Spatial analysis of in situ cytometry data

Ellis Patrick⁰, Nicolas Canete⁰
(0) The University of Sydney

Find me on Tues Nov 24th, 1:40-3pm AEDT in Remo, table 113

Abstract
Understanding the interplay between different types of cells and their immediate environment is critical for understanding the mechanisms of cells themselves and their function in the context of human diseases. Recent advances in high-parameter in situ cytometry technologies have fundamentally revolutionized our ability to observe these complex cellular relationships providing an unprecedented characterisation of cellular heterogeneity in a tissue environment.

We will introduce an analytical framework, spicyR, for analysing data from high-parameter in situ cytometry assays including CODEX, CycIF, IMC and High Definition Spatial Transcriptomics. Ultimately, this framework is applicable to any assay that has undergone single-cell segmentation and produces information on a cells location in x-y space and the abundance of various molecular markers on the cell. Using point process models, our framework includes methodology for testing if the colocalisation of two cell-types has changed between two groups of subjects. While not necessary, this methodology can benefit from situations when multiple measurements are performed for each subject. We will also demonstrate how point process models can be exploited to identify consistent spatial organisation of multiple cell-types in an unsupervised way. This can be used to enable the characterization of interactions between multiple cell-types simultaneously and can facilitate the identification of distinct tissue compartments or identification of complex cellular microenvironments.