{
  "abstract": "High-content screening of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) is widely used for disease modeling, yet standard pipelines rely on whole-well averages that obscure cell-to-cell heterogeneity. Moving from well-averages to single-cell analysis reveals hidden variations, but may introduce a pseudoreplication bias if cells are analysed as independent data points. We present CardioShift, an open-source bioimage informatics framework designed to map single-cell distributions by properly accounting for this nested variance structure. Applying this framework to 32,818 Ca2+ transients and 10,719 contractility-lipid profiles, we show that cell-to-cell variability represents the largest source of variance for most functional parameters, demonstrating how traditional well averages mask condition-dependent phenotypes. Furthermore, unsupervised clustering identifies condition-dependent shifts in functional subpopulations, including a distinct cellular state that accumulates lipids but maintains baseline contraction kinetics that was not detected using well- and single-cell averaging approaches. CardioShift provides a robust analytical approach to resolve hidden single-cell distributions.",
  "abstract_shown": true,
  "affiliations": [
    "University Medical Center Utrecht"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "name": "T. C. F. Spanjersberg"
    },
    {
      "name": "C. N. van der Wilt"
    },
    {
      "name": "J.-C. Chang"
    },
    {
      "name": "J. B. Helms"
    },
    {
      "name": "R. G. C. Maas"
    },
    {
      "name": "J. P. G. Sluijter"
    },
    {
      "name": "V. Fontaine"
    },
    {
      "name": "E. Villard"
    },
    {
      "name": "T. P. de Boer"
    },
    {
      "name": "R. J. A. Veltrop"
    },
    {
      "name": "F. G. van Steenbeek"
    },
    {
      "affs": [
        0
      ],
      "name": "M. Harakalova"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/88294fm2q7msq.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.31.763029",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763029v1.full",
  "id": "88294fm2q7msq",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763029v1",
  "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",
      "cell biology"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763029v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-31",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/88294fm2q7msq.ris",
  "sources": [
    {
      "first_seen": "2026-11-04T00:21:40Z",
      "native_id": "10.64898/2026.10.31.763029",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.31.763029v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:cell biology",
      "subfield": "cell-biology"
    }
  ],
  "title": "CardioShift: Resolving cell-to-cell functional heterogeneity in hiPSC-derived cardiomyocytes from high-throughput single-cell imaging",
  "title_text": "CardioShift: Resolving cell-to-cell functional heterogeneity in hiPSC-derived cardiomyocytes from high-throughput single-cell imaging",
  "type": "preprint",
  "updated_at": "2026-11-05T00:21:09Z",
  "url": "https://research.draconitic.com/paper/88294fm2q7msq",
  "venue": "bioRxiv",
  "versions": []
}