The DOI matches its Crossref record; 68 of the 69 references it cites were found in a registry or an index, and 1 are not checked yet; none of the 31 sources its claims cite is checked for support yet.
The single-cell transcriptional landscape of mammalian organogenesis
Open accessAbstract
Mammalian organogenesis is a remarkable process. Within a short timeframe, the cells of the three germ layers transform into an embryo that includes most of the major internal and external organs. Here we investigate the transcriptional dynamics of mouse organogenesis at single-cell resolution. Using single-cell combinatorial indexing, we profiled the transcriptomes of around 2 million cells derived from 61 embryos staged between 9.5 and 13.5 days of gestation, in a single experiment. The resulting ‘mouse organogenesis cell atlas’ (MOCA) provides a global view of developmental processes during this critical window. We use Monocle 3 to identify hundreds of cell types and 56 trajectories, many of which are detected only because of the depth of cellular coverage, and collectively define thousands of corresponding marker genes. We explore the dynamics of gene expression within cell types and trajectories over time, including focused analyses of the apical ectodermal ridge, limb mesenchyme and skeletal muscle. Data from single-cell combinatorial-indexing RNA-sequencing analysis of 2 million cells from mouse embryos between embryonic days 9.5 and 13.5 are compiled in a cell atlas of mouse organogenesis, which provides a global view of developmental processes occurring during this critical period.
Checked 2026-10-07 · 1 reference not checked yet
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This paper uses sci-RNA-seq3 to profile ~2 million cells from 61 mouse embryos staged E9.5–E13.5, producing the mouse organogenesis cell atlas (MOCA) of mid-gestational development. It identifies 38 major cell types, 572 non-doublet subtypes, and 56 developmental subtrajectories, with focused analyses of the apical ectodermal ridge and skeletal myogenesis.
Key findings
- From one experiment, the authors recovered 2,058,652 mouse embryo cells plus 13,359 HEK293T/NIH/3T3 control cells, with a median of 35,272 cells per embryo; sequencing was shallow (~5,000 raw reads per cell) but yielded a median of 671 UMIs (519 genes) per cell.
- MOCA contains 38 major cell types, 655 subclusters (572 non-doublet subtypes), and 56 developmental subtrajectories; 17,789 of 26,183 genes were differentially expressed across major cell types, including 2,863 cell type-specific marker genes.
- Monocle 3 organized 1,524,792 high-quality cells (UMI > 400) into ten major trajectories, and the study matched 96 MCA fetal cell types to 58 MOCA subtypes and 48 BCA cell types to 68 MOCA subtypes.
- Focused analyses identified AER subtype 6.23 (1,237 cells; 0.06% of MOCA) with novel markers Fndc3a, Adamts3, Slc16a10, Snap91, and Pou6f2, and a myogenic trajectory with 2,908 trajectory-dependent genes grouped into 14 patterns.
Methods
- Nuclei were extracted from 61 C57BL/6 mouse embryos at E9.5, E10.5, E11.5, E12.5, or E13.5, fixed, and processed with sci-RNA-seq3 combinatorial indexing; the library was sequenced in one Illumina NovaSeq run yielding 11 billion reads.
- Cells with UMI ≥ 200 were analyzed by Louvain clustering and t-SNE, followed by iterative subclustering; Scrublet was used for doublet detection, and marker genes were identified by differential expression.
- Trajectory inference used Monocle 3 with UMAP, PAGA/Louvain partitioning, principal graph learning, pseudotime, and Moran’s I; whole-mount in situ hybridization validated selected markers.
Limitations
- Paper-stated: only ~7% of cells entering the experiment were ultimately profiled, largely due to filtration steps; the matrix is sparse, the study does not exceed 1-fold coverage at any timepoint, and extremely rare cell types may be missed.
- Paper-stated: annotations are preliminary because mid-gestational mouse development has not been extensively studied at single-cell resolution, many published markers have limited specificity, and whole disaggregated embryos make anatomical assignment challenging.
- Evident from the text: sequencing was shallow (~5,000 raw reads per cell; median 671 UMIs), nuclear profiles were primarily intronic/nascent (59% intronic, 25% exonic), the estimated doublet rate was 10.3%, 13% of subtypes were annotated as likely artifacts, and trajectory discontinuity likely reflects missing ancestral states before E9.5.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
86 Own result · 27 Not checked yet · 18 Own interpretation · 17 Own method · 6 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Despite shallow sequencing (~5,000 raw reads per cell; 46% duplicate rate), we recovered a median of 671 UMIs (519 genes) per cell”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We annotated 13% of subtypes as likely artifacts (>10% of cells in these subtypes are predicted doublets”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“at E9.5, we detect cells corresponding to the primitive erythroid lineage, originating from the yolk sack (cluster 26; marked by Hbb−bh1).”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“3.7-fold deeper sequencing of a subset of wells nearly doubled complexity (to a median of 1,142 UMIs per cell; 87% duplicate rate).”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For the remaining 572 subtypes, we identified a median of 20 subtype-specific markers”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We profiled a median of 35,272 cells per embryo”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“17,789 of 26,183 genes (68%) were differentially expressed across the major cell types (5% FDR; Supplementary Table 4).”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We observed marked changes in the proportions of cell types during organogenesis.”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, the definitive erythroid lineage, originating from the fetal liver (cluster 22; marked by Hbb−bs), progressively displaces it to become the exclusive red cell lineage by E13.5”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“A similar analysis matched 48 cell types annotated in a recent mouse brain atlas (BCA)32 to 68 MOCA subtypes with high specificity”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
What the sources say
- Not checked yetcites [32] Zeisel, A. et al. Molecular architecture of the mouse nervous system. Cell 174, 999–1014 (2018). source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 43
- Probably not a substantial claim. 30
- The quote only partly states this claim. 1
