Statial: A Bioconductor package for identifying spatially-related changes in cell state
Author(s): Ellis Patrick,Farhan Ameen,Sourish Iyengar,Shila Ghazanfar
Affiliation(s): The University of Sydney
Social media: https://twitter.com/TheEllisPatrick
The human body comprises over 37 trillion cells with diverse forms and functions, which can exhibit dynamic changes based on their environmental context. Understanding the spatial interactions between cells and changes in their state within the tissue microenvironment is crucial to comprehending the development of human diseases. State-of-the-art technologies such as PhenoCycler, IMC, CosMx, Xenium, and others can deeply phenotype cells in their native environment, providing a high-throughput means of identifying spatially related changes in cell state. The Statial Bioconductor package offers a suite of complementary approaches for identifying changes in cell state explained by changes in cell type localization. In this presentation, we introduce new functionality in the Statial package that can 1) identify changes in cell state between distinct tissue environments, 2) uncover changes in marker expression associated with cell proximities, and 3) model spatial relationships between cells in the context of hierarchical cell lineage structures. We provide context for these approaches and explain when and why modeling spatial relationships between cells in these ways is appropriate. Finally, we demonstrate how these approaches can be used in a classification setting to predict patient prognosis or treatment response.