Spatialgater: an R Shiny webtool for in situ gating of cells in spatial omics experiments

Abstract Background Multiplexed imaging techniques generate high-dimensional datasets that contain their molecular profiles of cells combined with spatial coordinates, which can be stored in SpatialExperiment objects. Results Current analysis workflows using the SpatialExperiment class separate cells after clustering them by their bio-molecule expression levels without considering their spatial context within the tissue. While patch-/neighbourhood detection methods exist, there is no option to select single cells by their location at will. By introducing spatialgater, we aim to boost interactivity and reduce programming efforts of image analysis by enabling spatial selection of cells from SpatialExperiment objects through an intuitive web-based user interface. The package displays cells as dots on a zoom-able image and allows users to draw polygon gates directly on individual cells. An integrated k -nearest-neighbor feature automatically extends manual gates across similar spatial microenvironments. All selected cell identifiers can be exported as a CSV file and/or saved back into the original dataset as a new logical column. All manually drawn polygons are stored in a log file to guarantee traceability. Conclusion Spatialgater provides an accessible, interactive addition to spatial analysis pipelines. By using a publicly available imaging mass cytometry dataset from breast cancer tissue, we demonstrate its effectiveness in characterizing and comparing T-cells by their spatial location.