ReviewCell reports methods2022
Spatial statistics is a comprehensive tool for quantifying cell neighbor relationships and biological processes via tissue image analysis.
Review in Cell reports methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Society for Immunotherapy of Cancer: updates and best practices for multiplex immunohistochemistry (IHC) and immunofluorescence (IF) image analysis and data sharing.Journal for immunotherapy of cancer · 2025Guideline
- Lateral inhibition governs ancestral cellular patterning in fossil and extant liverworts.Development (Cambridge, England) · 2026Article
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- Decoding cellular population dynamics through mechanistic modelling and statistical data analysis.NPJ systems biology and applications · 2026Review
- Joint zonated quantification of multiple parameters in hepatic lobules.Scientific reports · 2026Article
- Estimating tumour immune infiltration: methodological convergence across histology and spatial technologies.Briefings in bioinformatics · 2026Review
- How stochastic cell fate and endoreduplication yield non-random epidermal patterns.Quantitative plant biology · 2026Article
- Keeping up with the neighbours: local synchronisation of cell fate decisions during development.EMBO reports · 2026Review
- Restraint of cancer cell plasticity by spatial homotypic clustering.Cancer cell · 2025Article
- From cells to pixels: A decision tree for designing bioimage analysis pipelines.Journal of microscopy · 2025Article
- A common pathway controls cell size in the sepal and leaf epidermis leading to a nonrandom pattern of giant cells.PLoS biology · 2025Article
- CytoSpatio: Learning cell type spatial relationships using multirange, multitype point process models.PLoS computational biology · 2025Article
- Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.Science advances · 2025Article
- A toolkit for mapping cell identities in relation to neighbors reveals conserved patterning of neuromesodermal progenitor populations.PLoS biology · 2025Article
- Topological data analysis of pattern formation of human induced pluripotent stem cell colonies.Scientific reports · 2025Article
- Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues.Journal of imaging · 2025Review
- Single Cell Spatial Transcriptomics Reveals Immunotherapy-Driven Bone Marrow Niche Remodeling in AML.bioRxiv : the preprint server for biology · 2025Article
- From Spatial Patterns to Prognosis: Decoding Single-Cell Architecture in Cancer with Hyperplex Immunofluorescence Imaging.Journal of Cancer · 2025Review
- Spatial effects of infiltrating T cells on neighbouring cancer cells and prognosis in stage III CRC patients.The Journal of pathology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.