Description

This track collection shows data from Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. The dataset covers ~200,000 single nuclei from a total of 16 human donors across 25 samples, using 4 different sample preparation protocols followed by droplet based single-cell RNA-seq. The samples were obtained from frozen tissue as part of the Genotype-Tissue Expression (GTEx) project. Samples were taken from the esophagus, skeletal muscle, heart, lung, prostate, breast, and skin. The dataset includes 43 broad cell classes, some specific to certain tissues and some shared across all tissue types.

This track collection contains three bar chart tracks of RNA expression. The first track, Cross Tissue Nuclei, allows cells to be grouped together and faceted on up to 4 categories: tissue, cell class, cell subclass, and cell type. The second track, Cross Tissue Details, allows cells to be grouped together and faceted on up to 7 categories: tissue, cell class, cell subclass, cell type, granular cell type, sex, and donor. The third track, GTEx Immune Atlas, allows cells to be grouped together and faceted on up to 5 categories: tissue, cell type, cell class, sex, and donor.

Please see the GTEx portal for further interactive displays and additional data.

Display Conventions and Configuration

Tissue-cell type combinations in the Full and Combined tracks are colored by which cell type they belong to in the below table:

Tissue-cell type combinations in the Immune Atlas track are shaded according to the below table:

Methods

Using the previously collected tissue samples from the Genotype-Tissue Expression project, nuclei were isolated using four different protocols and sequenced using droplet based single cell RNA-seq. CellBender v2.1 and other standard quality control techniques were applied, resulting in 209,126 nuclei profiles across eight tissues, with a mean of 918 genes and 1519 transcripts per profile.

Data from all samples was integrated with a conditional variation autoencoder in order to correct for multiple sources of variation like sex, and protocol while preserving tissue and cell type specific effects.

For detailed methods, please refer to Eraslan et al, or the GTEx portal website.

UCSC Methods

The gene expression files were downloaded from the GTEx portal. The UCSC command line utilities matrixClusterColumns, matrixToBarChartBed, and bedToBigBed were used to transform these into a bar chart format bigBed file that can be visualized. 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.

Credits

Thanks to the GTEx Consortium for creating and analyzing these data.

References

Eraslan G, Drokhlyansky E, Anand S, Fiskin E, Subramanian A, Slyper M, Wang J, Van Wittenberghe N, Rouhana JM, Waldman J et al. Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. Science. 2022 May 13;376(6594):eabl4290. PMID: 35549429; PMC: PMC9383269