Critical assessment of automated flow cytometry data analysis techniques.
Nat Methods
; 10(3): 228-38, 2013 Mar.
Article
em En
| MEDLINE
| ID: mdl-23396282
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
/
Biologia Computacional
/
Citometria de Fluxo
Tipo de estudo:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article