{
  "id": 6526453,
  "title": "PhenoMapR: scalable mapping of sample phenotypes to single-cell, spatial, and bulk transcriptomics data",
  "url": "https://urgent.news/2026/09/09/phenomapr-scalable-mapping-of-sample-phenotypes-to-single-cell",
  "topic": "science",
  "section": "Science",
  "published": "2026-09-09T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.08.749933v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Single-cell and spatial transcriptomic studies often lack sufficient sample size to compute robust statistical associations between a sample-level phenotype and cell types or spatial locations. In contrast, lower resolution methods such as bulk gene expression profiling have been applied at scale in large, annotated datasets, providing reliable signatures for phenotype associations. We introduce…",
  "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."
}