Lung Travaglini Lung Cells Track Settings
 
Lung cells 10x method binned by merged cell type from Travaglini et al 2020

Track collection: Lung cells from from Travaglini et al 2020

+  Description
+  All tracks in this collection (19)

Display mode:      Duplicate track

Label: Name or ID of item    Alternative name for item   

Log10(x+1) transform:    View limits maximum: UMI/cell (range 0-10000)

Categories:  
 smooth muscle (airway) cell
 alveolar Type 1 cell
 alveolar Type 2 cell
 artery/vein endothelial cell
 airway basal cell
 basophil/mast cell
 bronchial vessel cell
 capillary endothelial cell
 ciliated cell
 club cell
 dendritic cell
 fibroblast
 goblet cell
 lymphatic cell
 lymphocyte
 macrophage/monocyte
 mucous cell
 other/rare cell
 pericyte
 smooth muscle (vascular) cell
Data schema/format description and download
Assembly: Human Dec. 2013 (GRCh38/hg38)
Data last updated at UCSC: 2022-05-12 08:26:26

Description

This track displays data from A molecular cell atlas of the human lung from single-cell RNA sequencing. Using droplet-based and plate-based single-cell RNA sequencing (scRNA-seq), 58 lung cell type populations were identified: 15 epithelial, 9 endothelial, 9 stromal, and 25 immune. This dataset covers ~75,000 human cells across all lung tissue compartments and circulating blood.

This track collection contains 19 bar chart tracks of RNA expression in the human lung where cells are grouped such as by cell type (Lung Cells, Lung Cells FACS), tissue compartments (Lung Compart, Lung Compart FACS), detailed cell type (Lung Detail, Lung Detail FACS), organ donor (Lung Donor, Lung Donor FACS), halfway detailed cell type (Lung Half Det, Lung Half Det FACS), sample location (Lung Locat, Lung Locat FACS), or organ (Lung Organ, Lung Organ FACS). The default track displayed is Lung Cells.

Display Conventions

The cell types are colored by which class they belong to according to the following table.

Color Cell classification
fibroblast
immune
muscle
secretory
ciliated
epithelial
endothelial

Cells that fall into multiple classes will be colored by blending the colors associated with those classes. The colors will be purest in the Lung Cells subtrack, where the bars represent relatively pure cell types. They can give an overview of the cell composition within other categories in other subtracks as well.

Data Access

The raw bar chart data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Method

Healthy lung tissue and peripheral blood was surgically removed from 2 male patients (ages 46 and 75) and 1 female patient (age 51) undergoing lobectomy for focal lung tumors. Lung tissue was sampled from the bronchi (proximal), bronchiole (medial), and alveolar (distal) regions. Lung samples were dissociated and enriched with magnetic columns before being sorted into epithelial, endothelial/immune, and stromal cell suspensions. Lung and peripheral blood libraries were prepared using the 10x Genomics 3' v2 kit. In parallel, Smart-Seq2 (SS2) cDNA libraries were prepared using the Nextera XT library kit. Both 10x and SS2 libraries were sequenced on a NovaSeq 6000.

The cell/gene matrix and cell-level metadata was downloaded from the UCSC Cell Browser. The UCSC command line utility matrixClusterColumns, matrixToBarChart, and bedToBigBed were used to transform these into a bar chart format bigBed file that can be visualized. The coloring was done by defining colors for the broad level cell classes and then using another UCSC utility, hcaColorCells, to interpolate the colors across all cell types. The UCSC utilities can be found on our download server.

Data Access

The raw bar chart data can be explored interactively with the Table Browser or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Credit

Thanks to Kyle J. Travaglini, Ahmad N. Nabhan, and to the many authors who worked on producing and publishing this data set. The data were integrated into the UCSC Genome Browser by Jim Kent and Brittney Wick then reviewed by Gerardo Perez. The UCSC work was paid for by the Chan Zuckerberg Initiative.

References

Travaglini KJ, Nabhan AN, Penland L, Sinha R, Gillich A, Sit RV, Chang S, Conley SD, Mori Y, Seita J et al. A molecular cell atlas of the human lung from single-cell RNA sequencing. Nature. 2020 Nov;587(7835):619-625. PMID: 33208946; PMC: PMC7704697