{
  "id": 5906717,
  "title": "SCG: Spatially Co-Expressed Gene Identification through Spatially Varying Networks",
  "url": "https://urgent.news/2026/09/05/scg-spatially-co-expressed-gene-identification-through-spatially",
  "topic": "science",
  "section": "Science",
  "published": "2026-09-05T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.01.748618v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Spatial transcriptomics has enabled the advancement of gene expression analysis, yet spatial co-expression remains understudied. We introduce spatial covariance regression (SCR), a scalable Bayesian factor-model-based framework for estimation of spatially-resolved gene co-expression networks across tissue domains. These networks provide the spatial map of gene-gene correlations and enable the…",
  "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."
}