{
  "abstract": "Single-cell RNA sequencing coupled with V(D)J repertoire profiling enables simultaneous capture of lymphocyte transcriptomes and paired antigen receptor sequences, yet analysis of these multimodal datasets remains a substantial barrier for experimental immunologists. Existing graphical platforms either focus exclusively on transcriptomics or treat repertoire data as a secondary annotation, lacking the deep integration required for systems immunology. Here, I present SingleRepExplorer, a comprehensive, code-free analytical platform designed for 10x Genomics Cell Ranger output, built with R/Shiny, and distributed as a Docker container. The platform unifies transcriptomic preprocessing with Seurat, immune repertoire profiling with scRepertoire and immunarch, receptor–transcriptome multimodal correlation with CoNGA, cell-cell communication inference with CellChat, B-cell phylogenetic lineage reconstruction, CDR3 sequence-similarity networking, and CDR3 physicochemical characterization within a single interactive interface. Interface features include a Memory-Preserved Quality Control module for iterative threshold adjustment without data reload, JavaScript-based Lasso cell selection for interactive subclustering, and direct export of publication-ready editable vector graphics. I applied SingleRepExplorer to a publicly available pooled PBMC dataset from COVID-19 healthcare workers and vaccinated individuals. Without writing code, I observed a massively expanded cytotoxic T lymphocyte clonotype in the HCW_convalescent condition, characterized its diversity metrics, linked it to a transcriptionally distinct effector cluster expressing GNLY, GZMH, NKG7, and CD8A, and mapped its exploratory intercellular signaling footprint, highlighting Cluster 7-derived MIF and CCL5–CCR4 axes within the HCW_convalescent network. These illustrative results demonstrate that SingleRepExplorer enables an experimental immunologist to carry a dataset from raw sequencing output to systems-level hypotheses entirely through a graphical interface, and benchmarking of the platform’s core modules against independent reference workflows is reported alongside. The platform is freely available at https://github.com/amufaamo/SingleRepExplorer .",
  "abstract_shown": true,
  "affiliations": [
    "Bioinformatics Analysis Center, Kagawa University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Masakazu Ishikawa"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/86b2thwb8s6je.bib",
  "cited_by": 0,
  "doi": "10.3389/fimmu.2026.1891118",
  "fulltext_url": null,
  "id": "86b2thwb8s6je",
  "issns": [
    "1664-3224"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1891118/full",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "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": "W7224112137",
  "pdf_url": "https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2026.1891118/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-28",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/86b2thwb8s6je.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:17Z",
      "native_id": "10.3389/fimmu.2026.1891118",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1891118/full"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Single-cell and spatial transcriptomics",
      "subfield": "molecular-biology"
    }
  ],
  "title": "SingleRepExplorer: a unified interactive platform for integrated single-cell transcriptomic and immune repertoire analysis",
  "title_text": "SingleRepExplorer: a unified interactive platform for integrated single-cell transcriptomic and immune repertoire analysis",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:17Z",
  "url": "https://research.draconitic.com/paper/86b2thwb8s6je",
  "venue": "Frontiers in Immunology",
  "versions": []
}