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Optimizing multiplexed imaging experimental design through tissue spatial segregation estimation

View ORCID ProfilePierre Bost, View ORCID ProfileDaniel Schulz, Stefanie Engler, Clive Wasserfall, Bernd Bodenmiller
doi: https://doi.org/10.1101/2021.11.28.470262
Pierre Bost
1University of Zurich, Department of Quantitative Biomedicine, Zurich, 8057, Switzerland
2ETH Zurich, Institute for Molecular Health Sciences, Zurich, 8093 Switzerland
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  • ORCID record for Pierre Bost
Daniel Schulz
1University of Zurich, Department of Quantitative Biomedicine, Zurich, 8057, Switzerland
2ETH Zurich, Institute for Molecular Health Sciences, Zurich, 8093 Switzerland
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Stefanie Engler
1University of Zurich, Department of Quantitative Biomedicine, Zurich, 8057, Switzerland
2ETH Zurich, Institute for Molecular Health Sciences, Zurich, 8093 Switzerland
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Clive Wasserfall
3Department of Pathology, Immunology, and Laboratory Medicine, Diabetes Institute, University of Florida, Gainesville, FL 32610, USA
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Bernd Bodenmiller
1University of Zurich, Department of Quantitative Biomedicine, Zurich, 8057, Switzerland
2ETH Zurich, Institute for Molecular Health Sciences, Zurich, 8093 Switzerland
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  • For correspondence: bernd.bodenmiller@uzh.ch
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Abstract

Recent advances in multiplexed imaging methods allow simultaneous detection of dozens of proteins and hundreds of RNAs enabling deep spatial characterization of both healthy and diseased tissues. Parameters for design of optimal sequencing-based experiments have been established, but such parameters, especially those estimating how much area has to be imaged to capture all cell phenotype clusters, are lacking for multiplex imaging studies. Here, using a spatial transcriptomic atlas of healthy and tumor human tissues, we developed a new statistical framework that determines the number and area of fields of view necessary to accurately identify all cell types that are part of a tissue. Using this strategy on imaging mass cytometry data, we identified a measurement of tissue spatial segregation that enables optimal experimental design. This strategy will enable significantly improved design of multiplexed imaging studies.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 19, 2022.
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Optimizing multiplexed imaging experimental design through tissue spatial segregation estimation
Pierre Bost, Daniel Schulz, Stefanie Engler, Clive Wasserfall, Bernd Bodenmiller
bioRxiv 2021.11.28.470262; doi: https://doi.org/10.1101/2021.11.28.470262
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Optimizing multiplexed imaging experimental design through tissue spatial segregation estimation
Pierre Bost, Daniel Schulz, Stefanie Engler, Clive Wasserfall, Bernd Bodenmiller
bioRxiv 2021.11.28.470262; doi: https://doi.org/10.1101/2021.11.28.470262

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