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“most subtypes can be distinguished from all 571 other non-doublet subtypes based on marker gene sets and >4-fold expression differences (63% with 2 markers, 95% with 4 markers”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“our ‘shotgun cellular coverage’ of the mouse embryo is 0.8× at E9.5 (200K cells/embryo; 152K profiled across all replicates), 0.3× at E10.5 (1.1M cells/embryo; 378K profiled), 0.2× at E11.5 (2.6M cells/embryo; 616K profiled), 0.08× at E12.5 (6M cells/embryo; 475K profiled), and 0.03× at E13.5 (13M cells/embryo; 437K profiled).”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“We used Scrublet22 to detect 4.3% likely doublet cells, corresponding to a doublet estimate of 10.3% including both within- and between-cluster doublets”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
What the sources say
- Not checked yetcites [22] Wolock, S. L., Lopez, R. & Klein, A. M. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Preprint at https://www.biorxiv.org/content/10.1101/357368v1 (2018). source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Embryos were readily identified as male (n = 31) or female (n = 30)”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plainn = 31- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“From one experiment, we recovered 2,058,652 cells from mouse embryos and 13,359 cells from HEK293T or NIH/3T3 cells (UMI (unique molecular identifier) count ≥ 200).”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We performed pseudotemporal ordering of AER cells, yielding a simple early-to-late trajectory and 710 differentially expressed genes”
§ The single cell transcriptional landscape of mammalian organogenesis > Characterization of the apical ectodermal ridge
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although detected at all timepoints and nearly all embryos, the estimated number of AER cells per embryo peaks between E10.5 and E11.5”
§ The single cell transcriptional landscape of mammalian organogenesis > Characterization of the apical ectodermal ridge
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Amongst these, we identified 2,863 cell type-specific marker genes (mean 75; those with >2-fold expression difference between first and second ranked cell type; a cutoff of >5-fold yielded 932 marker genes”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As we are profiling RNA in nuclei, 59% of UMIs per cell strand-specifically mapped to introns, and 25% to exons.”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Later stage embryos exhibited somewhat reduced UMI counts, possibly reflecting decreasing nuclear mRNA content”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Reassuringly, cells from replicate embryos of the same developmental stage were similarly distributed, whereas cells from different stages were not”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 655 subtypes consist of a median of 1,869 cells, and range from 51 (a subtype of notochord) to 65,894 (a subtype of connective tissue progenitors) cells”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 38 major cell types are represented by a median of 47,073 cells, the largest containing 144,648 cells (connective tissue progenitors), and the smallest only 1,000 cells (neutrophils).”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While most major cell types proliferated exponentially, a few were transient and disappeared by E13.5”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For example, the primordial germ cell subcluster 16.13, which includes just 88 of 2,058,652 cells in the dataset, is contributed to by cells from all five timepoints.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Cell clustering, t-SNE visualization and marker gene identification
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There are three neural crest trajectories, corresponding to sensory neurons, Schwann cell precursors and melanocytes. The hematopoietic trajectory includes megakaryocytes, erythrocytes and white blood cells, while the remaining four trajectories (endothelial, epithelial, hepatic, lens) each correspond to a single major cell type”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“consider primordial germ cells, which were readily identifiable despite their rarity (subtypes 16.13 and 6.27, which sum to 269/2,058,652 cells or 0.01% of MOCA).”
§ The single cell transcriptional landscape of mammalian organogenesis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that UMAP finished processing two million cells dataset in around 3 CPU hours while t-SNE took more than 64 CPU hours.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plainSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In some cases, we observe a single, simple linear trajectory. However, we also observe many examples of branching trajectories, as well as of cell types that appear to be generated via multiple parallel paths.”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“We detected 4.3% potential doublet cells in the whole data set, which corresponds to an overall estimated doublet rate of 10.3% (including both within- and between-cluster doublets).”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Cell clustering, t-SNE visualization and marker gene identification
What the sources say
- Not checked yetcites [63] Mao, Q., Yang, L., Wang, L., Goodison, S. & Sun, Y. SimplePPT: a simple principal tree algorithm. In Proc. 2015 SIAM International Conference on Data Mining (eds Venkatasubramanian, S. & Ye, J.) 792–800 (SIAM, 2015). source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Cells expressing Myf5 co-localized with a subset of Pax7+ cells, consistent with the role of Myf5 in embryonic myogenesis46.”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing skeletal myogenesis
What the sources say
- Not checked yetcites [46] Comai, G., Sambasivan, R., Gopalakrishnan, S. & Tajbakhsh, S. Variations in the efficiency of lineage marking and ablation confound distinctions between myogenic cell populations. Dev. Cell 31, 654–667 (2014). source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“After removing 12% of cells corresponding to doublet-annotated cells and/or subclusters, we iteratively reanalyzed the ten major trajectories”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although the estimated number of cells per embryo in each trajectory increases exponentially, their proportions remain relatively stable, with the exception of hepatocytes, which markedly increase their contribution from 0.3% at E9.5 to 2.8% at E13.5”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we used Monocle 3 to construct a myogenesis-specific trajectory, which featured multiple focal concentrations of E9.5 cells, with cells from later stages distributed over several paths radiating outward”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing skeletal myogenesis
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the resulting atlas (MOCA), we identify over 500 subtypes of cells and 56 developmental subtrajectories, each distinguished by multiple marker genes and collectively spanning essentially every organ system.”
