{
  "abstract": "Single-cell atlases are rapidly outgrowing the memory capacity of standard workstations, challenging the in-memory paradigm underlying mainstream computational ecosystems. Here, scAtlasPy decouples scale of atlas from memory capacity by leveraging the disk-resident computing. It enables full-resolution analysis of a 100-million-cell atlas with only 42.9 GB peak memory, whereas state-of-the-art platforms are limited at 3 million cells with 512 GB memory. scAtlasPy achieves 137,745 cells/s, 10.4x faster than scDataset with 82.6% lower memory usage for random minibatch retrieval. Its extensible architecture offers a flexible platform for diverse atlas-scale analytical tasks, facilitating the discovery of complex cellular heterogeneity and functions in massive cell atlases.",
  "abstract_shown": true,
  "affiliations": [
    "XIDIAN UNIVERSITY"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "H. Xu"
    },
    {
      "name": "Y. Ye"
    },
    {
      "name": "S. Zhang"
    },
    {
      "name": "R. Xie"
    },
    {
      "name": "J. Li"
    },
    {
      "name": "J. Lin"
    },
    {
      "name": "Y. Hu"
    },
    {
      "affs": [
        0
      ],
      "name": "L. Gao"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/026rwmcgsf2r6.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.03.748766",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.03.748766v1.full",
  "id": "026rwmcgsf2r6",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.03.748766v1",
  "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": "W7208711159",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.03.748766v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/026rwmcgsf2r6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:18Z",
      "native_id": "10.64898/2026.09.03.748766",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.03.748766v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioinformatics",
      "subfield": "bioinformatics"
    }
  ],
  "title": "Atlas-scale single-cell analysis beyond in-memory paradigm with scAtlasPy",
  "title_text": "Atlas-scale single-cell analysis beyond in-memory paradigm with scAtlasPy",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:18Z",
  "url": "https://research.draconitic.com/paper/026rwmcgsf2r6",
  "venue": "bioRxiv",
  "versions": []
}