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Updated: Jun 22, 2025
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
A Spatial Omnibus Test (SPOT) for Spatial Proteomic Data
Sarah Samorodnitsky1,2, Katie Campbell3, Antoni Ribas3
1Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle 98109, USA.
Motivation:
Spatial proteomics can reveal the spatial organization of immune cells in the tumor immune microenvironment. Relating measures of spatial clustering, such as Ripley's K or Besag's L, to patient outcomes may offer important clinical insights. However, these measures require pre-specifying a radius in which to quantify clustering, yet no consensus exists on the optimal radius which may be context-specific.
Results:
We propose a SPatial Omnibus Test (SPOT) which conducts this analysis across a range of candidate radii. At each radius, SPOT evaluates the association between the spatial summary and outcome, adjusting for confounders. SPOT then aggregates results across radii using the Cauchy combination test, yielding an omnibus P-value characterizing the overall degree of association. Using simulations, we verify that the type I error rate is controlled and show SPOT can be more powerful than alternatives. We also apply SPOT to ovarian and lung cancer studies.
Availability And Implementation:
An R package and tutorial are provided at https://github.com/sarahsamorodnitsky/SPOT.
