flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry

Lux M, Brinkman RR, Chauve C, Laing A, Lorenc A, Abeler-Dörner L, Hammer B (2018)
Bioinformatics 34(13): 2245-2253.

Zeitschriftenaufsatz | E-Veröff. vor dem Druck | Englisch
 
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Autor*in
Lux, MarkusUniBi; Brinkman, Ryan Remy; Chauve, Cedric; Laing, Adam; Lorenc, Anna; Abeler-Dörner, Lucie; Hammer, BarbaraUniBi
Abstract / Bemerkung
Motivation Identification of cell populations in flow cytometry is a critical part of the analysis and lays the groundwork for many applications and research discovery. The current paradigm of manual analysis is time consuming and subjective. A common goal of users is to replace manual analysis with automated methods that replicate their results. Supervised tools provide the best performance in such a use case, however they require fine parameterization to obtain the best results. Hence, there is a strong need for methods that are fast to setup, accurate and interpretable. Results flowLearn is a semi-supervised approach for the quality-checked identification of cell populations. Using a very small number of manually gated samples, through density alignments it is able to predict gates on other samples with high accuracy and speed. On two state-of-the-art data sets, our tool achieves median(F1)-measures exceeding 0.99 for 31%, and 0.90 for 80% of all analyzed populations. Furthermore, users can directly interpret and adjust automated gates on new sample files to iteratively improve the initial training.
Stichworte
Flow Cytometry; Machine Learning; Gating
Erscheinungsjahr
2018
Zeitschriftentitel
Bioinformatics
Band
34
Ausgabe
13
Seite(n)
2245-2253
ISSN
1367-4803
eISSN
1460-2059
Page URI
https://pub.uni-bielefeld.de/record/2917896

Zitieren

Lux M, Brinkman RR, Chauve C, et al. flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry. Bioinformatics. 2018;34(13):2245-2253.
Lux, M., Brinkman, R. R., Chauve, C., Laing, A., Lorenc, A., Abeler-Dörner, L., & Hammer, B. (2018). flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry. Bioinformatics, 34(13), 2245-2253. doi:10.1093/bioinformatics/bty082
Lux, Markus, Brinkman, Ryan Remy, Chauve, Cedric, Laing, Adam, Lorenc, Anna, Abeler-Dörner, Lucie, and Hammer, Barbara. 2018. “flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry”. Bioinformatics 34 (13): 2245-2253.
Lux, M., Brinkman, R. R., Chauve, C., Laing, A., Lorenc, A., Abeler-Dörner, L., and Hammer, B. (2018). flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry. Bioinformatics 34, 2245-2253.
Lux, M., et al., 2018. flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry. Bioinformatics, 34(13), p 2245-2253.
M. Lux, et al., “flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry”, Bioinformatics, vol. 34, 2018, pp. 2245-2253.
Lux, M., Brinkman, R.R., Chauve, C., Laing, A., Lorenc, A., Abeler-Dörner, L., Hammer, B.: flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry. Bioinformatics. 34, 2245-2253 (2018).
Lux, Markus, Brinkman, Ryan Remy, Chauve, Cedric, Laing, Adam, Lorenc, Anna, Abeler-Dörner, Lucie, and Hammer, Barbara. “flowLearn: Fast and precise identification and quality checking of cell populations in flow cytometry”. Bioinformatics 34.13 (2018): 2245-2253.

2 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

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