{
  "abstract": "Aims\n\nSpatially resolved omics technologies enable investigation of cellular interactions within their local microenvironments (neighbourhoods) directly in situ. Although several computational methods have been developed for neighbourhood analysis, significant limitations remain in how neighbourhoods are defined and interrogated. Here, we present Kandinsky, a toolkit that provides a flexible and versatile framework for defining and analysing cell neighbourhoods.Methods\n\nWe developed Kandinsky to improve flexibility in neighbourhood analysis and maximise compatibility with a wide range of spatial omics data. We therefore implemented multiple approaches for identifying cell- or spot-based neighbourhoods that serve as input for four analytical modules: differential gene or protein expression analysis, neighbourhood clustering, co-localisation/dispersion, and spatial hot and cold areas. In addition to its core functionality, Kandinsky enables the execution of external tools within the same analytical framework.Results\n\nWe applied Kandinsky to real and simulated spatial datasets to benchmark its performance against existing methods and demonstrate its ability to uncover biologically meaningful spatial interactions. Kandinsky achieved competitive performance in terms of accuracy, memory usage, and runtime. In real datasets, it suggested transcriptional changes associated with acinar-to-beta cell reprogramming in the healthy pancreas; recapitulated stromal, immune, and tumour-associated clusters in pancreatic cancer; revealed the spatial co-localisation of myoepithelial cells with specific breast cancer subpopulations; and confirmed the association between regions of high CD74 expression and immune cell infiltration.Conclusion\n\nKandinsky is a flexible and versatile toolkit for neighbourhood analysis that facilitates the exploration and interpretation of complex spatial omics data.",
  "abstract_shown": true,
  "affiliations": [
    "Centre for Cancer Evolution, Barts Cancer Institute, Queen Mary University of London, London EC1M 6AU, UK.",
    "Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK.",
    "Department of Oncology and Hemato-Oncology, University of Milan, Milan 20122, Italy.",
    "Italian Institute for Genomic Medicine, c/o IRCCS, Candiolo 10060, Italy.",
    "IFOM ETS-The AIRC Institute of Molecular Oncology, Milan 20139, Italy.",
    "Genomics Research Platform and Single Cell Laboratory, Guy's and St Thomas' NHS Foundation Trust, London SE1 9RT, UK.",
    "Department of Research Pathology, UCL Cancer Institute, University College London, London WC1E 6DD, UK."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Pietro Andrei"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Mariachiara Grieco"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Amelia Acha-Sagredo"
    },
    {
      "affs": [
        2,
        4
      ],
      "name": "Tommaso Becchi"
    },
    {
      "affs": [
        5
      ],
      "name": "Pawan Dhami"
    },
    {
      "affs": [
        5
      ],
      "name": "Kathy Fung"
    },
    {
      "affs": [
        6
      ],
      "name": "Manuel Rodriguez-Justo"
    },
    {
      "affs": [
        2,
        3,
        4
      ],
      "name": "Matteo Cereda"
    },
    {
      "affs": [
        0,
        1,
        2
      ],
      "name": "Francesca D Ciccarelli"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1062tjm0dn1qn.bib",
  "cited_by": 1,
  "doi": "10.70401/exo.2025.0017",
  "fulltext_url": "https://europepmc.org/articles/PMC7619520",
  "id": "1062tjm0dn1qn",
  "issns": [],
  "landing_url": "https://europepmc.org/article/MED/42924602",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W4412475689",
  "pdf_url": "https://europepmc.org/articles/PMC7619520?pdf=render",
  "pmcid": "PMC7619520",
  "pmid": "42924602",
  "published": "2026-07-31",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1062tjm0dn1qn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:02Z",
      "native_id": "MED:42924602",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42924602"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Single-cell and spatial transcriptomics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "Kandinsky: Enabling neighbourhood analysis of spatial omics data for functional insights on cell ecosystems.",
  "title_text": "Kandinsky: Enabling neighbourhood analysis of spatial omics data for functional insights on cell ecosystems.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:21:02Z",
  "url": "https://research.draconitic.com/paper/1062tjm0dn1qn",
  "venue": "EXO : beyond the cell",
  "versions": []
}