Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris

Probably not a substantial claim: may not pass S3 (load-bearing).

Cluster annotations were given in a cell ontology controlled vocabulary to support comparisons between experiments.

“For each cluster, we provide annotations in the controlled vocabulary of a cell ontology19 to facilitate inter-experiment comparisons.”

• cites [19] Bakken, T. et al. Cell type discovery and representation in the era of high-content single cell phenotyping. BMC Bioinformatics 18 (Suppl 17), 559 (2017). sourceSupported

May combine two claims.

The average sequencing depth was 814,488 reads per FACS cell and 7,709 UMIs per microfluidic droplet cell.

“Single-cell transcriptomes were sequenced to an average depth of 814,488 reads per cell (FACS) and 7,709 unique molecular identifiers (UMIs) per cell (microfluidic droplet).”

May combine two claims.

Bladder, liver, lung, mammary gland, trachea, tongue, and spleen showed nearly twice as many genes detected per cell with FACS as with droplet, while heart and marrow showed comparable numbers.

“The bladder, liver, lung, mammary gland, trachea, tongue, and spleen show nearly twice as many genes detected per cell with FACS compared to microfluidic droplet, whereas heart and marrow show comparable numbers (Extended Data Fig. 5a).”

May combine two claims.

Han et al.'s data contains four times as many cells and includes sample types not present in the authors' data, such as neonatal and fetal organs, cell lines, and young adult ovary, peripheral blood, placenta, prostate, small intestine, stomach, testis, and uterus.

“Their data contains four times as many cells and included several sample types not present in our data, such as neonatal and fetal organs, cell lines, and young adult ovary, peripheral blood, placenta, prostate, small intestine, stomach, testis, and uterus.”

• cites Han et al.20 Han, X. et al. Mapping the mouse cell atlas by microwell-seq. Cell 172, 1091–1107.e17 (2018). sourceNot checked — no full text of the source

May combine two claims.

The transcription factor sets that distinguish each individual cell type from all other cells vary substantially in size, from 2 to 813 factors, and are not necessarily unique to each cell type.

“We then determined the TF sets distinguishing each individual cell type from all other cells. These sets vary substantially in size (from 2 to 813 TFs) and are not necessarily unique to each cell type (Fig. 5g–i; Supplementary Table 4).”

May combine two claims.

The authors' FACS data contains four times as many genes per cell as Han et al., and they analyzed several organs not present in Han et al., such as aorta, four brain regions, diaphragm, four fat types, four adult heart chambers, adult skin, tongue, and trachea.

“However, our FACS data contains four times as many genes per cell, and we analyzed several organs not present in the Han et al. data set, such as aorta, four brain regions, diaphragm, four fat types, four adult heart chambers, adult skin, tongue, and trachea.”

• cites Han et al.20 Han, X. et al. Mapping the mouse cell atlas by microwell-seq. Cell 172, 1091–1107.e17 (2018). sourceNot checked — no full text of the source

May combine two claims.

Cluster 2 contains mostly non-thymic T cells expressing the high affinity IL2 receptor (Il2ra, Il2rb), suggesting they are activated.

“while Cluster 2 contains mostly non-thymic T cells expressing the high affinity IL2 receptor (Il2ra, Il2rb), suggesting they are activated.”

May combine two claims.

Cluster 0 contains thymic cells undergoing VDJ recombination marked by RAG (Rag1, Rag2) and TdT (Dntt) expression, including uncommitted double positive T cells (Cd4+, Cd8a+).

“Cluster 0 comprises thymic cells undergoing VDJ recombination characterized by RAG (Rag1, Rag2) and TdT (Dntt) expression, and includes uncommitted double positive T-cells (Cd4+, Cd8a+).”

May combine two claims.

Cluster 2 contained B cells from fat, limb muscle, lung, spleen, marrow, and liver, as well as cells annotated as leukocytes and lymphocytes from thymus, heart, and limb muscle.

“Cluster 2 contains B cells from fat, limb muscle, lung, spleen, marrow, and liver, but also cells annotated as leukocytes and lymphocytes from the thymus, heart, and limb muscle.”

May combine two claims.

In global clustering, cells from different organs often mixed, and 25 of 54 clusters contained at least five cells from distinct organs.

“As expected, cells from different organs often mixed, with 25 of 54 clusters containing (at least five) cells from distinct organs (Fig. 3).”

May combine two claims.

When the analysis used cell surface markers, RNA splicing factors, or both combined, entanglement was 0.22, 0.25, and 0.34, respectively, suggesting that none of these molecular classes define cell type as well as transcription factors do.

