{
  "id": 14984287,
  "title": "Scale-resolved correlation functions unify spatial omics across platforms and resolutions",
  "url": "https://urgent.news/2026/10/16/scale-resolved-correlation-functions-unify-spatial-omics-across",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-16T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.10.09.757915v1?rss=1"
  },
  "original_language": "en",
  "account": "Spatial omics platforms, each with distinct resolutions, panel sizes, sensitivities, and modalities, generate multidimensional data sets that are difficult to compare due to their platform-specific nature. To address this challenge, researchers have developed SCOTE (Spatial COvariance TEnsors), a computational framework designed to quantify spatial relationships of feature pairs across various length scales. This technique applies to both molecule coordinates and binned counts, enabling the comparison of the same quantity, along with its statistical errors, across different platforms, samples, and patients.\n\nBy measuring these relationships, SCOTE effectively distinguishes measurement effects from biological signals, revealing platform artifacts as identifiable, scale-localized features. The framework's molecule-level functions have proven particularly useful in identifying effects that were previously overlooked by cell-level analyses. For instance, SCOTE successfully detected a knockout effect in mouse spleen tissue, which had been missed by cell-level approaches.\n\nMoreover, SCOTE reveals that tissue area and the number of replicates, rather than molecule depth, determine the statistical error in spatial omics data sets. This framework is designed to accommodate the rapidly expanding volume of spatial omics data, running efficiently on both CPUs and GPUs. It can process a billion-molecule whole-transcriptome section at all length scales, complete with uncertainties, within just 26 minutes on a single GPU.",
  "summary": "Spatial omics platforms populate a multidimensional parameter space and differ in resolution, panel size, sensitivity, and modality. This diversity has led to platform-specific analyses whose results are rarely comparable. Here we present SCOTE (Spatial COvariance TEnsors), a computational framework that quantifies spatial relationships of all feature pairs across all length scales, for molecule…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}