Evidence map›Paper›PMID 38641842›Full record

ArticleGenome biology2024

Single Cell Atlas: a single-cell multi-omics human cell encyclopedia.

Lu Pan, Paolo Parini, Roman Tremmel, Joseph Loscalzo, Volker M Lauschke, Bradley A Maron, Paola Paci, Ingemar Ernberg, Nguan Soon Tan, Zehuan Liao and 4 more

Abstract read
In one paragraph

Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Review
  2. Article
  3. Computational modelling of cell identity.The Biochemical journal · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Lu PanInstitute of Environmental Medicine, Karolinska Institutet, 171 65, Solna, Sweden.
Paolo PariniCardio Metabolic Unit, Department of Medicine, and, Department of Laboratory Medicine , Karolinska Institutet, 141 86, Stockholm, Sweden.
Roman TremmelDr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, 70376, Stuttgart, Germany.
Joseph LoscalzoDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
Volker M LauschkeDr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, 70376, Stuttgart, Germany.
Bradley A MaronDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
Paola PaciDepartment of Computer, Control and Management Engineering, Sapienza University of Rome, 00185, Rome, Italy.
Ingemar ErnbergDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 65, Solna, Sweden.
Nguan Soon TanSchool of Biological Sciences, Nanyang Technological University, Singapore, 637551, Singapore.
Zehuan LiaoDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 171 65, Solna, Sweden.
Weiyao YinInstitute of Environmental Medicine, Karolinska Institutet, 171 65, Solna, Sweden.
Sundararaman RengarajanDepartment of Physical Therapy, Movement & Rehabilitation Sciences, Northeastern University, Boston, MA, 02115, USA.
Xuexin LiDepartment of General Surgery, The Fourth Affiliated Hospital, China Medical University, Shenyang, 110032, China. xuexin.li@ki.se.ORCID 0000-0001-5824-9720
SCA Consortium

Funding

Karolinska Institutet C24401073Karolinska Institutet C331612602Karolinska Institutet C62623013
6 · The paper itself

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.

Indexed as

AscomycotaMultiomicsAdultDatabases, FactualFetusGene Expression ProfilingHumansFlow cytometryHuman databaseMass cytometryMulti-omicsSingle-cell ATAC-sequencingSingle Cell AtlasSingle-cell immune profilingSingle-cell omicsSingle-cell RNA-sequencingSpatial transcriptomics

Identifiers

PMID38641842
PMCPMC11027364

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.