“In contrast, when we repeated the analysis using cell surface markers, RNA splicing factors, or the two groups combined (equivalent to a random set of genes), the entanglement was 0.22, 0.25 and 0.34, respectively, suggesting that none of these molecular classes define cell type to the extent that transcription factors do.”

May combine two claims.

Cluster 1 represents mature T cells, but primarily splenic ones.

“Finally, Cluster 1 also represents mature T cells, but primarily splenic.”

May combine two claims.

Mis-annotation seems to occur only for populations smaller than about 30 cells, which make up under 4% of the overall dataset, and this represents a lower limit of sensitivity in the current release.

“This seems only to occur for populations smaller than ~30 cells, which comprise under 4% of the overall dataset, and represents a lower limit of sensitivity in the current release of data interpretation.”

May combine two claims.

The two methods differ by organ in the number of cells analyzed, reads per cell, and genes per cell.

“Comparing methods shows organ-specific differences in the number of cells analyzed (Fig. 1b, c), reads per cell (Extended Data Fig. 3a, c) and genes per cell (Extended Data Fig. 3b, d).”

May combine two claims.

Cluster 4 contains predominantly proliferating thymic T cells that may be pre-T cells expanding after VDJ recombination.

“Cluster 4 contains predominantly proliferating thymic T cells which may represent pre-T cells expanding following VDJ recombination.”

May combine two claims.

With both methods, epithelial cells and leukocytes were the most abundant cell types analyzed, but FACS captured a greater diversity of cell types.

“Furthermore, with both methods the most abundant cell types analyzed are epithelial cells and leukocytes, although FACS captured a larger diversity of cell types (Extended Data Fig. 4).”

May combine two claims.

For cell types captured by both methods in spleen and kidney, the proportions of each cell type were equivalent, with Pearson correlation coefficients of 0.99 for both organs.

“For those cell types captured by both methods, the proportion of each cell type is equivalent (Pearson correlation coefficient: spleen = 0.99, kidney = 0.99).”

May combine two claims.

Median detected genes in bladder were about 4,900 for FACS, 2,900 for droplet, and 900 for microwell-seq; in kidney they were about 1,400, 1,900, and 500, respectively.

“For example, the median number of genes detected in bladder is ~4,900 (FACS), 2,900 (droplet), and 900 (microwell-seq), while in kidney it is ~1,400 (FACS), 1,900 (droplet), and 500 (microwell-seq).”

• cites Han et al.20 Han, X. et al. Mapping the mouse cell atlas by microwell-seq. Cell 172, 1091–1107.e17 (2018). sourceNot checked — no full text of the source

May combine two claims.

Clusters 3 and 48 each contained endothelial cells from five or more organs, and clusters 1 and 24 contained mesenchymal and stromal cells from four or more organs.

“For example, clusters 3 and 48 each contain endothelial cells from five or more organs, and clusters 1 and 24 contain mesenchymal and stromal cells from four or more organs.”

May combine two claims.

The authors clearly observed dissociation-related satellite cell markers in several organs including limb muscle, but many organs showed little evidence of cellular activation.

“We clearly observed these markers in several organs including limb muscle (Extended Data Fig. 11), but many showed little evidence of cellular activation.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The median library saturation for all microfluidic droplet libraries was approximately 0.9.

“Dotted horizontal line demarcates the median saturation (~ 0.9).”

May combine two claims.

Microfluidic droplets capture fewer molecules per cell but a greater number of cells compared with FACS.

“FACS detects more molecules per cell, but fewer cells. Microfluidic droplets detect fewer molecules per cell, but more cells.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The number of cells analyzed was 44,949 for FACS, 55,656 for microfluidic droplet, and 28,372 for microwell-Seq.

“Fraction of all detected genes (defined as > 0 reads or UMIs) for each cell, across all organs, detected at increasing read or UMI thresholds for FACS (left; n= 44,949 individual cells), microfluidic droplet (middle; n= 55,656 individual cells), and microwell-Seq (right; n= 28,372 individual cells).”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The number of genes detected was measured in 21,105 FACS cells, 55,032 microfluidic droplet cells, and 25,891 microwell-Seq cells.

“The number of genes detected (threshold of > 0 reads or UMIs per cell) by FACS (red; n= 21,105 individual cells), microfluidic droplets (green; n = 55,032 individual cells), and microwell-Seq (blue; n= 25,891 individual cells) (Han et al.).”

• cites Han et al.Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

May combine two claims.

FACS captures a higher number of molecules per cell but a lower number of cells compared with microfluidic droplets.

“FACS detects more molecules per cell, but fewer cells. Microfluidic droplets detect fewer molecules per cell, but more cells.”

May combine two claims.

Despite biases between methods, both methods accurately recapitulate average cell type gene expression profiles.

