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CytoBinning: immunological insights from multi-dimensional data

View ORCID ProfileYang Shen, Benjamin Chaigne-Delalande, Richard W.J. Lee, Wolfgang Losert
doi: https://doi.org/10.1101/321893
Yang Shen
1Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, United States
2Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States
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Benjamin Chaigne-Delalande
2Laboratory of Immunology, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, United States
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Richard W.J. Lee
3Translational Health Sciences, Faculty of Health Sciences, University of Bristol, Bristol BS8 1TD, United Kingdom
4Inflammation and Immunotherapy Theme National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital (National Health Service) Foundation Trust and University College London Institute of Ophthalmology, London EC1V 2PD, United Kingdom
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Wolfgang Losert
1Institute for Physical Science and Technology, University of Maryland, College Park, MD 20742, United States
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  • For correspondence: wlosert@umd.edu
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Abstract

New cytometric techniques continue to push the boundaries of multi-parameter quantitative data acquisition at the single-cell level particularly in immunology and medicine. Sophisticated analysis methods for such ever higher dimensional datasets are rapidly emerging, with advanced data representations and dimensional reduction approaches. However, these are not yet standardized and clinical scientists and cell biologists are not yet experienced in their interpretation. More fundamentally their range of statistical validity is not yet fully established. We therefore propose a new method for the automated and unbiased analysis of high-dimensional single cell datasets that is simple and robust, with the goal of reducing this complex information into a familiar 2D scatter plot representation that is of immediate utility to a range of biomedical and clinical settings. Using publicly available flow cytometry and mass cytometry datasets we demonstrate that this method (termed CytoBinning), recapitulates the results of traditional manual cytometric analyses and leads to new and testable hypotheses.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.
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Posted May 14, 2018.
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CytoBinning: immunological insights from multi-dimensional data
Yang Shen, Benjamin Chaigne-Delalande, Richard W.J. Lee, Wolfgang Losert
bioRxiv 321893; doi: https://doi.org/10.1101/321893
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CytoBinning: immunological insights from multi-dimensional data
Yang Shen, Benjamin Chaigne-Delalande, Richard W.J. Lee, Wolfgang Losert
bioRxiv 321893; doi: https://doi.org/10.1101/321893

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