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
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Lux, MarkusUniBi;
Brinkman, Ryan Remy;
Chauve, Cedric;
Laing, Adam;
Lorenc, Anna;
Abeler-Dörner, Lucie;
Hammer, BarbaraUniBi ![](https://pub.uni-bielefeld.de/images/icon_orcid.png)
![](https://pub.uni-bielefeld.de/images/icon_orcid.png)
Einrichtung
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
Urheberrecht / Lizenzen
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.
Daten bereitgestellt von European Bioinformatics Institute (EBI)
2 Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
High-Throughput Analysis of Clinical Flow Cytometry Data by Automated Gating.
Lee H, Sun Y, Patti-Diaz L, Hedrick M, Ehrhardt AG., Bioinform Biol Insights 13(), 2019
PMID: 30983860
Lee H, Sun Y, Patti-Diaz L, Hedrick M, Ehrhardt AG., Bioinform Biol Insights 13(), 2019
PMID: 30983860
Improving the Quality and Reproducibility of Flow Cytometry in the Lung. An Official American Thoracic Society Workshop Report.
Tighe RM, Redente EF, Yu YR, Herold S, Sperling AI, Curtis JL, Duggan R, Swaminathan S, Nakano H, Zacharias WJ, Janssen WJ, Freeman CM, Brinkman RR, Singer BD, Jakubzick CV, Misharin AV., Am J Respir Cell Mol Biol 61(2), 2019
PMID: 31368812
Tighe RM, Redente EF, Yu YR, Herold S, Sperling AI, Curtis JL, Duggan R, Swaminathan S, Nakano H, Zacharias WJ, Janssen WJ, Freeman CM, Brinkman RR, Singer BD, Jakubzick CV, Misharin AV., Am J Respir Cell Mol Biol 61(2), 2019
PMID: 31368812
23 References
Daten bereitgestellt von Europe PubMed Central.
Critical assessment of automated flow cytometry data analysis techniques.
Aghaeepour N, Finak G; FlowCAP Consortium; DREAM Consortium, Hoos H, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH, Dougall D, Khodabakhshi AH, Mah P, Obermoser G, Spidlen J, Taylor I, Wuensch SA, Bramson J, Eaves C, Weng AP, Fortuno ES 3rd, Ho K, Kollmann TR, Rogers W, De Rosa S, Dalal B, Azad A, Pothen A, Brandes A, Bretschneider H, Bruggner R, Finck R, Jia R, Zimmerman N, Linderman M, Dill D, Nolan G, Chan C, El Khettabi F, O'Neill K, Chikina M, Ge Y, Sealfon S, Sugar I, Gupta A, Shooshtari P, Zare H, De Jager PL, Jiang M, Keilwagen J, Maisog JM, Luta G, Barbo AA, Majek P, Vilcek J, Manninen T, Huttunen H, Ruusuvuori P, Nykter M, McLachlan GJ, Wang K, Naim I, Sharma G, Nikolic R, Pyne S, Qian Y, Qiu P, Quinn J, Roth A, Meyer P, Stolovitzky G, Saez-Rodriguez J, Norel R, Bhattacharjee M, Biehl M, Bucher P, Bunte K, Di Camillo B, Sambo F, Sanavia T, Trifoglio E, Toffolo G, Dimitrieva S, Dreos R, Ambrosini G, Grau J, Grosse I, Posch S, Guex N, Keilwagen J, Kursa M, Rudnicki W, Liu B, Maienschein-Cline M, Manninen T, Huttunen H, Ruusuvuori P, Nykter M, Schneider P, Seifert M, Vilar JM., Nat. Methods 10(3), 2013
PMID: 23396282
Aghaeepour N, Finak G; FlowCAP Consortium; DREAM Consortium, Hoos H, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH, Dougall D, Khodabakhshi AH, Mah P, Obermoser G, Spidlen J, Taylor I, Wuensch SA, Bramson J, Eaves C, Weng AP, Fortuno ES 3rd, Ho K, Kollmann TR, Rogers W, De Rosa S, Dalal B, Azad A, Pothen A, Brandes A, Bretschneider H, Bruggner R, Finck R, Jia R, Zimmerman N, Linderman M, Dill D, Nolan G, Chan C, El Khettabi F, O'Neill K, Chikina M, Ge Y, Sealfon S, Sugar I, Gupta A, Shooshtari P, Zare H, De Jager PL, Jiang M, Keilwagen J, Maisog JM, Luta G, Barbo AA, Majek P, Vilcek J, Manninen T, Huttunen H, Ruusuvuori P, Nykter M, McLachlan GJ, Wang K, Naim I, Sharma G, Nikolic R, Pyne S, Qian Y, Qiu P, Quinn J, Roth A, Meyer P, Stolovitzky G, Saez-Rodriguez J, Norel R, Bhattacharjee M, Biehl M, Bucher P, Bunte K, Di Camillo B, Sambo F, Sanavia T, Trifoglio E, Toffolo G, Dimitrieva S, Dreos R, Ambrosini G, Grau J, Grosse I, Posch S, Guex N, Keilwagen J, Kursa M, Rudnicki W, Liu B, Maienschein-Cline M, Manninen T, Huttunen H, Ruusuvuori P, Nykter M, Schneider P, Seifert M, Vilar JM., Nat. Methods 10(3), 2013
PMID: 23396282
A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.