§ The single cell transcriptional landscape of mammalian organogenesis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Compared with skipping UMI error correction, 99.4% of reads remain after UMI error correction, which indicated to us that the error correction step only has minor impact on the estimated UMI counts per cell (less than 1%).”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Processing of sequencing reads
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“cell types found at later developmental timepoints such as inhibitory neurons are connected to early CNS precursors (radial glia) by a ‘bridge’ of neural progenitor cells; however, the same radial glial cells project in a different direction towards increasingly mature oligodendrocytes”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The estimated nuclei extraction efficiency ranged from 60% to 85%.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Mouse embryo nuclei extraction and fixation
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Globally, we detected 2,908 genes expressed in a trajectory-dependent manner (FDR < 0.05 and Moran’s I > 0.01) that grouped into 14 distinct patterns”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing skeletal myogenesis
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Doublet-derived subclusters (2/29 epithelial subtypes and 5/16 endothelial subtypes) are excluded from these plots”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A total of 2,908 genes were clustered via hierarchical clustering. The dendrogram was cut into 14 modules using the cutree function in R”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Some cells from complex trajectories (mesenchymal trajectory, neural tube/notochord trajectory, epithelial trajectory and endothelial trajectory) show outlier pseudotime values (more than 3 standard deviation higher than the mean values).”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“At a sequencing depth of 23,207 reads per cell, we observed a median of 5,461 UMIs per HEK293T cell and 5,087 UMIs per NIH/3T3 cell”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plainn = 10,914- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The number of clusters and subclusters identified with the same parameters drops from 38 (a, bottom plot) to 27 (c) and 16 (b, bottom plot) to 12 (c), respectively.”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“644 of 655 sub-clusters (98%) have at least one such gene marker with a 2-fold difference, and 441 of 655 (67%) have at least one such marker with a 5-fold difference.”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“40 clusters were identified.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Cell clustering, t-SNE visualization and marker gene identification
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The detected doublet cell rate was modestly correlated with number of cells profiled per well during reverse transcription (Spearman’s rho: 0.35).”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We merged two groups corresponding to sensory neurons (12 & 3), and another two groups corresponding to blood cells (6 & 7), as each pair was closely located in UMAP space upon visual inspection, yielding the ten supergroups shown in a similar heatmap in Fig. 4b.”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although the estimated number of cells per embryo in each of these supergroups increases exponentially, their proportions remain relatively stable”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Another two clusters both appeared to correspond to the definitive erythroid lineage and were merged.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Cell clustering, t-SNE visualization and marker gene identification
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Our profiles may thus primarily reflect nascent transcription, temporally offset but also predictive21 of the cellular transcriptome.”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
What the sources say
- Not checked yetcites [21] La Manno, G. et al. RNA velocity of single cells. Nature 560, 494–498 (2018). source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As expected, MOCA subtypes that failed to match MCA cell types tended to derive from earlier stages (e.g. neural tube) or were rare (e.g. lens), while MCA cell types that failed MOCA subtypes were mostly tissue-specific immune or epithelial cells, potentially because they emerge after E13.5.”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“A limitation is that only ~7% of cells entering the experiment were ultimately profiled, with losses largely consequent to filtration steps intended to remove aggregates of nuclei.”
§ The single cell transcriptional landscape of mammalian organogenesis > Single cell RNA-seq of 2 million cells
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“However, although two scRNA-seq atlases of mouse were recently released10,11, they are mostly restricted to adult organs, and do not attempt to characterize the emergence and dynamics of cell types during development.”
§ The single cell transcriptional landscape of mammalian organogenesis > Main
What the sources say
- Not checked yetcites [10] Han, X. et al. Mapping the Mouse Cell Atlas by Microwell-seq. Cell 172, 1091–1107 (2018). source
- Not checked yetcites [11] The Tabula Muris Consortium, Quake, S. R., Wyss-Coray, T. & Darmanis, S. Transcriptomic characterization of 20 organs and tissues from mouse at single cell resolution creates a Tabula Muris. Preprint at https://www.biorxiv.org/content/10.1101/237446v2 (2018).
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Nonetheless, the atlases unquestionably inform one another, as the MCA’s anatomical resolution is useful for localizing MOCA subtypes, while MOCA’s developmental focus informs the embryonic origin of MCA cell types”
§ The single cell transcriptional landscape of mammalian organogenesis > Identification of cell types and subtypes
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“An additional path traversed by cells from E9.5, which expressed Lhx2, Tbx1, and Pitx2 but very low levels of Pax3, feeds into the trajectory just upstream of the Myf5 and Myod1 segments, and possibly corresponds to pharyngeal mesoderm45.”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing skeletal myogenesis
What the sources say
- Not checked yetcites [45] Braun, T. & Gautel, M. Transcriptional mechanisms regulating skeletal muscle differentiation, growth and homeostasis. Nat. Rev. Mol. Cell Biol. 12, 349–361 (2011). source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“No statistical methods were used to predetermine sample size.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Data reporting
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The UMAP algorithm itself is also more efficient (the algorithm complexity of UMAP is O(N) vs. O(Nlog(N)) for t-SNE).”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
What the sources say
- Not checked yetcites [66]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Monocle 3’s implementation of the above procedures (in the partitionCells() function) scales to millions of cells.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Most contemporary algorithms for trajectory reconstruction assume a continuous manifold (whereas our data begin at E9.5, and therefore are missing at least some ancestral states) and do not allow for convergence of cell fates”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Investigators were blinded to group allocation during data collection and analysis: embryo collection and sci-RNA-seq3 analysis were performed by two different researchers.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Data reporting
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Embryos were collected from at least three independent litters per development stage.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Embryo dissection
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Embryos used in experiment were randomized before sample preparation.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Data reporting
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Mid-gestational mouse development has not previously been extensively studied at single cell resolution”
§ The single cell transcriptional landscape of mammalian organogenesis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Notably, the AER subtrajectory projects out of surface ectoderm and then back into epidermis, consistent with its transitory nature.”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The third major enhancement is that Monocle 3 can learn principal graphs with loops instead of requiring that the trajectory be a tree.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“many published markers have limited specificity.”
§ The single cell transcriptional landscape of mammalian organogenesis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“both CNS excitatory and inhibitory neurons appear to develop through multiple, convergent trajectories, possibly due to the maturation in multiple anatomical locations.”
§ The single cell transcriptional landscape of mammalian organogenesis > Reconstructing developmental trajectories
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, although we are reasonably confident in our annotations, they should be regarded as preliminary.”
§ The single cell transcriptional landscape of mammalian organogenesis > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“However, where t-SNE mainly aims to place highly similar cells in the same regions of a low-dimensional space, UMAP also preserves longer-range distance relationships.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
What the sources say
- Not checked yetcites [66]
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Running time and fine detail in the trajectory will depend on the number principal graph nodes; more nodes generally results in a more accurate tree but at increased running time.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Its visualization quality is competitive with the popular t-SNE (t-stochastic neighbor embedding) method used widely in single-cell transcriptomics.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
What the sources say
- Not checked yetcites [66]
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Embryos were readily separated into females (more reads mapping to Xist than chrY genes) and males (more reads mapping to chrY genes than Xist).”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Whole mouse embryo analysis
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“PAGA then constructs a graph in which the vertices are Louvain communities. Two vertices are linked with an edge in the PAGA graph when the cells in the respective communities are neighbors in the kNN graph more frequently than would be expected under a simple binomial model68.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
What the sources say
- Not checked yetcites [68]
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In order to calculate cell-wise pseudotime, we developed a projection strategy which is applicable to datasets with millions of cells.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Although SimplePPT does provide tuning parameters that control graph smoothness to a certain extent, we have found that a simple heuristic pruning procedure is effective and easier for users to understand how to control.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > Trajectory inference with Monocle 3
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The authors state this as an assumption.
