Spatial Touchstone: A Comprehensive Assessment of Imaging-Based Spatial Transcriptomics, Reproducibility and Best Practices

Spatial transcriptomics is a rapidly advancing field, yet it lacks standardized metrics for evaluating imaging-based in situ hybridization technologies. In this study, we emphasize the importance of rigorous experimental design and standardized operating procedures (SOPs) in defining performance metrics across multiple modalities—from single-cell to spatial transcriptomics to spatial proteomics. Our Spatial Touchstone (ST) dataset, generated from six tissue types across three global sites (n=76 assays), provides a comprehensive evaluation of reproducibility, sensitivity, dynamic ranges, signal-to-noise ratio, false discovery rates, cell type annotation, and congruence with single-cell profiling. Using single-nucleus RNA sequencing (snRNA-seq) on the same formalin-fixed paraffin-embedded tissues, we created a reference for transcriptional profiles to assess cellular organization and biomarker localization. In the absence of an independent 'gold standard’ in the field, this study provides an objective assessment of technical performance through standardized protocols, Spatial Touchstone Protocols (STSOP). Our open-source software, SpatialQC, allows users to evaluate samples across all technical metrics and directly impute cell annotations from single-cell datasets. This study features the largest imaging-based spatial transcriptomics data repository available, with a total of 203 spatial profiles. It incorporates both public (n=127) and ST datasets (n=76) through the Spatial Touchstone Portal (STP), available at www.spatialtouchstone.org. This resource offers users easy access to analyze and compare their own data against an extensive collection of imaging-based datasets. We show that the ST datasets demonstrate high reproducibility (r=0.93 to 1.0) and set a new benchmark for the field. Finally, we establish metrics to evaluate and integrate imaging based multi omics data from single cell into spatial transcriptomics to spatial proteomics. The ST project provides a comprehensive, reproducible assessment across platforms and sites, establishing essential standards for imaging-based spatial multi omics (transcriptomics and proteomics) and paving the way for future research and technological advancements. The study utilized two leading spatial technologies, Xenium and CosMx SMI, as representative examples of cutting-edge commercial platforms for evaluating technical performance. These platforms were evaluated across six tissue types in both normal (appendix/AP, colon/CO, pancreas/PA, ileum/IL) and cancerous (breast/BR and prostate/PR) conditions, focusing on accuracy, precision, reproducibility, sensitivity, and specificity. It used commercially available panels for both RNA (CosMx Human Universal Cell Characterization RNA Panel targeting 950 human genes and a 50-target add-on panel set; Xenium Human Multi-Tissue and Cancer Panel targeting 377 human genes; Xenium Human Breast Panel targeting 380 human genes) and protein (NanoString 64-plex human protein panel). All samples were analyzed on both imaging-based platforms (full scan of the entire section) generating 76 profiles, subjected to snRNA-seq (snPATHO-seq, n=6) and hematoxylin and eosin (H&E) staining (n=44) (n=126 total).