{
  "abstract": "Motivation: Simulated single-cell and spatial transcriptomic datasets that capture circadian dynamics while providing known ground truth remain scarce, limiting systematic evaluation of circadian analysis methods. Results: We developed scCircaSim to generate circadian single-cell and spatial transcriptomic data from a single-time-point reference. The framework combines phase progression with reference-derived network propagation of anchor gene rhythms and incorporates neighborhood effects for spatial simulation. Outputs retain reference heterogeneity and provide known cell or spot phases, rhythmicity labels, and gene-level mesor, amplitude, and phase values. Validation showed retention of reference structure and recovery of specified temporal patterns. Benchmarks of four cell phase inference methods and three rhythmic gene analysis methods revealed differences in phase accuracy, rhythmicity detection, and parameter recovery. scCircaSim supports reproducible method evaluation and preliminary experimental planning. Availability and Implementation: scCircaSim is implemented in R and available at https://github.com/Liwei-DynamicsLab/scCircaSim.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Cardiac Ultrasound, The Affiliated Hospital of Qingdao University, Qingdao, China"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "name": "C. Li"
    },
    {
      "name": "L. Zhang"
    },
    {
      "name": "Q. Zhang"
    },
    {
      "name": "L. Zhao"
    },
    {
      "name": "X. Song"
    },
    {
      "name": "Y. Tian"
    },
    {
      "name": "G. Tang"
    },
    {
      "name": "H. Zhou"
    },
    {
      "name": "Z. Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "P. Sun"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/895q83wme9nv1.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.05.764753",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.11.05.764753v1.full",
  "id": "895q83wme9nv1",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.11.05.764753v1",
  "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",
      "bioinformatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.11.05.764753v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-05",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/895q83wme9nv1.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T00:21:26Z",
      "native_id": "10.64898/2026.11.05.764753",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.11.05.764753v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "scCircaSim: A Circadian Simulator for Single-Cell and Spatial Transcriptomics",
  "title_text": "scCircaSim: A Circadian Simulator for Single-Cell and Spatial Transcriptomics",
  "type": "preprint",
  "updated_at": "2026-11-08T00:21:10Z",
  "url": "https://research.draconitic.com/paper/895q83wme9nv1",
  "venue": "bioRxiv",
  "versions": []
}