About 100 cells are required to detect a cell type.
“Assuming that ~100 cells are required to detect a cell type”
The authors state this as an assumption.
The cell type in question is present at only one timepoint.
“and that the cell type in question is only present at one timepoint”
The authors state this as an assumption.
Gene expression follows a negative binomial distribution in the AER spline fitting.
“assuming gene expression following the negative binomial distribution”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“we applied Monocle336 pseudotime to 2,190 radial glia lineage cells (Figure 4B). We identified three trajectories corresponding to distinct cell fates, termed the ependymal (EPD) trajectory, astrocyte (ASC) trajectory, and the neural intermediate progenitor cell (NPC) trajectory.”
From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [36]
In the citing paper
“Recent cell atlases using high-throughput single-cell RNA-sequencing (scRNA-seq) and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) technologies have provided an increasingly detailed view of mouse developmental gene expression and gene regulatory dynamics”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Cao et al., 2019
In the citing paper
“These stages include most of the key events in mouse organogenesis (Cao et al., 2019).”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Cao et al., 2019
In the citing paper
“Spatial pseudotime analysis of progenitor cells in these three stages using monocle 3 (Cao et al., 2019) confirmed these results (Figures 5D-5F and S7E).”
From Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays (2022) · cites this paper as Cao et al., 2019
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > sci-RNA-seq3 library preparation and sequencing
“After ligation reaction, 60 μL nuclei dilution buffer (10 mM Tris-HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl2 and 1% BSA) was added into each well.”
§ The single cell transcriptional landscape of mammalian organogenesis > METHODS > sci-RNA-seq3 library preparation and sequencing
“The ligation reaction was done at 16°C for 3 hours.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
“(j) t-SNE visualization of subcluster specific marker expression (as example, cell number n = 74,651): Calb1 (left), Nox3 (middle) and Tex14 (right) are gene markers for three endothelial subclusters.”
§ The single cell transcriptional landscape of mammalian organogenesis > Extended Data
“(c) t-SNE visualization and marker-based annotation of endothelial cell subtypes (n = 35,878).”
Citations
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S. L., Jagodnik, K. M., Lachmann, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw377 · Cited by 10,799
UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826
SCANPY: large-scale single-cell gene expression data analysis
Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology · doi:10.1186/s13059-017-1382-0 · Cited by 8,881
NOTES ON CONTINUOUS STOCHASTIC PHENOMENA
MORAN, P. A. P. (1950) · Biometrika · doi:10.1093/biomet/37.1-2.17 · Cited by 8,622
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N. J., Livak, K. J., Mikkelsen, T. S., & Rinn, J. L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2859 · Cited by 7,314
Self-citationUMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
McInnes, L., Healy, J., & Melville, J. (2018) · arXiv · doi:10.48550/arxiv.1802.03426 · Cited by 7,101
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422
Cited by
Sorted by citations
Items 901–1,000 of 1,025
Reilly, A., Creamer, J. P., Stewart, S., Stolla, M. C., Wang, Y., Du, J., Wellington, R., Busch, S., Estey, E. H., Becker, P. S., et al. (2022) · Cell stem cell · doi:10.1016/j.stem.2022.02.010 · Cited by 40
TFAP2 paralogs facilitate chromatin access for MITF at pigmentation and cell proliferation genes
Kenny, C., Dilshat, R., Seberg, H., Otterloo, E. V., Bonde, G., Helverson, A., Franke, C. M., Steingrı́msson, E., & Cornell, R. A. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010207 · Cited by 40
Neuronal cell types, projections, and spatial organization of the central amygdala
O’Leary, T. P., Kendrick, R. M., Bristow, B. N., Sullivan, K. E., Wang, L., Clements, J., Lemire, A. L., & Cembrowski, M. S. (2022) · iScience · doi:10.1016/j.isci.2022.105497 · Cited by 42
Normalization for sampled count data
Booeshaghi, A. S., Hallgrímsdóttir, I. B., Gálvez-Merchán, Á., & Pachter, L. (2022) · doi:10.1101/2022.05.06.490859 · Cited by 39
The Origins of Phenotypic Heterogeneity in Cancer
Lenz, G., Onzi, G. R., Lenz, L. S., Buss, J. H., dos Santos, J. A., & Begnini, K. R. (2021) · Cancer Research · doi:10.1158/0008-5472.can-21-1940 · Cited by 39
Stage-specific nutritional management and developmental programming to optimize meat production
Zhao, L., Liu, X., Gomez, N. A., Gao, Y., Son, J. S., Chae, S. A., Zhu, M. J., & Du, . (2023) · Journal of Animal Science and Biotechnology/Journal of animal science and biotechnology · doi:10.1186/s40104-022-00805-0 · Cited by 39
Tresenrider, A. M., Sridhar, A., Eldred, K. C., Cuschieri, S. A., Hoffer, D., Trapnell, C., & Reh, T. A. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100548 · Cited by 39
