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Spatial statistics is a comprehensive tool for quantifying cell neighbor relationships and biological processes via tissue image analysis

Huw Summers Orcid Logo, John W. Wills, Paul Rees Orcid Logo

Cell Reports Methods, Volume: 2, Issue: 11, Start page: 100348

Swansea University Authors: Huw Summers Orcid Logo, Paul Rees Orcid Logo

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DOI (Published version): 10.1016/j.crmeth.2022.100348

Abstract

Automated microscopy and computational image analysis has transformed cell biology, providing quantitative, spatially resolved information on cells and their constituent molecules from the sub-micron to the whole-organ scale. Here we explore the application of spatial statistics to the cellular rela...

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Published in: Cell Reports Methods
ISSN: 2667-2375
Published: Elsevier BV 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa62019
Abstract: Automated microscopy and computational image analysis has transformed cell biology, providing quantitative, spatially resolved information on cells and their constituent molecules from the sub-micron to the whole-organ scale. Here we explore the application of spatial statistics to the cellular relationships within tissue microscopy data and discuss how spatial statistics offers cytometry a powerful yet underused mathematical tool set for which the required data are readily captured using standard protocols and microscopy equipment. We also highlight the often-overlooked need to carefully consider the structural heterogeneity of tissues in terms of the applicability of different statistical measures and their accuracy and demonstrate how spatial analyses offer a great deal more than just basic quantification of biological variance. Ultimately, we highlight how statistical modeling can help reveal the hierarchical spatial processes that connect the properties of individual cells to the establishment of biological function.
Keywords: cell imagings; patial statistics; tissue analysis; cytometry
College: Faculty of Science and Engineering
Funders: Swansea University
Issue: 11
Start Page: 100348

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