{
  "abstract": "Cell-cell communication underpins intercellular responses allowing cells to dynamically change states across conditions; however current methods typically aggregate signals by cell type annotations which may introduce biases. We developed HyperCom, a hypergraph-based method to infer cell-resolved cell-cell communication from single cell transcriptomics data. HyperCom constructs a hypergraph from known ligand-receptor interactions and the expression of those ligands and receptors in individual cells and performs graph diffusion on the hypergraph to score cells on a continuous spectrum from sender to receiver for each LR pair. HyperCom then generates a cell-type agnostic ranking of LR pairs by communication either over the whole dataset or in a condition-aware manner. Validation of HyperCom on physical cell-to-cell contact, spatial, and multicondition datasets highlight its flexibility to capture subtle per cell communication information. HyperCom is available as a species-agnostic, scalable, and open source R package: https://github.com/pawelab/HyperCom.",
  "abstract_shown": true,
  "affiliations": [
    "Boston University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "name": "J. K. Moy"
    },
    {
      "affs": [
        0
      ],
      "name": "P. F. Przytycki"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/czp19q3g91kcb.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.30.755742",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755742v1.full",
  "id": "czp19q3g91kcb",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755742v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioinformatics"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7220934442",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755742v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-30",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/czp19q3g91kcb.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:33Z",
      "native_id": "10.64898/2026.09.30.755742",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755742v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "HyperCom: a hypergraph-based method to infer cell-resolved cell-cell communication",
  "title_text": "HyperCom: a hypergraph-based method to infer cell-resolved cell-cell communication",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:33Z",
  "url": "https://research.draconitic.com/paper/czp19q3g91kcb",
  "venue": "bioRxiv",
  "versions": []
}