Self-citationGleason, C. E., Dickson, M. A., Klein, M. E., Antonescu, C. R., Gularte‐Mérida, R., Benitez, M., Delgado, J. I., Kataru, R. P., Tan, M. W. Y., Bradić, M., et al. (2023) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-23-2378 · Cited by 39
Imaz-Rosshandler, I., Rode, C., Guibentif, C., Harland, L. T. G., Ton, M.-L. N., Dhapola, P., Keitley, D., Argelaguet, R., Calero‐Nieto, F. J., Nichols, J., et al. (2023) · Development · doi:10.1242/dev.201867 · Cited by 41
Kim, W. K., Buckley, A. J., Lee, D., Hiroto, A., Nenninger, C. H., Olson, A. W., Wang, J., Li, Z., Vikram, R., Adzavon, Y. M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45489-4 · Cited by 39
Park, S. S., Lee, Y., Choi, Y. W., Lim, S. B., Park, S. H., Kim, H. K., Shin, J. S., Kim, Y. H., Lee, D. H., Kim, J., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113912 · Cited by 39
Johnson, C., Williams, M., Sham, K., Belluschi, S., Ma, W., Wang, X., Lau, W. W. Y., Kaufmann, K. B., Krivdova, G., Calderbank, E. F., et al. (2024) · Blood · doi:10.1182/blood.2023021426 · Cited by 45
Ye, K., Bu, F., Zhong, L., Dong, Z., Ma, Z., Tang, Z., Zhang, Y., Yang, X. Y., Xu, X., Wang, E., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50737-8 · Cited by 39
Xia, K., Luo, P., Yu, J., He, S., Dong, L., Gao, F., Chen, X., Ye, Y., Gao, Y., Ma, Y., et al. (2024) · Human Reproduction · doi:10.1093/humrep/deae199 · Cited by 40
Huang, H.-Y., Chen, Y.-Z., Zhao, C., Zheng, X.-N., Yu, K., Yue, J., Ju, H., Shi, Y., & Tian, L. H. (2024) · Nature Communications · doi:10.1038/s41467-024-53659-7 · Cited by 39
Nano, P. R., Fazzari, E., Azizad, D. J., Martija, A. A., Nguyen, C. V., Wang, S., Giang, V., Kan, R. L., Yoo, J., Wick, B. D., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01933-2 · Cited by 42
High-throughput screening of nanoparticles in drug delivery
Tomé, I., Francisco, V., Fernandes, H., & Ferreira, L. (2021) · APL Bioengineering · doi:10.1063/5.0057204 · Cited by 39
scMRA: a robust deep learning method to annotate scRNA-seq data with multiple reference datasets
Yuan, M., Chen, L., & Deng, M. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab700 · Cited by 39
Ex vivo reconstitution of fetal oocyte development in humans and cynomolgus monkeys
Mizuta, K., Katou, Y., Nakakita, B., Kishine, A., Nosaka, Y., Saito, S., Iwatani, C., Tsuchiya, H., Kawamoto, I., Nakaya, M., et al. (2022) · The EMBO Journal · doi:10.15252/embj.2022110815 · Cited by 39
Zhai, Y., Singh, P., Dolnik, A., Brázda, P., Atlasy, N., Gaudio, N. D., Döhner, K., Döhner, H., Minucci, S., Martens, J. H. A., et al. (2022) · Molecular Cancer · doi:10.1186/s12943-022-01635-4 · Cited by 38
Single-cell landscape of primary central nervous system diffuse large B-cell lymphoma
Liu, N., Jiang, C., Yao, X., Fang, M., Qiao, X., Zhu, L., Yang, Z., Gao, X., Ji, Y., Niu, C., et al. (2023) · Cell Discovery · doi:10.1038/s41421-023-00559-7 · Cited by 38
Vijayakumar, S., Sala, R., Kang, G., Chen, A. C., Pablo, M. A., Adebayo, A. I., Cipriano, A., Fowler, J. L., Gomes, D., Ang, L. T., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41302-w · Cited by 38
Reconstructing axial progenitor field dynamics in mouse stem cell-derived embryoids
Bolondi, A., Law, B. K., Kretzmer, H., Gassaloglu, S. I., Buschow, R., Riemenschneider, C., Yang, D., Walther, M., Veenvliet, J. V., Meissner, A., et al. (2024) · Developmental Cell · doi:10.1016/j.devcel.2024.03.024 · Cited by 38
Tan, Z., Chen, P., Dong, X., Guo, S., Leung, V., Cheung, J. P. Y., Chan, D., Richardson, S. M., Hoyland, J. A., To, M. K.-T., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114342 · Cited by 38
Aging human abdominal subcutaneous white adipose tissue at single cell resolution
Whytock, K. L., Divoux, A., Sun, Y., Pino, M. F., Yu, G., Jin, C. A., Robino, J. J., Plekhanov, A., Varlamov, O., Smith, S. R., et al. (2024) · Aging Cell · doi:10.1111/acel.14287 · Cited by 39
Zhong, T., Li, X., Lei, K., Tang, R., Deng, Q., Love, P. E., Zhou, Z., Zhao, B., & Li, X. (2024) · Nature Communications · doi:10.1038/s41467-024-53264-8 · Cited by 38
Gao, M., Wang, M., Zhou, S., Hou, J., He, W., Shu, Y., & Wang, X. (2024) · Cancer Cell International · doi:10.1186/s12935-024-03592-y · Cited by 38
Liu, Y., Ye, G., Huang, L., Zhang, C., Sheng, Y., Wu, B., Han, L., Wu, C., Dong, B., & Qi, Y. (2020) · Aging · doi:10.18632/aging.103945 · Cited by 38
Taylor, S. A., Chen, S.-Y., Gadhvi, G. T., Feng, L., Gromer, K. D., Abdala‐Valencia, H., Nam, K.-W., Dominguez, S. T., Montgomery, A. B., Reyfman, P. A., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0244743 · Cited by 38
Computational Stem Cell Biology: Open Questions and Guiding Principles
Cahan, P., Cacchiarelli, D., Dunn, S.-J., Hemberg, M., Lopes, S. M. C. D. S., Morris, S. A., Rackham, O. J. L., del Sol, A., & Wells, C. A. (2021) · Cell stem cell · doi:10.1016/j.stem.2020.12.012 · Cited by 38
Stepwise chromatin and transcriptional acquisition of an intraepithelial lymphocyte program
London, M., Bilate, A. M. B., Castro, T. B. R., Sujino, T., & Mucida, D. (2021) · Nature Immunology · doi:10.1038/s41590-021-00883-8 · Cited by 38
Pietrobono, S., Gaudio, E., Gagliardi, S., Zitani, M., Carrassa, L., Migliorini, F., Petricci, E., Manetti, F., Makukhin, N., Bond, A. G., et al. (2021) · Oncogene · doi:10.1038/s41388-021-01783-9 · Cited by 38