“Such gene expression profiles largely correlate (Pearson correlation coefficient: 0.74 – 0.90), suggesting that while biases between methods exist, both accurately recapitulate average cell type gene expression profiles.”

Probably not a substantial claim: may not pass S3 (load-bearing).

All organs were annotated using a standard method.

“All organs used a standard annotation method; an example using liver is contained in the Organ Annotation Vignette.”

May combine two claims.

The release permits exact replication of all results, supports further analyses not done here, and offers a comparative framework for future studies with murine disease models.

“This release allows for the exact replication of all results, facilitates in-depth analyses not completed here, and provides a comparative framework for future studies using the large variety of murine disease models.”

May combine two claims.

For nearly all reprogramming protocols, the transcription factors used also specified the targeted cell type in the data, suggesting that the data can inform novel reprogramming schemes.

“In fact, for nearly all reprogramming protocols the TFs used also specified the targeted cell type in our data (Supplementary Table 5), suggesting that our data can inform novel reprogramming schemes.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Han et al. published a complementary single-cell RNA-seq study across mouse organs.

“Recently, Han et al.20 published a complementary scRNA-seq study across mouse organs.”

• cites Han et al.20 Han, X. et al. Mapping the mouse cell atlas by microwell-seq. Cell 172, 1091–1107.e17 (2018). sourceNot checked — no full text of the source

May combine two claims.

Many cell types in the dataset had not previously been isolated in pure populations, and the data add new information about their characteristic gene expression.

“Many of these cell types have not previously been obtained in pure populations, and our data provide a wealth of new information on their characteristic gene expression profiles.”

May combine two claims.

The cell types missed by FACS are partly explained by cellular abundance and sampling depth, and possibly by capture and lysis biases between methods.

“This is partially explained by cellular abundance and sampling depth (12,333 microfluidic droplet cells vs. 2,216 FACS cells, Supplementary Table 1), and possibly from cell capture and lysis biases between methods.”

May combine two claims.

Dissociation-related satellite cell markers are not universal, and organs likely have unique dissociation-related expression profiles.

“Therefore, the dissociation- related satellite cell markers are not universal, and organs likely display unique dissociation-related expression profiles.”

May combine two claims.

The data are not a complete representation of all mouse organs and cell types, but they are a first draft attempt at an organism-wide representation of cellular diversity.

“While these data are by no means a complete representation of all mouse organs and cell types, they provide a first draft attempt to create an organism-wide representation of cellular diversity.”

May combine two claims.

The design made it possible to compare cell type composition across organs and to compare shared cell types between organs.

“This enabled the direct comparison of cell type composition between organs, and the comparison of shared cell types across organs.”

May combine two claims.

Most cells of similar types cluster together across organs and biological replicates, showing that batch effects are not the main source of variance in the dataset.

“The fact that most cells of similar cell types cluster together across organs and biological replicates shows that batch effects are not the main source of variance in the dataset.”

May combine two claims.

Cell types were annotated using standard cell ontology terms, enabling cross-organ and cross-experiment analyses.

“3) We annotated cell types using standard cell ontology terms, thereby enabling cross-organ and cross-experiment analyses”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

MHC class II was previously thought to be restricted to professional antigen presenting cells in mice, although it is known in human T cells.

“While this is known in human T cells, MHC class II was previously thought restricted to professional antigen presenting cells in mice22.”

• cites [22] Holling, T. M., Schooten, E. & van Den Elsen, P. J. Function and regulation of MHC class II molecules in T-lymphocytes: of mice and men. Hum. Immunol. 65, 282–290 (2004). sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

All data, analysis, and code are freely available.

“1) All data, analysis, and code is freely available”

May combine two claims.

Mis-annotation is a predictable artifact of annotating whole clusters rather than individual cells, so a rare cell type grouped with a more populous type will be mis-annotated.

“This is a predictable artifact of the annotation scheme: since entire clusters, rather than individual cells, were annotated in each organ, a sufficiently rare cell type that was algorithmically grouped with a more populous cell type will be mis-annotated.”

May combine two claims.

All data, protocols, analysis scripts, and an interactive browser are publicly available.

“All data, protocols, analysis scripts, and an interactive data browser are publicly shared (http://tabula-muris.ds.czbiohub.org/ ).”

May combine two claims.

The presence of dissociation-related gene expression changes does not prevent cell type identification or comparison of cell types across organs.

“Importantly, the presence of such gene expression changes does not prevent cell type identification or the comparison of cell types across organs.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Because the nomenclature differed, the overlap analysis was limited to cell types that could be matched with reasonable confidence.

