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spatial transcriptome datasets  (10X Genomics)

 
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    Structured Review

    10X Genomics spatial transcriptome datasets
    (A) Expression of CNIH4 gene in each microdomain in BRCA spatial <t>transcriptome</t> sections; (B–E) The cell type with the largest proportion in each microdomain at BRCA idle resolution and the spatial transcriptome localization of the CNIH4 gene. Each dot is a spot for spatial transcriptome sequencing, and different colors represent different cell types. The darker the color (red) in the same spot, the higher the expression of the CNIH4 gene in the spot; (F–I) Spearman correlation of CNIH4 gene expression with each cell type in microdomains at idle resolution. The red line indicates a positive correlation, the green line denotes a negative correlation, the gray line signifies no statistical significance, and the thickness of the line reflects the absolute value of the correlation coefficient.
    Spatial Transcriptome Datasets, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spatial+transcriptomic+(st)+dataset/dataset+spatial+transcriptome/pmc11882561-44-0-7
    Average 86 stars, based on 1 article reviews
    spatial transcriptome datasets - by Bioz Stars, 2026-10
    86/100 stars

    Images

    1) Product Images from "Deciphering the role of CNIH4 in pan-cancer landscapes and its significance in breast cancer progression"

    Article Title: Deciphering the role of CNIH4 in pan-cancer landscapes and its significance in breast cancer progression

    Journal: Frontiers in Genetics

    doi: 10.3389/fgene.2025.1536620

    (A) Expression of CNIH4 gene in each microdomain in BRCA spatial transcriptome sections; (B–E) The cell type with the largest proportion in each microdomain at BRCA idle resolution and the spatial transcriptome localization of the CNIH4 gene. Each dot is a spot for spatial transcriptome sequencing, and different colors represent different cell types. The darker the color (red) in the same spot, the higher the expression of the CNIH4 gene in the spot; (F–I) Spearman correlation of CNIH4 gene expression with each cell type in microdomains at idle resolution. The red line indicates a positive correlation, the green line denotes a negative correlation, the gray line signifies no statistical significance, and the thickness of the line reflects the absolute value of the correlation coefficient.
    Figure Legend Snippet: (A) Expression of CNIH4 gene in each microdomain in BRCA spatial transcriptome sections; (B–E) The cell type with the largest proportion in each microdomain at BRCA idle resolution and the spatial transcriptome localization of the CNIH4 gene. Each dot is a spot for spatial transcriptome sequencing, and different colors represent different cell types. The darker the color (red) in the same spot, the higher the expression of the CNIH4 gene in the spot; (F–I) Spearman correlation of CNIH4 gene expression with each cell type in microdomains at idle resolution. The red line indicates a positive correlation, the green line denotes a negative correlation, the gray line signifies no statistical significance, and the thickness of the line reflects the absolute value of the correlation coefficient.

    Techniques Used: Expressing, Sequencing, Gene Expression

    Related Articles

    Single Cell:

    Article Title: Comprehensive multi-omics analysis of the prognostic value and immune signature of NCF2 in pan-cancer and its relationship with acute myeloid leukemia.
    Article Snippet: Background: The neutrophil cytoplasmic factor 2 (NCF2) gene encodes the p67phox protein, which has been implicated in the pathogenesis of several diseases.. However, its specific role in tumorigenesis remains ambiguous.. This study seeks to clarify the prognostic implications, immune profile, and therapeutic responses associated with NCF2 across different cancer types.

    other:

    Article Title: Deciphering the role of CNIH4 in pan-cancer landscapes and its significance in breast cancer progression
    Article Snippet: Spatial transcriptome datasets were obtained from the 10x Genomics server ( https://www.10xgenomics.com/ ) and previous studies ( ; ). provide details of the spatial transcriptome dataset and detailed abbreviations for the 33 tumors.

    Clinical Proteomics:

    Article Title: Spatial transcriptomics study of Castleman disease.
    Article Snippet: .. Therefore, we utilized spatial transcriptome technology on the 10X Genomics platform to study one normal lymph node and three lesion lymph nodes which were from CD patients with hyaline vascular, plasma cell, and mixed types, respectively. ..

    Formalin-fixed Paraffin-Embedded:

    Article Title: Identification and targeting of cancer-associated fibroblast signature genes for prognosis and therapy in Cutaneous melanoma.
    Article Snippet: Background: Cancer-associated fibroblasts (CAFs) play pivotal roles in tumor invasion and metastasis.. However, studies on CAF biomarkers in Cutaneous Melanoma (CM) are still scarce.. This study aimed to explore the potential CAF biomarkers in CM, propose the potential therapeutic targets, and provide new insights for targeted therapy of CAFs in CM.

    Gene Expression:

    Article Title: SPathDB: a comprehensive database of spatial pathway activity atlas
    Article Snippet: .. Spatial transcriptome datasets of human and mouse were collected from the Gene Expression Omnibus (GEO) database , 10× Genomics ( https://www.10xgenomics.com/ ), Mendeley Data ( https://data.mendeley.com/ ) and CROST ( https://ngdc.cncb.ac.cn/crost/ ). ..



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    Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial <t>transcriptome</t> displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.
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    Image Search Results


    Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial transcriptome displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.

    Journal: Discover Oncology

    Article Title: Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

    doi: 10.1007/s12672-024-01162-2

    Figure Lengend Snippet: Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial transcriptome displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.

    Article Snippet: The spatial transcriptome sequencing (ST-seq) dataset was obtained from Mendeley Data platform ( https://data.mendeley.com/datasets/g67bkbnhhg/1 ) and input to python environment.

    Techniques: Expressing

    Dissection of immunosuppressive cells of cuproptosis-related tumor microenvironment. A UMAP showing the 16 subtypes of 99,210 Immune cells; B violin plot of the relative expression levels of the canocial markers in each subtype; C heatmap showing the enrichment of immune checkpoint and suppressive genes; D spatial transcriptome displayed the distribution of Treg, CD8_Exhausted and TAM signature scores; E heatmap showing the four gene expression patterns deduced by TDEseq analysis; F violin plots showing the relative expression levels of CRG scores in the immunosuppressive cells across different stages; G Chord diagram showing the number of interactions among the four subtypes; H Bubble plot showing the ligand-receptor pairs in the main subtype; I Heatmap showing the relative expression levels of key genes of the four subtypes among the different stages. The paired ligand-receptor shown in H were connected by lines.

    Journal: Discover Oncology

    Article Title: Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

    doi: 10.1007/s12672-024-01162-2

    Figure Lengend Snippet: Dissection of immunosuppressive cells of cuproptosis-related tumor microenvironment. A UMAP showing the 16 subtypes of 99,210 Immune cells; B violin plot of the relative expression levels of the canocial markers in each subtype; C heatmap showing the enrichment of immune checkpoint and suppressive genes; D spatial transcriptome displayed the distribution of Treg, CD8_Exhausted and TAM signature scores; E heatmap showing the four gene expression patterns deduced by TDEseq analysis; F violin plots showing the relative expression levels of CRG scores in the immunosuppressive cells across different stages; G Chord diagram showing the number of interactions among the four subtypes; H Bubble plot showing the ligand-receptor pairs in the main subtype; I Heatmap showing the relative expression levels of key genes of the four subtypes among the different stages. The paired ligand-receptor shown in H were connected by lines.

    Article Snippet: The spatial transcriptome sequencing (ST-seq) dataset was obtained from Mendeley Data platform ( https://data.mendeley.com/datasets/g67bkbnhhg/1 ) and input to python environment.

    Techniques: Dissection, Expressing, Gene Expression