Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas 9606(Dataset ID: STDS0000073)

0
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1,399
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2,785
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Spots: 2,997
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Genes: 19,738
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PMID: 31932730
Summary
Visualization
Data
Analysis results
Related
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Catalog
Dataset information
Contributors
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How to cite
Dataset information
Summary:
Single-cell RNA sequencing (scRNA-seq) enables the systematic identification of cell populations in a tissue, but characterizing their spatial organization remains challenging. We combine a microarray-based spatial transcriptomics method that reveals spatial patterns of gene expression using an array of spots, each capturing the transcriptomes of multiple adjacent cells, with scRNA-Seq generated from the same sample. To annotate the precise cellular composition of distinct tissue regions, we introduce a method for multimodal intersection analysis. Applying multimodal intersection analysis to primary pancreatic tumors, we find that subpopulations of ductal cells, macrophages, dendritic cells and cancer cells have spatially restricted enrichments, as well as distinct coenrichments with other cell types. Furthermore, we identify colocalization of inflammatory fibroblasts and cancer cells expressing a stress-response gene module. Our approach for mapping the architecture of scRNA-seq-defined subpopulations can be applied to reveal the interactions inherent to complex tissues.
Overall design:
Single-cell RNA-sequencing and spatial transcriptomics of primary pancreatic cancer tissue from six patients. 2018-03-12
Technology:
Spatial Transcriptomics
Platform:
Illumina NextSeq 500
Species:
Homo sapiens(hg38)
Tissues:
Pancreas
Organ parts:
Pancreatic adenocarcinoma
Submission date: 2018-03-02Update date: 2020-11-05
Sample number: 9
DOI: To be continue
Contributors
Reuben Moncada
Contact: itai.yanai@nyumc.org
Accessions
GEO Series Accessions: GSE111672
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] Reuben Moncada. Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas 9606[DS/OL]. STOmicsDB, 2018[2018-03-02]. https://db.cngb.org/stomics/datasets/STDS0000073/. 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: Moncada, Reuben et al. “Integrating microarray-based spatial transcriptomics and single-cell RNA-seq reveals tissue architecture in pancreatic ductal adenocarcinomas.” Nature biotechnology vol. 38,3 (2020): 333-342. doi:10.1038/s41587-019-0392-8