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human hippocampus dataset  (Spatial Transcriptomics Inc)

 
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    Structured Review

    Spatial Transcriptomics Inc human hippocampus dataset
    a Bright-field image and manually annotated segmentation of <t>hippocampus</t> layers and white matter (WM) in the human hippocampus. b Spatial clustering of hippocampal regions using MultiGATE, SpatialGlue, and Seurat WNN. Clustering performance is assessed using the Adjusted Rand Index (ARI), with higher values indicating greater clustering accuracy. c Box plots representing attention scores for peak–gene pairs across different genomic distances, grouped based on whether they are supported by expression quantitative trait loci (eQTL) evidence. The box plots indicate the medians (centerlines), means (triangles), first and third quartiles (bounds of boxes), and 1.5 × interquartile range (whiskers). Sample sizes per bin (False/True): 0–25 kb (621/222), 25–50 kb (479/88), 50–75 kb (461/78), 75–100 kb (469/44), 100–125 kb (446/30), 125–150 kb (405/29). d Receiver operating characteristic (ROC) curves comparing the performance of MultiGATE and other methods in predicting eQTL-associated regulatory interactions. e Visualization of MultiGATE-predicted cis-regulatory interactions for the target genes CA12 and PRKD3 along with eQTL evidence. Source data are provided as a Source Data file.
    Human Hippocampus Dataset, supplied by Spatial Transcriptomics Inc, 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+transcriptomics+data/pmc12552752-274-3-12?v=Spatial+Transcriptomics+Inc
    Average 86 stars, based on 1 article reviews
    human hippocampus dataset - by Bioz Stars, 2026-07
    86/100 stars

    Images

    1) Product Images from "MultiGATE: integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning"

    Article Title: MultiGATE: integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning

    Journal: Nature Communications

    doi: 10.1038/s41467-025-63418-x

    a Bright-field image and manually annotated segmentation of hippocampus layers and white matter (WM) in the human hippocampus. b Spatial clustering of hippocampal regions using MultiGATE, SpatialGlue, and Seurat WNN. Clustering performance is assessed using the Adjusted Rand Index (ARI), with higher values indicating greater clustering accuracy. c Box plots representing attention scores for peak–gene pairs across different genomic distances, grouped based on whether they are supported by expression quantitative trait loci (eQTL) evidence. The box plots indicate the medians (centerlines), means (triangles), first and third quartiles (bounds of boxes), and 1.5 × interquartile range (whiskers). Sample sizes per bin (False/True): 0–25 kb (621/222), 25–50 kb (479/88), 50–75 kb (461/78), 75–100 kb (469/44), 100–125 kb (446/30), 125–150 kb (405/29). d Receiver operating characteristic (ROC) curves comparing the performance of MultiGATE and other methods in predicting eQTL-associated regulatory interactions. e Visualization of MultiGATE-predicted cis-regulatory interactions for the target genes CA12 and PRKD3 along with eQTL evidence. Source data are provided as a Source Data file.
    Figure Legend Snippet: a Bright-field image and manually annotated segmentation of hippocampus layers and white matter (WM) in the human hippocampus. b Spatial clustering of hippocampal regions using MultiGATE, SpatialGlue, and Seurat WNN. Clustering performance is assessed using the Adjusted Rand Index (ARI), with higher values indicating greater clustering accuracy. c Box plots representing attention scores for peak–gene pairs across different genomic distances, grouped based on whether they are supported by expression quantitative trait loci (eQTL) evidence. The box plots indicate the medians (centerlines), means (triangles), first and third quartiles (bounds of boxes), and 1.5 × interquartile range (whiskers). Sample sizes per bin (False/True): 0–25 kb (621/222), 25–50 kb (479/88), 50–75 kb (461/78), 75–100 kb (469/44), 100–125 kb (446/30), 125–150 kb (405/29). d Receiver operating characteristic (ROC) curves comparing the performance of MultiGATE and other methods in predicting eQTL-associated regulatory interactions. e Visualization of MultiGATE-predicted cis-regulatory interactions for the target genes CA12 and PRKD3 along with eQTL evidence. Source data are provided as a Source Data file.

    Techniques Used: Expressing



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    Single-nucleus transcriptome and spatial <t>transcriptomics</t> landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.
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    Image Search Results


    Single-nucleus transcriptome and spatial transcriptomics landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

    Journal: Frontiers in Immunology

    Article Title: Single-nucleus and spatial transcriptomics reveal intestinal cellular heterogeneity, differentiation, and cell communication mechanisms in SAP-induced intestinal injury

    doi: 10.3389/fimmu.2026.1719902

    Figure Lengend Snippet: Single-nucleus transcriptome and spatial transcriptomics landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

    Article Snippet: The spatial transcriptomics data were obtained according to the protocol of STOmics Gene Expression Set-S1 on the website ( https://www.stomics.tech/ ), which is an improved version of initial procedures.

    Techniques: Spatial Transcriptomics, Staining, Marker