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10x visium spatial transcriptomics sections (Spatial Transcriptomics Inc)

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Spatial Transcriptomics Inc 10x visium spatial transcriptomics sections

a H&E-stained images of <t>10X</t> <t>Visium</t> spatial <t>transcriptomics</t> sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues. The two control samples represent the upper and lower halves of the same slide (stitched together). Scale bar = 2 mm. b Spatial mapping of tissue region clusters (Alveoli, Bronchi, Vessel, Unspecified) on spatial transcriptomics spots from Control (left) and PVOD (right) lung samples. c Violin plot showing HMOX1 expression levels across tissue regions in Control and PVOD lung samples. P values were determined via two-sided Wilcoxon rank-sum test. d Violin plots depicting expression of arterial endothelial markers ( KDR, CXCL12 ) and venous related marker ( ACKR1 ) in vessel regions comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. e Violin plots showing arterial and venous endothelial gene set scores in vessel regions of Control versus PVOD samples. P values were determined via two-sided Wilcoxon rank-sum test. f Volcano plot of differentially expressed genes in vessel regions between PVOD and Control groups. P values were determined via two-sided Wilcoxon rank-sum test with Benjamini–Hochberg correction for multiple testing. Significance thresholds were set at |log2 fold change| > 0.5 and adjusted p -value < 0.05. The top 5 upregulated and top 5 downregulated genes are annotated in the plot. GO biological processes ( g ) and KEGG pathways ( h ) significantly enriched (FDR < 0.05) from upregulated genes in PVOD vessel regions. P values were calculated using the hypergeometric test with Benjamini–Hochberg correction for multiple testing. Ten relevant terms associated with pulmonary vascular disease are shown, ranked by combined score. Dot size represents the percentage of genes in the gene set, and dot color indicates –log10(FDR). i Volcano plot of transcription factor activity differences (z-score normalized AUC scores) between Control and PVOD vessel regions analyzed by the limma method. j Violin plot showing ETS1 AUC scores in Control and PVOD vessel regions. k Violin plot of ETS1 expression in venous endothelial cells from scRNA-seq data comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. l ETS1 transcription factor binding motif (metacluster_183.1) obtained from the cisTarget motif collection (v10nr_clust). m Spatial distribution of cell type proportions (EC_arterial, EC_venous, Macrophages, Muscular cells, Fibroblasts) inferred by RCTD deconvolution. Color intensity corresponds to the relative abundance of each cell type, with darker colors indicating higher proportions. n Heatmaps showing Pearson correlation between RCTD cell type scores and cell death pathway gene set scores in Alveoli (top) and Vessel (bottom) region of the PVOD lung sample (* P < 0.05, ** P < 0.01, *** P < 0.001). P values are indicated in the figures. Source data are provided as a file.

10x Visium Spatial Transcriptomics Sections, 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
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10x visium spatial transcriptomics sections - by Bioz Stars, 2026-05

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1) Product Images from "Macrophage ferroptosis potentiates GCN2 deficiency induced pulmonary venous arterialization"

Article Title: Macrophage ferroptosis potentiates GCN2 deficiency induced pulmonary venous arterialization

Journal: Nature Communications

doi: 10.1038/s41467-025-64035-4

a H&E-stained images of 10X Visium spatial transcriptomics sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues. The two control samples represent the upper and lower halves of the same slide (stitched together). Scale bar = 2 mm. b Spatial mapping of tissue region clusters (Alveoli, Bronchi, Vessel, Unspecified) on spatial transcriptomics spots from Control (left) and PVOD (right) lung samples. c Violin plot showing HMOX1 expression levels across tissue regions in Control and PVOD lung samples. P values were determined via two-sided Wilcoxon rank-sum test. d Violin plots depicting expression of arterial endothelial markers ( KDR, CXCL12 ) and venous related marker ( ACKR1 ) in vessel regions comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. e Violin plots showing arterial and venous endothelial gene set scores in vessel regions of Control versus PVOD samples. P values were determined via two-sided Wilcoxon rank-sum test. f Volcano plot of differentially expressed genes in vessel regions between PVOD and Control groups. P values were determined via two-sided Wilcoxon rank-sum test with Benjamini–Hochberg correction for multiple testing. Significance thresholds were set at |log2 fold change| > 0.5 and adjusted p -value < 0.05. The top 5 upregulated and top 5 downregulated genes are annotated in the plot. GO biological processes ( g ) and KEGG pathways ( h ) significantly enriched (FDR < 0.05) from upregulated genes in PVOD vessel regions. P values were calculated using the hypergeometric test with Benjamini–Hochberg correction for multiple testing. Ten relevant terms associated with pulmonary vascular disease are shown, ranked by combined score. Dot size represents the percentage of genes in the gene set, and dot color indicates –log10(FDR). i Volcano plot of transcription factor activity differences (z-score normalized AUC scores) between Control and PVOD vessel regions analyzed by the limma method. j Violin plot showing ETS1 AUC scores in Control and PVOD vessel regions. k Violin plot of ETS1 expression in venous endothelial cells from scRNA-seq data comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. l ETS1 transcription factor binding motif (metacluster_183.1) obtained from the cisTarget motif collection (v10nr_clust). m Spatial distribution of cell type proportions (EC_arterial, EC_venous, Macrophages, Muscular cells, Fibroblasts) inferred by RCTD deconvolution. Color intensity corresponds to the relative abundance of each cell type, with darker colors indicating higher proportions. n Heatmaps showing Pearson correlation between RCTD cell type scores and cell death pathway gene set scores in Alveoli (top) and Vessel (bottom) region of the PVOD lung sample (* P < 0.05, ** P < 0.01, *** P < 0.001). P values are indicated in the figures. Source data are provided as a file.