Ballarin, L., Karahan, A., Salvetti, A., Rossi, L., Manni, L., Rinkevich, B., Rosner, A., Voskoboynik, A., Rosental, B., Canesi, L., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.688106 · Cited by 38
Fa, B., Wei, T., Zhou, Y., Johnston, L. J., Yuan, X., Ma, Y., Zhang, Y., & Yu, Z. (2021) · Nature Communications · doi:10.1038/s41467-021-24489-8 · Cited by 38
Gli1+ progenitors mediate bone anabolic function of teriparatide via Hh and Igf signaling
Shi, Y., Liao, X., Long, J. Y., Yao, L., Chen, J., Yin, B., Lou, F., He, G., Ye, L., Qin, L., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109542 · Cited by 38
High-throughput Microwell-seq 2.0 profiles massively multiplexed chemical perturbation
Chen, H., Liao, Y., Zhang, G., Sun, Z., Yang, L. X., Fang, X., Sun, H., Ma, L., Fu, Y., Li, J., et al. (2021) · Cell Discovery · doi:10.1038/s41421-021-00333-7 · Cited by 38
Gaydosik, A. M., Stonesifer, C. J., Khaleel, A. E., Geskin, L. J., & Fuschiotti, P. (2022) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-21-4437 · Cited by 38
Larson, A., Codden, C. J., Huggins, G. S., Rastegar, H., Chen, F. Y., Maron, B. J., Rowin, E. J., Maron, M. S., & Chin, M. T. (2022) · Scientific Reports · doi:10.1038/s41598-022-08561-x · Cited by 38
Ichino, L., Picard, C. L., Yun, J., Chotai, M., Wang, S., Lin, E. K., Papareddy, R. K., Xue, Y., & Jacobsen, S. E. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111699 · Cited by 38
Quan, Y., Wei, W., Ergin, V., Rameshbabu, A. P., Huang, M., Tian, C., Saladi, S. V., Indzhykulian, A. A., & Chen, Z. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2215253120 · Cited by 37
Longitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1
Tejwani, L., Ravindra, N. G., Lee, C., Cheng, Y., Nguyen, B., Luttik, K. P., Ni, L., Zhang, S., Morrison, L. M., Gionco, J. T., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.10.039 · Cited by 37
Liu, Q., Ma, W., Chen, R., Li, S., Wang, Q., Wei, C., Hong, Y., Sun, H., Cheng, Q., Zhao, J., et al. (2024) · Advanced Science · doi:10.1002/advs.202308384 · Cited by 39
Simon, M., Stüve, P., Schmidleithner, L., Bittner, S., Beumer, N., Strieder, N., Schmidl, C., Pant, A., Gebhard, C., Eigenberger, A., et al. (2024) · Immunity · doi:10.1016/j.immuni.2024.06.015 · Cited by 37
Joint trajectory inference for single-cell genomics using deep learning with a mixture prior
Du, J., Chen, T., Gao, M., & Wang, J. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2316256121 · Cited by 41
Wang, H., He, X., Ma, M., Dou, T., Wei, Y., Rux, D. R., Qin, L., Yang, Y., Zhu, Y., & Yao, L. (2025) · Communications Biology · doi:10.1038/s42003-025-08316-0 · Cited by 37
GZMK+CD8+ T cells: multifaceted roles beyond cytotoxicity
Guo, C., Wang, C., Wang, X., Yu, D., & Liu, Z. (2025) · Trends in Immunology · doi:10.1016/j.it.2025.06.003 · Cited by 37
A single-cell analysis of the molecular lineage of chordate embryogenesis
Zhang, T., Xu, Y., Imai, K. S., Fei, T., Wang, G., Dong, B., Yu, T., Satou, Y., Shi, W., & Bao, Z. (2020) · Science Advances · doi:10.1126/sciadv.abc4773 · Cited by 37
Vitamin D sufficiency enhances differentiation of patient-derived prostate epithelial organoids
McCray, T., Pacheco, J. V., Loitz, C. C., Garcia, J. V., Baumann, B., Schlicht, M. J., Valyi‐Nagy, K., Abern, M. R., & Nonn, L. (2021) · iScience · doi:10.1016/j.isci.2020.101974 · Cited by 37
Cheng, X., Lai, H., Luo, W., Zhang, M., Miao, J., Song, W., Xing, S., Wang, J., & Gao, W. (2021) · Cell Death and Disease · doi:10.1038/s41419-021-03740-6 · Cited by 37
Huang, J., Zhu, Z., Ji, D., Sun, R., Yang, Y., Liu, L., Shao, Y., Chen, Y., Li, L., & Sun, B. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2021.792122 · Cited by 37
Repurposing antiparasitic antimonials to noncovalently rescue temperature-sensitive p53 mutations
Tang, Y., Song, H., Wang, Z., Xiao, S., Xiang, X., Zhan, H., Wu, L., Wu, J., Xing, Y., Tan, Y., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110622 · Cited by 37
Zhuang, H., Wang, H., & Ji, Z. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac235 · Cited by 37
From multitude to singularity: An up-to-date overview of scRNA-seq data generation and analysis
Carangelo, G., Magi, A., & Semeraro, R. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.994069 · Cited by 39
Lee, Y. H., Kim, Y., Kim, K. S., Jang, M., Song, H. Y., Jung, S.-H., Ha, D.-S., Park, J. S., Lee, J., Kim, K. M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37044-4 · Cited by 37
Decoding Aging Hallmarks at the Single-Cell Level
Ma, S., Chi, X., Cai, Y., Ji, Z., Wang, S., Ren, J., & Liu, G. (2023) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-020722-120642 · Cited by 37
Bayesian inference of RNA velocity incorporating timepoints, lineage bifurcations, and count data
Gu, Y., Song, Y., Blaauw, D. T., & Welch, J. D. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1014060 · Cited by 37
GGC repeat expansion in NOTCH2NLC induces dysfunction in ribosome biogenesis and translation
Fan, Y., Li, M., Yang, H. J., Li, S.-J., Hao, X., Li, J.-D., Wang, Y.-C., Tang, M., Zhang, C., Shi, J., et al. (2023) · Brain · doi:10.1093/brain/awad058 · Cited by 36
Dynamic enhancer landscapes in human craniofacial development
Rajderkar, S., Paraiso, K. D., Amaral, M. L., Kosicki, M., Cook, L., Darbellay, F., Spurrell, C. H., Osterwalder, M., Zhu, Y., Wu, H., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-46396-4 · Cited by 36
