{
  "abstract": "Targeted spatial transcriptomics platforms such as 10x Genomics Xenium measure a predefined panel of genes. A gene is usually detected in fewer cells in the spatial assay than in the single-cell RNA sequencing (scRNA-seq) reference used to choose it, by an amount that differs from gene to gene. We present eXtensible Spatial Panel Evaluation And Refinement (X- SPEAR), a framework for designing and checking Xenium gene panels. Its marker-selection method, Decision-rule Aggregation for Rare-cell Typing (DART), learns short Boolean gene rules and keeps several gene-disjoint rules per cell type. DART first thins the reference to per-gene detection rates measured in a previous experiment, which we call a Xenium prior, so no Xenium data from the target sample are needed before the panel is ordered. A Xenium prior helped most when it matched the target’s assay chemistry and species, even when it came from a different tissue, and a mismatched prior could lower accuracy. With such a prior, DART outperformed four marker-selection methods on held-out Xenium data from ovarian cancer, mouse brain and cervical cancer at matched panel size: by 0.04–0.10 macro-averaged F 1 score (macro- F 1 ) over the Wilcoxon rank-sum test, 0.04–0.08 over COSine similarity-based marker Gene identification (COSG), 0.10–0.17 over Necessary and Sufficient Forest (NS-Forest) and 0.04–0.08 over the probe-set selection method Spapros. It reached the Wilcoxon test’s best accuracy with 42–69% fewer genes. DART’s rules agree with the classifier that uses the panel and name recognisable marker programs for each cell type. X-SPEAR also checks the probes of any panel for predicted off-target transcripts that are expressed in other cell types. X-SPEAR is available as an open-source Python package.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "name": "Rushil Patel",
      "orcid": "0009-0006-1514-6995"
    },
    {
      "name": "Bryant Duong"
    },
    {
      "name": "Veer Patel"
    },
    {
      "name": "Rachel Lyn-Sue"
    },
    {
      "name": "Kyungbin Oh"
    },
    {
      "name": "Yuyan Cheng",
      "orcid": "0000-0003-4647-4917"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6v4bw71bwgws8.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.13.756865",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.756865v1.full",
  "id": "6v4bw71bwgws8",
  "issns": [
    "2692-8205"
  ],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.756865v1",
  "language": "en",
  "licence": "CC0-1.0",
  "licence_label": "CC0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/publicdomain/zero/1.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genomics"
    ],
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7223032392",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.13.756865v1.full.pdf",
  "pmcid": "PMC13738414",
  "pmid": "42995853",
  "published": "2026-10-13",
  "publisher": "Cold Spring Harbor Laboratory Preprints",
  "ris": "https://research.draconitic.com/paper/6v4bw71bwgws8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:28:43Z",
      "native_id": "10.64898/2026.10.13.756865",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.13.756865v1"
    },
    {
      "first_seen": "2026-11-09T12:23:24Z",
      "native_id": "PMC13738414",
      "source": "pmc",
      "url": "https://doi.org/10.64898/2026.10.13.756865"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genomics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "X-SPEAR: An Extensible Framework for Spatial Panel Evaluation and Refinement",
  "title_text": "X-SPEAR: An Extensible Framework for Spatial Panel Evaluation and Refinement",
  "type": "preprint",
  "updated_at": "2026-11-09T12:23:24Z",
  "url": "https://research.draconitic.com/paper/6v4bw71bwgws8",
  "venue": "bioRxiv",
  "versions": []
}