Spatial charting of single-cell transcriptomes in tissues(Dataset ID: STDS0000144)
chevron_leftchevron_right
Catalog
Dataset information
Contributors
Accessions
How to cite
Dataset information
Summary:
We performed single-cell RNA sequencing and spatial transcriptomics experiments on two ductal carcinoma in situ tissues and applied CellTrek to identify tumor subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data show that CellTrek can accurately map single cells in diverse tissue types to resolve their spatial organization.Overall design:
We developed a computational method called CellTrek that combines single-cell RNA sequencing and spatial transcriptomics datasets to achieve single-cell spatial mapping through coembedding and metric learning approaches.Technology:
10x Visium,scRNA
Platform:
Illumina NovaSeq 6000 (Homo sapiens)
Species:
Homo sapiens(hg38)
Tissues:
Breast
Disease:
Ductal carcinoma in situSubmission date: 2021-07-31Update date: 2022-08-16
Sample number: 4Section number: 4
DOI: To be continue
Contributors
Wei, Runmin,He, Siyuan,Navin, Nicholas
Accessions
GEO Series Accessions:
GSE181254
How to cite
- Cite database of STOmicsDB:[1] Xu, Zhicheng et al. "STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization." Nucleic acids research vol. 52,D1 (2024): D1053-D1061. doi: 10.1093/nar/gkad933'
- Cite visualization dataset:[2] Wei, Runmin,He, Siyuan,Navin, Nicholas. Spatial charting of single-cell transcriptomes in tissues[DS/OL]. STOmicsDB, 2021[2021-07-31]. https://db.cngb.org/stomics/datasets/STDS0000144/. doi: xxxxxx#Format: {contributors}. {title}[DS/OL]. STOmicsDB, {the year of submission data}[{submission data}]. {dataset link}. doi: {doi ID}
- Cite original data article:Citation: Wei, Runmin et al. “Spatial charting of single-cell transcriptomes in tissues.” Nature biotechnology vol. 40,8 (2022): 1190-1199. doi:10.1038/s41587-022-01233-1