An integrated transcriptomic cell atlas of human endoderm-derived organoids
An integrated transcriptomic cell atlas of human endoderm-derived organoids is a dataset published in Nature Genetics (2025). On theSindex it has a DataRank of 0.478, placing it in the top 48.7% of the data-sharing corpus. It has been cited 25 times, with 22 citing works in its 1-hop citation network. Its calibrated FAIR score is 60/100.
Abstract
Human pluripotent stem cells and tissue-resident fetal and adult stem cells can generate epithelial tissues of endodermal origin in vitro that recapitulate aspects of developing and adult human physiology. Here, we integrate single-cell transcriptomes from 218 samples covering organoids and other models of diverse endoderm-derived tissues to establish an initial version of a human endoderm-derived organoid cell atlas. The integration includes nearly one million cells across diverse conditions, data sources and protocols. We compare cell types and states between organoid models and harmonize cell annotations through mapping to primary tissue counterparts. Focusing on the intestine and lung, we provide examples of mapping data from new protocols and show how the atlas can be used as a diverse cohort to assess perturbations and disease models. The human endoderm-derived organoid cell atlas makes diverse datasets centrally available and will be valuable to assess fidelity, characterize perturbed and diseased states, and streamline protocol development.
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
- Dataset classification
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
DataRank Breakdown
Base Score Contribution
0.396
From this paper's citation signal
Citation Network Contribution
0.0823
From 8 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- Fast, sensitive and accurate integration of single-cell data with HarmonyNature Methods201910,108 citationsDataRank 1.4
- Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal nicheNature20097,052 citationsDataRank 1.3
- Generalizing RNA velocity to transient cell states through dynamical modelingNature Biotechnology20203,016 citationsDataRank 1.2
- Benchmarking atlas-level data integration in single-cell genomicsNature Methods20211,376 citationsDataRank 10.3Top 21%
- The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humansScience2022979 citationsDataRank 9.0Top 23%
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 83% comes from its base citations and 17% from the citation network (8 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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