{
  "abstract": "Gaussian process models underlie many spatial transcriptomics tools but typically assume stationary covariance. To test this assumption, we use approximate Bayes factors from R-INLA to compare stationary and non-stationary Matern covariance functions across 12 Visium datasets; covariance non-stationarity is substantially evident as it appears in 3% to 50% of genes across datasets. We find that gene sets associated with effector functions are enriched among genes favoring non-stationary spatial covariance.",
  "abstract_shown": true,
  "affiliations": [
    "University of Victoria"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "P. Velidi"
    },
    {
      "name": "Z. Wei"
    },
    {
      "name": "F. Nathoo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0k0f1q45gh28n.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.08.10.743911",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.08.10.743911v2.full",
  "id": "0k0f1q45gh28n",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.08.10.743911v2",
  "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",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7203548411",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.08.10.743911v2.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-10",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/0k0f1q45gh28n.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:37Z",
      "native_id": "10.64898/2026.08.10.743911",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.08.10.743911v5"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Covariance Nonstationarity is Evident in Spatial Transcriptomics and Provides a New Categorization of Spatially Varying Genes",
  "title_text": "Covariance Nonstationarity is Evident in Spatial Transcriptomics and Provides a New Categorization of Spatially Varying Genes",
  "type": "preprint",
  "updated_at": "2026-10-30T12:28:18Z",
  "url": "https://research.draconitic.com/paper/0k0f1q45gh28n",
  "venue": "bioRxiv",
  "versions": []
}