Aghaeepour N, Chattopadhyay P, Chikina M, Dhaene T, Van Gassen S, Kursa M, Lambrecht BN, Malek M, McLachlan GJ, Qian Y, Qiu P, Saeys Y, Stanton R, Tong D, Vens C, Walkowiak S, Wang K, Finak G, Gottardo R, Mosmann T, Nolan GP, Scheuermann RH, Brinkman RR., Cytometry A 89(1), 2015
PMID: 26447924
Aghaeepour N, Chattopadhyay P, Chikina M, Dhaene T, Van Gassen S, Kursa M, Lambrecht BN, Malek M, McLachlan GJ, Qian Y, Qiu P, Saeys Y, Stanton R, Tong D, Vens C, Walkowiak S, Wang K, Finak G, Gottardo R, Mosmann T, Nolan GP, Scheuermann RH, Brinkman RR., Cytometry A 89(1), 2015
PMID: 26447924
viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia.
Amir el-AD, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, Shenfeld DK, Krishnaswamy S, Nolan GP, Pe'er D., Nat. Biotechnol. 31(6), 2013
PMID: 23685480
Amir el-AD, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, Shenfeld DK, Krishnaswamy S, Nolan GP, Pe'er D., Nat. Biotechnol. 31(6), 2013
PMID: 23685480
The International Mouse Phenotyping Consortium: past and future perspectives on mouse phenotyping.
Brown SD, Moore MW., Mamm. Genome 23(9-10), 2012
PMID: 22940749
Brown SD, Moore MW., Mamm. Genome 23(9-10), 2012
PMID: 22940749
Reconstructing cell cycle and disease progression using deep learning.
Eulenberg P, Kohler N, Blasi T, Filby A, Carpenter AE, Rees P, Theis FJ, Wolf FA., Nat Commun 8(1), 2017
PMID: 28878212
Eulenberg P, Kohler N, Blasi T, Filby A, Carpenter AE, Rees P, Theis FJ, Wolf FA., Nat Commun 8(1), 2017
PMID: 28878212
Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium.
Finak G, Langweiler M, Jaimes M, Malek M, Taghiyar J, Korin Y, Raddassi K, Devine L, Obermoser G, Pekalski ML, Pontikos N, Diaz A, Heck S, Villanova F, Terrazzini N, Kern F, Qian Y, Stanton R, Wang K, Brandes A, Ramey J, Aghaeepour N, Mosmann T, Scheuermann RH, Reed E, Palucka K, Pascual V, Blomberg BB, Nestle F, Nussenblatt RB, Brinkman RR, Gottardo R, Maecker H, McCoy JP., Sci Rep 6(), 2016
PMID: 26861911
Finak G, Langweiler M, Jaimes M, Malek M, Taghiyar J, Korin Y, Raddassi K, Devine L, Obermoser G, Pekalski ML, Pontikos N, Diaz A, Heck S, Villanova F, Terrazzini N, Kern F, Qian Y, Stanton R, Wang K, Brandes A, Ramey J, Aghaeepour N, Mosmann T, Scheuermann RH, Reed E, Palucka K, Pascual V, Blomberg BB, Nestle F, Nussenblatt RB, Brinkman RR, Gottardo R, Maecker H, McCoy JP., Sci Rep 6(), 2016
PMID: 26861911
Friedman, 2001
Per-channel basis normalization methods for flow cytometry data.