“As the nomenclature is not identical, the analysis was performed between cell types that could be matched with a certain degree of confidence between the three methods (Supplementary Table 2).”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Littermates were not recorded or tracked, and mice were housed at the VA VMU for no longer than 2 weeks before euthanasia.

“Littermates were not recorded or tracked, and mice were housed at the VA VMU for no longer than 2 weeks before euthanasia.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Sample wells were included only when their cDNA concentration was at least one standard deviation above the mean blank concentration.

“Sample wells were then selected if their cDNA concentrations were at least one standard deviation greater than the mean concentration of the blanks.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Sorters were calibrated with FACS buffer every day before collecting cells and after every 8 sorted plates.

“Sorters were calibrated using FACS buffer every day before collecting any cells, and also after every 8 sorted plates.”

Classified as probably not a substantial claim.

A global analysis of all FACS cells and all microfluidic droplet cells was performed to produce an unbiased clustering.

“A similar analysis was done globally for all FACS processed cells and for all microfluidic droplet processed cells to produce an unbiased clustering.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Any cell with fewer than 500 detected genes was removed.

“Cells with fewer than 500 detected genes were excluded.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Although not exhaustive, the dataset provides a rich resource of the most highly studied organs in biology.

“While it is not an exhaustive characterization of all mouse organs, it does provide a rich dataset of the most highly studied organs in biology.”

Classified as probably not a substantial claim. May combine two claims.

Tabula Muris has many uses, including discovering new putative cell types, finding novel gene expression in known cell types, and comparing cell types across organs.

“This Tabula Muris, or “Mouse Atlas”, has many uses, including the discovery of new putative cell types, the discovery of novel gene expression in known cell types, and the ability to compare cell types across organs.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

For FACS, cells with under 50,000 reads were removed; for microfluidic droplet, cells with under 1000 UMI were removed.

“Cells with fewer than 50,000 reads (FACS) or 1000 UMI (microfluidic droplet) were excluded.”

Probably not a substantial claim: may not pass S3 (load-bearing).

No sample size choice was made before the study.

“No sample size choice was performed prior to the study.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Cell IDs were sorted in lexicographic order to guarantee reproducibility.

“Cells were lexicographically sorted by cell ID to ensure reproducibility.”

Classified as probably not a substantial claim.

Cell types were assigned to clusters based on the abundance of known marker genes.

“Cell types were assigned to each cluster using the abundance of known marker genes.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Clusters that appeared to be mixtures of cell types were refined by increasing the clustering resolution or by subsetting the data and rerunning steps 3-7.

“When clusters appeared to be mixtures of cell types, they were refined either by increasing the resolution parameter for clustering or subsetting the data and rerunning steps 3–7.”

Probably not a substantial claim: may not pass S3 (load-bearing).

All animal care and procedures followed institutional guidelines approved by the VA Palo Alto Committee on Animal Research.

“All animal care and procedures were carried out in accordance with institutional guidelines approved by the VA Palo Alto Committee on Animal Research.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Sample plates were included for downstream processing only when the mean blank concentration exceeded 0 ng/μl and the standard curve R2 exceeded 0.98.

“Sample plates were selected for downstream processing if the mean concentration of blanks (ERCC-containing, non-cell wells) was greater than 0 ng/μl, and, after linear regression of the values obtained from the Quant-iT dsDNA standard curve, the R2 value was greater than 0.98.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Four 10-15 week old male and four virgin female C57BL/6JN mice were shipped from the National Institute on Aging colony at Charles River to the VA Palo Alto Veterinary Medical Unit.

“Four 10–15 week old male and four virgin female C57BL/6JN (derived from C57BL/6J in 2016) mice were shipped from the National Institute on Aging colony at Charles River to the Veterinary Medical Unit (VMU) at the VA Palo Alto (VA).”

May combine two claims.

Tabula Muris provides a framework and description of many of the most populous and important cell populations in the mouse, and is a foundation for future studies across diverse physiological disciplines.

“Tabula Muris provides a framework and description of many of the most populous and important cell populations within the mouse, and represents a foundation for future studies across a multitude of diverse physiological disciplines.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Randomization and blinding were not performed, and the authors were aware of all data and metadata variables throughout the study.

“Randomization and blinding were not performed – the authors were aware of all data and metadata related variables during the entire course of the study.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Isolating viable single cells from both pancreas and liver of the same mouse was not possible, so 2 males and 2 females were used for each.

“Isolating viable single cells from both pancreas and liver of the same mouse was not possible, therefore, 2 males and 2 females were used for each.”

Classified as probably not a substantial claim.

Full-length transcript data makes possible transcription factor, splice variant, and sequence variant analyses.

“7) Full-length transcript data makes possible transcription factor, splice variant, and sequence variant analyses.”