Critical assessment of automated flow cytometry data analysis techniques

Nima Aghaeepour, Greg Finak, Holger Hoos, Tim R. Mosmann, Ryan Brinkman, Raphael Gottardo, Richard H. Scheuermann*, FlowCAP Consortium, DREAM Consortium

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

366 Citaten (Scopus)
39 Downloads (Pure)


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.

Originele taal-2English
Pagina's (van-tot)228-238
Aantal pagina's11
TijdschriftNature Methods
Nummer van het tijdschrift3
StatusPublished - mrt-2013
Extern gepubliceerdJa

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