Hahne F, Khodabakhshi AH, Bashashati A, Wong CJ, Gascoyne RD, Weng AP, Seyfert-Margolis V, Bourcier K, Asare A, Lumley T, Gentleman R, Brinkman RR., Cytometry A 77(2), 2010
PMID: 19899135
Hahne F, Khodabakhshi AH, Bashashati A, Wong CJ, Gascoyne RD, Weng AP, Seyfert-Margolis V, Bourcier K, Asare A, Lumley T, Gentleman R, Brinkman RR., Cytometry A 77(2), 2010
PMID: 19899135
An open-source solution for advanced imaging flow cytometry data analysis using machine learning.
Hennig H, Rees P, Blasi T, Kamentsky L, Hung J, Dao D, Carpenter AE, Filby A., Methods 112(), 2016
PMID: 27594698
Hennig H, Rees P, Blasi T, Kamentsky L, Hung J, Dao D, Carpenter AE, Filby A., Methods 112(), 2016
PMID: 27594698
Keogh, 2001
Fast bayesian optimization of machine learning hyperparameters on large datasets
Klein, Proceedings of Machine Learning Research 54(), 2016
Klein, Proceedings of Machine Learning Research 54(), 2016
Thinking outside the gate: single-cell assessments in multiple dimensions
Kvistborg, Immunity 42(), 2015
Kvistborg, Immunity 42(), 2015
Gating mass cytometry data by deep learning.
Li H, Shaham U, Stanton KP, Yao Y, Montgomery RR, Kluger Y., Bioinformatics 33(21), 2017
PMID: 29036374
Li H, Shaham U, Stanton KP, Yao Y, Montgomery RR, Kluger Y., Bioinformatics 33(21), 2017
PMID: 29036374
Lisboa, 2013
The end of gating? An introduction to automated analysis of high dimensional cytometry data.
Mair F, Hartmann FJ, Mrdjen D, Tosevski V, Krieg C, Becher B., Eur. J. Immunol. 46(1), 2015
PMID: 26548301
Mair F, Hartmann FJ, Mrdjen D, Tosevski V, Krieg C, Becher B., Eur. J. Immunol. 46(1), 2015
PMID: 26548301
flowDensity: reproducing manual gating of flow cytometry data by automated density-based cell population identification.
Malek M, Taghiyar MJ, Chong L, Finak G, Gottardo R, Brinkman RR., Bioinformatics 31(4), 2014
PMID: 25378466
Malek M, Taghiyar MJ, Chong L, Finak G, Gottardo R, Brinkman RR., Bioinformatics 31(4), 2014
PMID: 25378466
Computational flow cytometry: helping to make sense of high-dimensional immunology data.
Saeys Y, Van Gassen S, Lambrecht BN., Nat. Rev. Immunol. 16(7), 2016
PMID: 27320317
Saeys Y, Van Gassen S, Lambrecht BN., Nat. Rev. Immunol. 16(7), 2016
PMID: 27320317
Shapiro, 2005
Silverman, 1986
Upton, 1996
Accelerating t-sne using tree-based algorithms
Van, J. Mach. Learn. Res 15(), 2014
Van, J. Mach. Learn. Res 15(), 2014
FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data.
Van Gassen S, Callebaut B, Van Helden MJ, Lambrecht BN, Demeester P, Dhaene T, Saeys Y., Cytometry A 87(7), 2015
PMID: 25573116
Van Gassen S, Callebaut B, Van Helden MJ, Lambrecht BN, Demeester P, Dhaene T, Saeys Y., Cytometry A 87(7), 2015
PMID: 25573116
Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data.
Weber LM, Robinson MD., Cytometry A 89(12), 2016
PMID: 27992111
Weber LM, Robinson MD., Cytometry A 89(12), 2016
PMID: 27992111
Export
Markieren/ Markierung löschen
Markierte Publikationen
Web of Science
Dieser Datensatz im Web of Science®Quellen
PMID: 29462241
PubMed | Europe PMC
Suchen in