Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Identification and Visualization of Cell Subgroups in Uncompensated Flow Cytometry Data(Elsevier Ltd., 2020) Güzel, Başak Esin Köktürk; Karaçalı, Bilge; Karaçalı, Bilge; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyWe 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.