Fig. 5: Single-Slide Spatial Multiomics Annotation using TACIT.

a A spatial transcriptomics experiment on minor salivary glands from GVHD patients used a Xenium platform with a 280-gene panel targeting structural and immune cells, revealing a high-density immune area with overlays of specific transcripts. b A subsequent spatial proteomics experiment on the same slide utilized a Phenocycler Fusion with a 36-antibody panel, sharing the segmentation mask for consistent spatial single-cell data extraction. c UMAP analysis of the Xenium data with TACIT and Louvain showed greater annotation granularity with TACIT, highlighting cell types identified only by TACIT (arrows). d A Voronoi plot for a GVHD case displayed detailed annotation reconstruction by TACIT, showing the heterogeneity in a dense immune infiltrate. e A Venn diagram demonstrated that TACIT identified 22 cell types, including four not matched by Louvain, although Louvain’s detected types were also identified by TACIT. f The absolute error in cell type assignments compared to human pathologist evaluations varied between TACIT and Louvain. g Another UMAP from the Phenocycler Fusion data emphasized TACIT’s higher granularity, with unique cell types marked (arrows). h A second Voronoi plot based on spatial proteomics data for a GVHD case illustrated TACIT’s annotation at a slightly lower resolution than the transcriptomics data. i A proteomics Venn diagram showed TACIT recognized and assigned 18 cell types, with two structural and two immune types uniquely detected. j The absolute error in cell quantity signatures from a spatial transcriptomics assay, compared with a human pathologist’s evaluation for each cell type, confirmed TACIT’s precision over Louvain. Source data are provided as a Source Data file.