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Identification and visualization of cell subgroups in uncompensated flow cytometry data

Access

info:eu-repo/semantics/closedAccess

Date

2020

Author

Guzel, Basak Esin Kokturk
Karacali, Bilge

Metadata

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Abstract

We propose a new method for identification and visualization of cell-sub groups in uncompensated multi-color flow cytometry data. The method combines annealing-based model-free expectation-maximization to identify cell sub-groups and joint diagonalization on clustered data for better visualization. The proposed method was evaluated on a real, publicly available 8-color flow cytometry dataset manually gated beforehand for lymphocytes. The results obtained in three separable scenarios indicate that the method accurately identifies cell subgroups while properly adjusting visualization of identified cell groups by reducing the spectral overlap between the different fluorochrome channels.

Source

Chemometrics And Intelligent Laboratory Systems

Volume

196

URI

https://doi.org/10.1016/j.chemolab.2019.103892
https://hdl.handle.net/11147/10201

Collections

  • Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection [4697]
  • WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection [4802]



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