Nima Aghaeepour and Greg Finak and Holger Hoos and Mosmann, {Tim R.} and Ryan Brinkman and Raphael Gottardo and Scheuermann, {Richard H.} and {FlowCAP Consortium} and {DREAM Consortium}",
note = "Relation: https://www.rug.nl/research/jbi/ Rights: University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science",
year = "2013",
month = "3",
doi = "10.1038/NMETH.2365",
language = "English",
volume = "10",
pages = "228--238",
journal = "Nature Methods",
issn = "1548-7105",
publisher = "Nature Publishing Group",
number = "3",

}

RIS

TY - JOUR

T1 - Critical assessment of automated flow cytometry data analysis techniques

AU - Aghaeepour, Nima

AU - Finak, Greg

AU - Hoos, Holger

AU - Mosmann, Tim R.

AU - Brinkman, Ryan

AU - Gottardo, Raphael

AU - Scheuermann, Richard H.

AU - FlowCAP Consortium

AU - DREAM Consortium

N1 - Relation: https://www.rug.nl/research/jbi/ Rights: University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science

PY - 2013/3

Y1 - 2013/3

N2 - Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.

AB - Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.

KW - SYSTEMS BIOLOGY

KW - CELLULAR HIERARCHY

KW - ACUTE-LEUKEMIA

KW - STANDARDIZATION

KW - IDENTIFICATION

KW - CHALLENGES

KW - CONTINUUM

KW - CELLS

U2 - 10.1038/NMETH.2365

DO - 10.1038/NMETH.2365

M3 - Article

VL - 10

SP - 228

EP - 238

JO - Nature Methods

JF - Nature Methods

SN - 1548-7105

IS - 3

ER -

ID: 2405696