{
  "id": 809861,
  "title": "Principal Genes: A PCA-based approach to highly variable genes selection for scRNA-Seq analysis",
  "url": "https://urgent.news/2026/08/13/principal-genes-a-pca-based-approach-to-highly-variable-genes",
  "topic": "science",
  "section": "Science",
  "published": "2026-08-13T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.08.07.743504v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Single cell RNA-sequencing (scRNA-Seq) data are typically represented as cell-by-gene count matrices, which capture the expression of each gene as detected in the sampled cells; often a heterogeneous population of multiple different cell types or cell states. Almost all scRNA-Seq analysis workflows have a gene selection step prior to applying clustering algorithms which helps remove genes with…",
  "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."
}