Figure Legend Snippet: a H&E-stained images of 10X Visium spatial transcriptomics sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues. The two control samples represent the upper and lower halves of the same slide (stitched together). Scale bar = 2 mm. b Spatial mapping of tissue region clusters (Alveoli, Bronchi, Vessel, Unspecified) on spatial transcriptomics spots from Control (left) and PVOD (right) lung samples. c Violin plot showing HMOX1 expression levels across tissue regions in Control and PVOD lung samples. P values were determined via two-sided Wilcoxon rank-sum test. d Violin plots depicting expression of arterial endothelial markers ( KDR, CXCL12 ) and venous related marker ( ACKR1 ) in vessel regions comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. e Violin plots showing arterial and venous endothelial gene set scores in vessel regions of Control versus PVOD samples. P values were determined via two-sided Wilcoxon rank-sum test. f Volcano plot of differentially expressed genes in vessel regions between PVOD and Control groups. P values were determined via two-sided Wilcoxon rank-sum test with Benjamini–Hochberg correction for multiple testing. Significance thresholds were set at |log2 fold change| > 0.5 and adjusted p -value < 0.05. The top 5 upregulated and top 5 downregulated genes are annotated in the plot. GO biological processes ( g ) and KEGG pathways ( h ) significantly enriched (FDR < 0.05) from upregulated genes in PVOD vessel regions. P values were calculated using the hypergeometric test with Benjamini–Hochberg correction for multiple testing. Ten relevant terms associated with pulmonary vascular disease are shown, ranked by combined score. Dot size represents the percentage of genes in the gene set, and dot color indicates –log10(FDR). i Volcano plot of transcription factor activity differences (z-score normalized AUC scores) between Control and PVOD vessel regions analyzed by the limma method. j Violin plot showing ETS1 AUC scores in Control and PVOD vessel regions. k Violin plot of ETS1 expression in venous endothelial cells from scRNA-seq data comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. l ETS1 transcription factor binding motif (metacluster_183.1) obtained from the cisTarget motif collection (v10nr_clust). m Spatial distribution of cell type proportions (EC_arterial, EC_venous, Macrophages, Muscular cells, Fibroblasts) inferred by RCTD deconvolution. Color intensity corresponds to the relative abundance of each cell type, with darker colors indicating higher proportions. n Heatmaps showing Pearson correlation between RCTD cell type scores and cell death pathway gene set scores in Alveoli (top) and Vessel (bottom) region of the PVOD lung sample (* P < 0.05, ** P < 0.01, *** P < 0.001). P values are indicated in the figures. Source data are provided as a file.

Techniques Used: Staining, Control, Expressing, Marker, Activity Assay, Binding Assay

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Journal: Nature Communications