Maizels, R. J., Snell, D. M., & Briscoe, J. (2024) · Cell Systems · doi:10.1016/j.cels.2024.04.004 · Cited by 36
Insights into left-right asymmetric development of chicken ovary at the single-cell level
Wang, T., Leng, D., Cai, Z., Chen, B., Li, J., Kui, H., Li, D., & Li, Z. (2024) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2024.08.002 · Cited by 36
Inferring cell trajectories of spatial transcriptomics via optimal transport analysis
Shen, X., Zuo, L., Ye, Z., Yuan, Z., Huang, K., Li, Z., Yu, Q., Zou, X., Wei, X., Xu, P., et al. (2025) · Cell Systems · doi:10.1016/j.cels.2025.101194 · Cited by 36
Wang, W., Zhang, X., Zhang, Y., Zhang, Z., Yang, C., Cao, W., Liang, Y., Zhou, Q., Hu, Q., Zhang, Y., et al. (2025) · Advanced Science · doi:10.1002/advs.202416846 · Cited by 36
Toker, I. A., Ripoll-Sánchez, L., Geiger, L. T., Sussfeld, A., Saini, K. S., Beets, I., Vértes, P. E., Schafer, W. R., Ben‐David, E., & Hobert, O. (2025) · Current Biology · doi:10.1016/j.cub.2025.05.036 · Cited by 36
A tumor-on-a-chip for in vitro study of CAR-T cell immunotherapy in solid tumors
Liu, H., Noguera-Ortega, E., Dong, X., Lee, W. D., Chang, J., Aday, S., Li, Y., Shin, Y., Shi, X., Liousia, M., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-025-02845-z · Cited by 41
Zheng, B., Ko, K.-P., Fang, X., Wang, X., Zhang, J., Jun, S., Kim, B.-J., Luo, W., Kim, M. J., Jung, Y., et al. (2021) · iScience · doi:10.1016/j.isci.2021.103440 · Cited by 36
Retinal ganglion cell-specific genetic regulation in primary open-angle glaucoma
Daniszewski, M., Senabouth, A., Liang, H. H., Han, X., Lidgerwood, G. E., Hernández, D., Sivakumaran, P., Clarke, J. E., Lim, S. Y., Lees, J. G., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100142 · Cited by 36
Haltom, A. R., Hassen, W. E., Hensel, J., Kim, J., Sugimoto, H., Li, B., McAndrews, K. M., Conner, M. R., Kirtley, M. L., Luo, X., et al. (2022) · Extracellular Vesicle · doi:10.1016/j.vesic.2022.100014 · Cited by 36
Saunders, A. B., Huang, K. W., Vondrak, C., Hughes, C., Smolyar, K., Sen, H., Philson, A. C., Nemesh, J. C., Wysoker, A., Kashin, S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34334-1 · Cited by 37
Chiou, K. L., DeCasien, A. R., Rees, K. P., Testard, C., Spurrell, C. H., Gogate, A. A., Pliner, H. A., Tremblay, S., Mercer, A., Whalen, C. J., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01197-0 · Cited by 36
Self-citationChromatin accessibility dynamics dictate renal tubular epithelial cell response to injury
Cao, X., Wang, J., Zhang, T., Liu, Z., Liu, L., Chen, Y., Li, Z., Zhao, Y., Yu, Q., Liu, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34854-w · Cited by 36
Kim, E., Dorrity, M. W., Fitzgerald, B. A., Seo, H., Sepuru, K. M., Queitsch, C., Mitsuda, N., Han, S., & Torii, K. U. (2022) · Nature Plants · doi:10.1038/s41477-022-01304-w · Cited by 36
A Guide to Trajectory Inference and RNA Velocity
Weiler, P., den Berge, K. V., Street, K., & Tiberi, S. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2756-3_14 · Cited by 37
Single cell genomics as a transformative approach for aquaculture research and innovation
Daniels, R. R., Taylor, R. S., Robledo, D., & Macqueen, D. J. (2023) · Reviews in Aquaculture · doi:10.1111/raq.12806 · Cited by 37
Fu, S., Bury, L. A. D., Eum, J., & Wynshaw-Boris, A. J. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.03.015 · Cited by 36
Lin, J.-P., Brake, A., Donadieu, M., Lee, A., Smith, G., Hu, K., Nair, G., Kawaguchi, R., Sati, P., Geschwind, D. H., et al. (2025) · Science · doi:10.1126/science.adp6325 · Cited by 35
Multiple parallel cell lineages in the developing mammalian cerebral cortex
Del-Valle-Anton, L., Amin, S., Cimino, D., Neuhaus, F., Dvoretskova, E., Fernández, V., Babal, Y. K., Garcı́a-Frigola, C., Prieto‐Colomina, A., Murcia‐Ramón, R., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn9998 · Cited by 35
Ruysseveldt, E., Steelant, B., Wils, T., Cremer, J., Bullens, D. M. A., Hellings, P. W., & Martens, K. (2024) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2024.04.021 · Cited by 35
Liu, C., Li, K., Sui, X., Zhao, T., Zhang, T., Chen, Z., Wu, H., Li, C. R., Li, H., Yang, F., et al. (2024) · Advanced Science · doi:10.1002/advs.202400185 · Cited by 35
Pekayvaz, K., Kilani, B., Joppich, M., Eivers, L., Brambs, S., Knottenberg, V., Akgöl, S., Yue, K., Li, L., Martinez-Navarro, A., et al. (2025) · Immunity · doi:10.1016/j.immuni.2025.03.020 · Cited by 36
Lobato-Moreno, S., Yildiz, U., Claringbould, A., Servaas, N. H., Vlachou, E. P., Arnold, C., Bauersachs, H. G., Campos-Fornés, V., Kim, M., Berest, I., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02700-8 · Cited by 35
Intestinal mast cell–derived leukotrienes mediate the anaphylactic response to ingested antigens
Bachtel, N. D., Cullen, J. L., Liu, M., Erickson, S. A., Kutyavin, V. I., El-Naccache, D. W., Florsheim, E. B., Lim, J., Sullivan, Z. A., Imaeda, R., et al. (2025) · Science · doi:10.1126/science.adp0246 · Cited by 35
Man, L., Guahmich, N. L., Kallinos, E., Redhead-Laconte, Z., Liu, S., Schattman, B., Redmond, D., Hancock, K., Zaninović, N., Schattman, G. L., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108027 · Cited by 35
Single-cell atlas of domestic pig cerebral cortex and hypothalamus
