Introduction | The data | Testing every pair of cell types | Seeing every pair at once | Looking at one pair | Looking at the images | Tissue compartments | Allocation or count? | Patients with several images | Adjusting for clinical covariates | Which radius? | Is co-localisation associated with survival? | A check you can run | How it works | Small studies | Reporting results | Coming from spicyR 1.x | Python | Very large data sets: SpatialData stores | Session information | References

Installation | Overview | Load example data | Segmentation | Visualise separation | Visualise outlines | Methods of Watershedding | Methods of cell body identification | Parallel Processing | Summarise cell features | Segmenting image files | Normalising cells | QC normalisation | Session Info

Installation | Overview | Example data | Linear modelling | Test for change in localisation for a specific pair of cells | Test for change in localisation for all pairwise cell combinations | Linear modelling for custom metrics | Performing survival analysis | Accounting for tissue inhomogeneity | Mixed effects modelling | Session information | References

Introduction | Installation | Datasets | Load data | Load using named accessors | Keren et al. (2018) | Ferguson et al. (2022) | Ferguson Images | Ferguson SpatialExperiment Object | Schurch et al. (2020) | Ali et al. (2020) | Amancherla et al. (2025) | Vannan et al. (2025) | Generating objects from raw data files | Session information