Article Title: Macrophage ferroptosis potentiates GCN2 deficiency induced pulmonary venous arterialization

doi: 10.1038/s41467-025-64035-4

Figure Lengend Snippet: a H&E-stained images of 10X Visium spatial transcriptomics sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues. The two control samples represent the upper and lower halves of the same slide (stitched together). Scale bar = 2 mm. b Spatial mapping of tissue region clusters (Alveoli, Bronchi, Vessel, Unspecified) on spatial transcriptomics spots from Control (left) and PVOD (right) lung samples. c Violin plot showing HMOX1 expression levels across tissue regions in Control and PVOD lung samples. P values were determined via two-sided Wilcoxon rank-sum test. d Violin plots depicting expression of arterial endothelial markers ( KDR, CXCL12 ) and venous related marker ( ACKR1 ) in vessel regions comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. e Violin plots showing arterial and venous endothelial gene set scores in vessel regions of Control versus PVOD samples. P values were determined via two-sided Wilcoxon rank-sum test. f Volcano plot of differentially expressed genes in vessel regions between PVOD and Control groups. P values were determined via two-sided Wilcoxon rank-sum test with Benjamini–Hochberg correction for multiple testing. Significance thresholds were set at |log2 fold change| > 0.5 and adjusted p -value < 0.05. The top 5 upregulated and top 5 downregulated genes are annotated in the plot. GO biological processes ( g ) and KEGG pathways ( h ) significantly enriched (FDR < 0.05) from upregulated genes in PVOD vessel regions. P values were calculated using the hypergeometric test with Benjamini–Hochberg correction for multiple testing. Ten relevant terms associated with pulmonary vascular disease are shown, ranked by combined score. Dot size represents the percentage of genes in the gene set, and dot color indicates –log10(FDR). i Volcano plot of transcription factor activity differences (z-score normalized AUC scores) between Control and PVOD vessel regions analyzed by the limma method. j Violin plot showing ETS1 AUC scores in Control and PVOD vessel regions. k Violin plot of ETS1 expression in venous endothelial cells from scRNA-seq data comparing Control and PVOD groups. P values were determined via two-sided Wilcoxon rank-sum test. l ETS1 transcription factor binding motif (metacluster_183.1) obtained from the cisTarget motif collection (v10nr_clust). m Spatial distribution of cell type proportions (EC_arterial, EC_venous, Macrophages, Muscular cells, Fibroblasts) inferred by RCTD deconvolution. Color intensity corresponds to the relative abundance of each cell type, with darker colors indicating higher proportions. n Heatmaps showing Pearson correlation between RCTD cell type scores and cell death pathway gene set scores in Alveoli (top) and Vessel (bottom) region of the PVOD lung sample (* P < 0.05, ** P < 0.01, *** P < 0.001). P values are indicated in the figures. Source data are provided as a file.

Article Snippet: Fig. 6 Spatial transcriptomics reveals enhanced venous arterialization and ETS1-mediated gene regulation in PVOD lung vessels. a H&E-stained images of 10X Visium spatial transcriptomics sections from Control ( n = 2 individuals) and PVOD ( n = 1 individual) lung tissues.

Techniques: Staining, Control, Expressing, Marker, Activity Assay, Binding Assay

Healthy human skin scRNA-seq datasets were collected and curated. Datasets were divided into PSU-containing and PSU-free samples. PSU-containing datasets underwent standardized reanalysis and processing, and integration performance was benchmarked. The most suitable tool was used to integrate these datasets into the HSCA core, followed by cell type annotation. Through transfer learning, 21 additional PSU-free datasets were incorporated, resulting in the HSCA extended (160 subjects, 177 samples, 110 cell types, >800,000 cells). Gene marker signatures were validated and refined using Visium HD spatial transcriptomics. Downstream analyses included the identification of novel and rare cell types, functional enrichment, and cell–cell communication analysis.

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: Healthy human skin scRNA-seq datasets were collected and curated. Datasets were divided into PSU-containing and PSU-free samples. PSU-containing datasets underwent standardized reanalysis and processing, and integration performance was benchmarked. The most suitable tool was used to integrate these datasets into the HSCA core, followed by cell type annotation. Through transfer learning, 21 additional PSU-free datasets were incorporated, resulting in the HSCA extended (160 subjects, 177 samples, 110 cell types, >800,000 cells). Gene marker signatures were validated and refined using Visium HD spatial transcriptomics. Downstream analyses included the identification of novel and rare cell types, functional enrichment, and cell–cell communication analysis.

Article Snippet: To validate the spatial organization of the PSU defined in our core atlas and to assess additional relevant cell types, we generated two 10X Visium HD spatial transcriptomics sections (8 μm spot diameter) derived from healthy facial skin of a 48-year-old White female donor ( ).

Techniques: Marker, Functional Assay

( a , b ) Two 10X Genomics Visium HD spatial transcriptomic sections (8 µm spot diameter) derived from healthy facial skin of a 48-year-old White female donor (temporal region). Spots were annotated with marker gene expression, and the derived cell types are overlaid on the H&E sections. The bottom-right inset of each panel displays the number of detected genes per spot (maximum 3,683 in D1 and 3,199 in D2). Bar = 250 µm. Abbreviations: see Supplementary Table 3.

