Meeting the challenges of high-dimensional single-cell data analysis in immunology
Patil S, Heuser C, De Almeida GP, Theis FJ, Zielinski CE (2019)
Publication Type: Journal article
Publication year: 2019
Journal
Book Volume: 10
Article Number: 1515
Journal Issue: JUL
Abstract
Recent advances in cytometry have radically altered the fate of single-cell proteomics by allowing a more accurate understanding of complex biological systems. Mass cytometry (CyTOF) provides simultaneous single-cell measurements that are crucial to understand cellular heterogeneity and identify novel cellular subsets. High-dimensional CyTOF data were traditionally analyzed by gating on bivariate dot plots, which are not only laborious given the quadratic increase of complexity with dimension but are also biased through manual gating. This review aims to discuss the impact of new analysis techniques for in-depths insights into the dynamics of immune regulation obtained from static snapshot data and to provide tools to immunologists to address the high dimensionality of their single-cell data.
Involved external institutions
Technische Universität München (TUM)
Germany (DE)
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich
Germany (DE)
Germany (DE)
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt (HMGU) / Helmholtz Munich
Germany (DE)
How to cite
APA:
Patil, S., Heuser, C., De Almeida, G.P., Theis, F.J., & Zielinski, C.E. (2019). Meeting the challenges of high-dimensional single-cell data analysis in immunology. Frontiers in Immunology, 10(JUL). https://dx.doi.org/10.3389/fimmu.2019.01515
MLA:
Patil, Subarea, et al. "Meeting the challenges of high-dimensional single-cell data analysis in immunology." Frontiers in Immunology 10.JUL (2019).
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