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Revolutionary single-cell and spatial transcriptomics technologies\u2014for example, as deployed by consortia such as the Human Cell Atlas\u2014partially capture this diversity and generate cellular profiles that expand at petabyte scale each year\n                    <jats:sup>1\u20135<\/jats:sup>\n                    . Yet researchers cannot search sequences across these datasets: standard pipelines do not scale or rely on references, retaining only gene or isoform counts, whereas accessing raw sequences requires collecting, downloading and processing millions of large files. Here we present Malva, a computational platform that enables ultrafast, species-agnostic and reference-free interrogation of the raw sequence space, enabling searching for any sequence, mutation, splice junction or pathogen, or spatial location of arbitrary transcripts. The continuously expanding Malva Index currently comprises around 74 million cells from thousands of experiments in health and disease. Malva enables reference-free discovery\u2014researchers can, for example, identify cell types and predict cell\u2013cell similarity directly from sequence composition. Building on Malva\u2019s speed and accuracy, we demonstrate how Malva can be flexibly connected to state-of-the-art neural networks and how to execute complex searches and enable automated analyses. Malva transforms single-cell atlases from static gene count tables into dynamic, sequence-resolved resources that may help to bridge human\u2013machine reasoning about biology.\n                  <\/jats:p>","DOI":"10.1038\/s41586-026-10975-w","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T15:01:38Z","timestamp":1787756498000},"page":"514-524","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Ultrafast and reference-free sequence discovery in single-cell data"],"prefix":"10.1038","volume":"658","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7970-0362","authenticated-orcid":false,"given":"Daniel","family":"Le\u00f3n-Peri\u00f1\u00e1n","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7771-3947","authenticated-orcid":false,"given":"Nikos","family":"Karaiskos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4785-4332","authenticated-orcid":false,"given":"Nikolaus","family":"Rajewsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"10975_CR1","doi-asserted-by":"publisher","first-page":"baaa073","DOI":"10.1093\/database\/baaa073","volume":"2020","author":"V Svensson","year":"2020","unstructured":"Svensson, V., da Veiga Beltrame, E. & Pachter, L. 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