Spatial Analysis Of High Dimensional In Situ Cytometry Data***

Spatial Analysis Of High Dimensional In Situ Cytometry Data***

Author(s): Ellis Patrick, Nick Canete, Elijah Willie, Alexander Nicholls

Affiliation(s): The University of Sydney

Twitter: @TheEllisPatrick

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 dimensional 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. In this workshop we will introduce an analytical framework for analysing data from high dimensional in situ cytometry assays including CODEX, CycIF, IMC and High Definition Spatial Transcriptomics. This framework makes use of functionality from our Bioconductor packages spicyR, listClust, scFeatures, treekoR and ClassifyR. By the end of this workshop attendees will be able to implement and assess some of the key steps of a spatial analysis pipeline including cell segmentation, feature normalisation, cell type identification, microenvironment characterisation, spatial hypothesis testing and patient classification. Understanding these key steps will provide attendees with the core skills needed to interrogate the comprehensive spatial information generated by these exciting new technologies.

Source code


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