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  Statistics for real-time deformability cytometry: Clustering, dimensionality reduction, and significance testing

Herbig, M., Mietke, A., Mueller, P., & Otto, O. (2018). Statistics for real-time deformability cytometry: Clustering, dimensionality reduction, and significance testing. Biomicrofluidics, 12(4): 042214. doi:10.1063/1.5027197.

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 Creators:
Herbig, M.1, Author
Mietke, Alexander2, Author           
Mueller, P.1, Author
Otto, O.1, Author
Affiliations:
1external, ou_persistent22              
2Max Planck Institute for the Physics of Complex Systems, Max Planck Society, ou_2117288              

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 MPIPKS: Structure formation and active systems
 Abstract: Real-time deformability (RT-DC) is a method for high-throughput mechanical and morphological phenotyping of cells in suspension. While analysis rates exceeding 1000 cells per second allow for a label-free characterization of complex biological samples, e.g., whole blood, data evaluation has so far been limited to a few geometrical and material parameters such as cell size, deformation, and elastic Young's modulus. But as a microscopy-based technology, RT-DC actually generates and yields multidimensional datasets that require automated and unbiased tools to obtain morphological and rheological cell information. Here, we present a statistical framework to shed light on this complex parameter space and to extract quantitative results under various experimental conditions. As model systems, we apply cell lines as well as primary cells and highlight more than 11 parameters that can be obtained from RT- DC data. These parameters are used to identify sub-populations in heterogeneous samples using Gaussian mixture models, to perform a dimensionality reduction using principal component analysis, and to quantify the statistical significance applying linear mixed models to datasets of multiple replicates. (C) 2018 Author(s).

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Language(s): eng - English
 Dates: 2018-06-042018-07
 Publication Status: Issued
 Pages: -
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 Identifiers: ISI: 000443760100016
DOI: 10.1063/1.5027197
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Title: Biomicrofluidics
Source Genre: Journal
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Publ. Info: Melville, NY : American Institute of Physics
Pages: - Volume / Issue: 12 (4) Sequence Number: 042214 Start / End Page: - Identifier: ISSN: 1932-1058
CoNE: https://pure.mpg.de/cone/journals/resource/1932-1058