{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T09:51:47Z","timestamp":1788947507802,"version":"build-2803163510"},"posted":{"date-parts":[[2025,10,3]]},"group-title":"Genomics","reference-count":46,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T00:00:00Z","timestamp":1759449600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,5,20]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                <jats:p>Single-cell Omic atlases are transforming biology and medicine, yet their demographic representativeness has not been systematically evaluated. We analyzed &gt;13,500 samples from the Human Cell Atlas (HCA), Human Tumor Atlas Network (HTAN), and PsychAD Consortium. Benchmarking against global and US general and disease-prevalence data, we found a striking, pervasive European over-representation and under-representation of Asian and Latino individuals. Nearly 70% of HCA samples lacked ancestry annotation, and among annotated samples, Europeans were over-represented sixfold. PsychAD was nearly two-thirds European. HTAN tumors were 69% European, with several cancer types showing sex skews beyond expected incidence. These disparities highlight that current single-cell resources risk embedding inequities into AI foundational models, biomarker discovery, and therapeutic development. We contextualize these findings within the structural, economic, and regulatory, survey the growing ecosystem of diversity-focused initiatives, and provide an actionable, field-specific checklist to help research teams design single-cell studies whose benefits extend equitably across populations.<\/jats:p>","DOI":"10.1101\/2025.10.01.677375","type":"posted-content","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T15:25:16Z","timestamp":1759505116000},"source":"Crossref","is-referenced-by-count":1,"title":["Are Different Populations Fairly Represented in Single-Cell Omic Atlases?"],"prefix":"10.64898","author":[{"given":"Catrina","family":"Yang","sequence":"first","affiliation":[{"name":"University of Oxford, Green Templeton College, Medical Sciences Division, Oxford, OX2 6HG, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kavitharini","family":"Saravanan","sequence":"additional","affiliation":[{"name":"University of North Carolina at Charlotte, Charlotte, NC, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aryan","family":"Saharan","sequence":"additional","affiliation":[{"name":"Saint Louis University, St. Louis, MO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5537-5817","authenticated-orcid":false,"given":"Kuan-lin","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Genetics and Genomic Sciences, Department of Artificial Intelligence and Human Health, Center for Transformative Disease Modeling, Tisch Cancer Institute, Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, 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