Extended methods for spatial cell classification with DBSCAN-CellX

Küchenhoff L, Lukas P, Metz-Zumaran C, Rothhaar P, Ruggieri A, Lohmann V, Höfer T, Stanifer ML, Boulant S, Talemi SR, Graw F (2023)

Publication Type: Journal article

Publication year: 2023

Journal

Scientific Reports Nature Publishing Group: Open Access Journals - Option B

Book Volume: 13

Article Number: 18868

Journal Issue: 1

DOI: 10.1038/s41598-023-45190-4

Abstract

Local cell densities and positioning within cellular monolayers and stratified epithelia have important implications for cell interactions and the functionality of various biological processes. To analyze the relationship between cell localization and tissue physiology, density-based clustering algorithms, such as DBSCAN, allow for a detailed characterization of the spatial distribution and positioning of individual cells. However, these methods rely on predefined parameters that influence the outcome of the analysis. With varying cell densities in cell cultures or tissues impacting cell sizes and, thus, cellular proximities, these parameters need to be carefully chosen. In addition, standard DBSCAN approaches generally come short in appropriately identifying individual cell positions. We therefore developed three extensions to the standard DBSCAN-algorithm that provide: (i) an automated parameter identification to reliably identify cell clusters, (ii) an improved identification of cluster edges; and (iii) an improved characterization of the relative positioning of cells within clusters. We apply our novel methods, which are provided as a user-friendly OpenSource-software package (DBSCAN-CellX), to cellular monolayers of different cell lines. Thereby, we show the importance of the developed extensions for the appropriate analysis of cell culture experiments to determine the relationship between cell localization and tissue physiology.

Authors with CRIS profile

Frederik Graw

Involved external institutions

Ruprecht-Karls-Universität Heidelberg DE Germany (DE) University of Florida US United States (USA) (US) Deutsches Krebsforschungszentrum (DKFZ) DE Germany (DE)

How to cite

APA:

Küchenhoff, L., Lukas, P., Metz-Zumaran, C., Rothhaar, P., Ruggieri, A., Lohmann, V.,... Graw, F. (2023). Extended methods for spatial cell classification with DBSCAN-CellX. Scientific Reports, 13(1). https://dx.doi.org/10.1038/s41598-023-45190-4

MLA:

Küchenhoff, Leonie, et al. "Extended methods for spatial cell classification with DBSCAN-CellX." Scientific Reports 13.1 (2023).

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