Zhu, J., Chen, F., Luo, L., Wu, W., Dai, J., Zhong, J., Lin, X., Chai, C., Ding, P., Liang, L., et al. (2021) · 中国科学通报：英文版 · doi:10.1016/j.scib.2021.04.002 · Cited by 35
Self-citationLong, Noncoding RNA Dysregulation in Glioblastoma
DeSouza, P., Qu, X., Chen, H., Patel, B., Maher, C. A., & Kim, A. H. (2021) · Cancers · doi:10.3390/cancers13071604 · Cited by 36
Entropy as a measure of variability and stemness in single-cell transcriptomics
Gandrillon, O., Gaillard, M., Espinasse, T., Garnier, N., Dussiau, C., Kosmider, O., & Sujobert, P. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.05.009 · Cited by 35
Recognition of Tumor-Associated Antigens and Immune Subtypes in Glioma for mRNA Vaccine Development
Ma, S., Ba, Y., Ji, H., Wang, F., Du, J., & Hu, S. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.738435 · Cited by 35
Zhang, Y., Zou, D., Zhu, T., Xu, T., Chen, M., Niu, G., Zong, W., Pan, R., Jing, W., Sang, J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab878 · Cited by 35
Lee, P.-J., Ho, C., Ho, H. H., Chen, W.-J., Lin, C.-H., Lai, Y., Juan, Y., Chu, W.-C., Lee, J.-H., Su, S., et al. (2021) · Theranostics · doi:10.7150/thno.62676 · Cited by 36
Single-cell transcriptomics identifies potential cells of origin of MYC rhabdoid tumors
Graf, M., Interlandi, M., Moreno, N., Holdhof, D., Göbel, C., Melcher, V., Mertins, J., Albert, T., Kastrati, D., Alfert, A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29152-4 · Cited by 35
Yin, K., Zhao, M., Lin, L., Chen, Y., Huang, S., Zhu, C., Liang, X., Lin, F., Wei, H., Zeng, H., et al. (2022) · Small Methods · doi:10.1002/smtd.202200341 · Cited by 35
Single-cell transcriptomic analysis of vascular endothelial cells in zebrafish embryos
Gurung, S., Restrepo, N. K., Chestnut, B., Klimkaitė, L., & Sumanas, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-17127-w · Cited by 35
Riegel, D., Romero-Fernández, E., Simon, M., Adenugba, A., Singer, K., Mayr, R., Weber, F., Kleemann, M., Imbusch, C. D., Kreutz, M. P., et al. (2023) · Molecular Cell · doi:10.1016/j.molcel.2022.12.029 · Cited by 35
Cheng, D., Qiu, K., Rao, Y., Mao, M., Li, L., Wang, Y., Song, Y., Chen, J., Yi, X., Shao, X., et al. (2023) · eLife · doi:10.7554/elife.82705 · Cited by 35
Pich-Bavastro, C., Yerly, L., Domizio, J. D., Tissot-Renaud, S., Gilliet, M. F., & Kuonen, F. (2023) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-23-0219 · Cited by 35
Choi, H., Lee, E. J., Shin, J. S., Kim, H., Bae, S., Choi, Y., & Lee, D. S. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-023-01123-9 · Cited by 36
Mapping Transcriptomic Vector Fields of Single CellsPreprint
Qiu, X., Zhang, Y., Hosseinzadeh, S., Yang, D., Pogson, A. N., Wang, L., Shurtleff, M., Yuan, R., Song, X., Ma, Y.-A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/696724 · Cited by 35
Self-citationPerrin, S., Ethel, M., Bretegnier, V., Goachet, C., Wotawa, C.-A., Luka, M., Coulpier, F., Masson, C., Ménager, M. M., & Colnot, C. (2024) · eLife · doi:10.7554/elife.92519 · Cited by 35
Bayin, N. S., Mizrak, D., Stephen, D. N., Lao, Z., Sims, P. A., & Joyner, A. L. (2021) · Science Advances · doi:10.1126/sciadv.abj1598 · Cited by 34
TALE transcription factors: Cofactors no more
Bobola, N., & Sagerström, C. G. (2022) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2022.11.015 · Cited by 34
Single-cell chromatin accessibility and transcriptome atlas of mouse embryos
Jiang, S., Huang, Z., Li, Y., Yu, C., Yu, H., Ke, Y., Jiang, L., & Liu, J. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112210 · Cited by 34
Metadata
- Authors
- Cao, J., Spielmann, M., Qiu, X., Huang, X., Ibrahim, D. M., Hill, A. J., Zhang, F., Mundlos, S., Christiansen, L., Steemers, F. J., Trapnell, C., & Shendure, J.
- Affiliations
- University of Washington (US)
- Max Planck Institute for Molecular Genetics (DE)
- Illumina (United States) (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Trapnell, Cole
- Shendure, Jay
- ORCID
- Venue
- Nature
- Published
- 2019-02-20
- Volume
- 566
- Issue
- 7745
- Pages
- 496-502
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6434952
- OpenAlex
- W2916020270
- Semantic Scholar
- cc5f35ade6b0ecee863956c541fb239c1db1d593
- Cited by
- 4,490
- References
- 64
- Citations by year
- 2026: 797 · 2025: 901 · 2024: 809 · 2023: 645 · 2022: 568 · 2021: 421 · 2020: 267 · 2019: 76
- FWCI
- 111.88
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Heart, Lung, and Blood Institute (R01HL118342, U54HL145611)
- National Human Genome Research Institute (DP1HG007811, R01HG006283)
- National Institute of Diabetes and Digestive and Kidney Diseases (U54DK107979)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (DP2HD088158)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- mouse embryo, single-cell transcriptomics, cell atlas, developmental trajectories, cell types, marker genes, apical ectodermal ridge, limb mesenchyme, skeletal muscle development, gene expression dynamics, three germ layers
- MeSH terms
- Animals, Ectoderm, Embryo, Mammalian, Female, Genetic Markers, Male, Mesoderm, Organ Specificity, Time Factors, Sequence Analysis, RNA, Muscle, Skeletal, Gene Expression Regulation, Developmental, Muscle Development, Organogenesis, Mice, Single-Cell Analysis, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
