{"entity": "publication", "iuid": "6ea7ad26a32a4eb39b11a8a9b0ef8f06", "timestamp": "2026-09-28T11:15:31.895Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/6ea7ad26a32a4eb39b11a8a9b0ef8f06.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/6ea7ad26a32a4eb39b11a8a9b0ef8f06"}}, "title": "Single Cell Atlas: a single-cell multi-omics human cell encyclopedia.", "authors": [{"family": "Pan", "given": "Lu", "initials": "L"}, {"family": "Parini", "given": "Paolo", "initials": "P"}, {"family": "Tremmel", "given": "Roman", "initials": "R"}, {"family": "Loscalzo", "given": "Joseph", "initials": "J"}, {"family": "Lauschke", "given": "Volker M", "initials": "VM"}, {"family": "Maron", "given": "Bradley A", "initials": "BA"}, {"family": "Paci", "given": "Paola", "initials": "P"}, {"family": "Ernberg", "given": "Ingemar", "initials": "I"}, {"family": "Tan", "given": "Nguan Soon", "initials": "NS"}, {"family": "Liao", "given": "Zehuan", "initials": "Z"}, {"family": "Yin", "given": "Weiyao", "initials": "W"}, {"family": "Rengarajan", "given": "Sundararaman", "initials": "S"}, {"family": "Li", "given": "Xuexin", "initials": "X", "orcid": "0000-0001-5824-9720", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8668449288f0444b93f8473a3407f186.json"}}, {"family": "SCA Consortium", "given": "", "initials": ""}], "type": "journal article", "published": "2024-04-19", "journal": {"title": "Genome Biol.", "issn": "1474-760X", "volume": "25", "issue": "1", "pages": "104", "issn-l": "1474-7596"}, "abstract": "Single-cell sequencing datasets are key in biology and medicine for unraveling insights into heterogeneous cell populations with unprecedented resolution. Here, we construct a single-cell multi-omics map of human tissues through in-depth characterizations of datasets from five single-cell omics, spatial transcriptomics, and two bulk omics across 125 healthy adult and fetal tissues. We construct its complement web-based platform, the Single Cell Atlas (SCA, www.singlecellatlas.org ), to enable vast interactive data exploration of deep multi-omics signatures across human fetal and adult tissues. The atlas resources and database queries aspire to serve as a one-stop, comprehensive, and time-effective resource for various omics studies.", "doi": "10.1186/s13059-024-03246-2", "pmid": "38641842", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11027364"}, {"db": "pii", "key": "10.1186/s13059-024-03246-2"}], "notes": [], "created": "2026-09-23T08:52:06.594Z", "modified": "2026-09-23T08:52:06.674Z"}