{
  "abstract": "Single-cell RNA-seq atlases are commonly explored with nonlinear embeddings that preserve neighborhoods but provide limited coordinate-level interpretation. We asked whether projecting the dominant principal components (PCs) of single-cell gene expression onto a unit sphere would yield an interpretable coordinate system. SPHERE-PCA L2-normalizes the first three PC coordinates, aligns a biologically defined root to the north pole, and represents each cell by three coordinates: root-aligned geodesic distance ({theta}), angular position ({phi}), and pre-projection radial magnitude (r). Across developmental and disease-associated datasets, this representation reveals structured spherical geometry, ranging from near-great-circle trajectories to multi-arc manifolds. In developmental atlases, root-aligned geodesic distance increases as CytoTRACE-inferred stemness decreases, while gene-coordinate analyses separate programs associated with angular position from those associated with radial magnitude. Fixed-loading perturbations decompose each gene's effect on cell position into progression, branch- or state-position, and radial activity components. SPHERE-PCA therefore provides a deterministic, loading-preserving coordinate framework for interpreting dominant transcriptomic variance and establishing a transparent geometric coordinate framework for perturbation analysis and virtual-cell models.",
  "abstract_shown": true,
  "affiliations": [
    "Johns Hopkins University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "name": "L. Yuan"
    },
    {
      "name": "X. Li"
    },
    {
      "name": "M. Le"
    },
    {
      "name": "S. C. Hicks"
    },
    {
      "name": "A. Deshpande"
    },
    {
      "name": "J. M. Taube"
    },
    {
      "affs": [
        0
      ],
      "name": "A. S. Szalay"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3y2v9r9gfbm6a.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.11.751061",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.11.751061v1.full",
  "id": "3y2v9r9gfbm6a",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.11.751061v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "systems biology"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7213605930",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.11.751061v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-11",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3y2v9r9gfbm6a.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:07Z",
      "native_id": "10.64898/2026.09.11.751061",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.11.751061v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:systems biology",
      "subfield": "systems-synthetic"
    }
  ],
  "title": "Interpretable spherical geometry of single-cell state transitions from dominant principal components",
  "title_text": "Interpretable spherical geometry of single-cell state transitions from dominant principal components",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:07Z",
  "url": "https://research.draconitic.com/paper/3y2v9r9gfbm6a",
  "venue": "bioRxiv",
  "versions": []
}