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: ( a , b ) Two 10X Genomics Visium HD spatial transcriptomic sections (8 µm spot diameter) derived from healthy facial skin of a 48-year-old White female donor (temporal region). Spots were annotated with marker gene expression, and the derived cell types are overlaid on the H&E sections. The bottom-right inset of each panel displays the number of detected genes per spot (maximum 3,683 in D1 and 3,199 in D2). Bar = 250 µm. Abbreviations: see Supplementary Table 3.

Techniques: Derivative Assay, Marker, Gene Expression

(a) Illustrative schematic of hair bulb anatomy. (b) Visium HD spots corresponding to the hair bulb overlaid on the tissue section. ( c ) Spatial feature plot of Dermal papilla markers. ( d ) Dot plot showing marker gene expression across major bulb cell types. ( e ) Catagen hair follicle section (D2) highlighting cell clustering. ( f ) Violin plots of gene expression in the catagen follicle cluster, reflecting hair-cycle-specific transcriptional dynamics. ( g ) Heatmap of spatial ligand-receptor crosstalk between follicular compartments inferred by CellChat. Bar = 8 µm. Abbreviations: see Supplementary Table 3.

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: (a) Illustrative schematic of hair bulb anatomy. (b) Visium HD spots corresponding to the hair bulb overlaid on the tissue section. ( c ) Spatial feature plot of Dermal papilla markers. ( d ) Dot plot showing marker gene expression across major bulb cell types. ( e ) Catagen hair follicle section (D2) highlighting cell clustering. ( f ) Violin plots of gene expression in the catagen follicle cluster, reflecting hair-cycle-specific transcriptional dynamics. ( g ) Heatmap of spatial ligand-receptor crosstalk between follicular compartments inferred by CellChat. Bar = 8 µm. Abbreviations: see Supplementary Table 3.

Techniques: Marker, Gene Expression

( a ) UMAP of the HSCA core restricted to 8,572 cells from lower follicular compartments. ( b ) RCTD deconvolution of Visium HD data (from ) using the HSCA core, showing concordant cell type gene signatures. ( c , d ) Violin plots of marker gene expression for the SHG in the HSCA core (c) and in Visium HD (d). ( e ) PHATE embedding of sebaceous gland cells illustrating differentiation trajectories. ( f ) Pie chart summarizing the relative abundance of sebocyte maturation stages in the HSCA core. ( g ) Pie chart showing dataset origin of sebaceous cells across maturation stages. ( h ) Violin plots of PTN and C1QTNF12 expression in sebaceous progenitors and the JZ in the HSCA core. ( i ) Independent spatial validation of PTN and C1QTNF12 expression in Visium HD sections. Abbreviations: see Supplementary Table 3.

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: ( a ) UMAP of the HSCA core restricted to 8,572 cells from lower follicular compartments. ( b ) RCTD deconvolution of Visium HD data (from ) using the HSCA core, showing concordant cell type gene signatures. ( c , d ) Violin plots of marker gene expression for the SHG in the HSCA core (c) and in Visium HD (d). ( e ) PHATE embedding of sebaceous gland cells illustrating differentiation trajectories. ( f ) Pie chart summarizing the relative abundance of sebocyte maturation stages in the HSCA core. ( g ) Pie chart showing dataset origin of sebaceous cells across maturation stages. ( h ) Violin plots of PTN and C1QTNF12 expression in sebaceous progenitors and the JZ in the HSCA core. ( i ) Independent spatial validation of PTN and C1QTNF12 expression in Visium HD sections. Abbreviations: see Supplementary Table 3.

Techniques: Marker, Gene Expression, Expressing, Biomarker Discovery

(a) Feature plot of CCER2 expression highlighting the Merkel cell cluster in the HSCA core. (b) Gene signature of the cluster, including the characteristic KRT20 marker for Merkel cells. (c) Functional enrichment analysis of the Merkel cell gene signature, visualized as a dot plot. ( d , e ) Spatial visualization of CCER2 expression in the bulge region of hair follicles in Visium HD sections.

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: (a) Feature plot of CCER2 expression highlighting the Merkel cell cluster in the HSCA core. (b) Gene signature of the cluster, including the characteristic KRT20 marker for Merkel cells. (c) Functional enrichment analysis of the Merkel cell gene signature, visualized as a dot plot. ( d , e ) Spatial visualization of CCER2 expression in the bulge region of hair follicles in Visium HD sections.

Techniques: Expressing, Marker, Functional Assay

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