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Spatial Transcriptomics Inc spatial transcriptomics visium
Spatial Transcriptomics Visium, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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(a) MI was induced followed by an intramyocardial injection of ECM hydrogel or saline 7 days post-MI. Hearts were then harvested for either snRNAseq or spatial <t>transcriptomics</t> 7 days post-injection (14 days post-MI). Sample size: n = 2 ECM hydrogel replicates, 7658 spots. (b) Myocardium (green) was labelled with anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue). (c) The adjacent cryosection was used for spatial transcriptomics via <t>10X</t> <t>Visium,</t> where the infarct containing ECM hydrogel (red) was found to cluster separately from the infarct alone (cyan). (d) The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) were found to be immune and vascularly dominating genes compared to the down regulated genes impacting the infarct zone (cyan). (e-f) All differentially expressed genes in the ECM hydrogel zone (red) and infarct only zone were subjected to GO enrichment.
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EAC primary and metastatic samples show a diverse landscape of TME and malignant cells in transcriptomic and epigenetic data (A) Schematic representation of the study workflow. Biopsies from 10 patients in our discovery cohort, including normal adjacent tissue (NAT), primary tissue, and metastatic samples, were subjected to single-nuclei RNA and ATAC sequencing using 10X Chromium technology. For a subset of these patients as well as three additional patients, matched primary and metastatic samples were profiled with 10X <t>Visium</t> and 10X Xenium spatial <t>transcriptomics</t> (ST) technologies. For single-nuclei data, cells were annotated by cell type and categorized into malignant and TME components. TME subtypes were linked to metastasis, with validation against an external pan-cancer fibroblast atlas. The malignant cell components underwent analysis using consensus non-negative matrix factorization (cNMF) to uncover malignant programs, which were further characterized for transcriptional and epigenetic heterogeneity at a single-cell and spatial level and candidate master transcription factors. External validation was performed in two single-cell validation cohorts, , and associations with clinical and molecular characteristics, as well as survival, were assessed in three bulk validation cohorts. , , (B) Uniform manifold approximation and projection (UMAP) representation of the full cohort in Harmony-corrected integrated transcriptomic data, with major cell type compartments labeled and cell counts indicated. (C) Proportion of major cell types in each sample based on transcriptomic data, with percentages for compartments representing over 5% of the total sample composition. (D) UMAP representation of the full cohort in Harmony-corrected integrated ATAC data, with cell type annotations transferred from the RNA annotations. “NA” denotes cells without paired associated RNA information. (E) Proportion of major cell types in each sample based on ATAC data, with percentages for compartments representing over 5% of the total sample composition.
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(a) MI was induced followed by an intramyocardial injection of ECM hydrogel or saline 7 days post-MI. Hearts were then harvested for either snRNAseq or spatial transcriptomics 7 days post-injection (14 days post-MI). Sample size: n = 2 ECM hydrogel replicates, 7658 spots. (b) Myocardium (green) was labelled with anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue). (c) The adjacent cryosection was used for spatial transcriptomics via 10X Visium, where the infarct containing ECM hydrogel (red) was found to cluster separately from the infarct alone (cyan). (d) The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) were found to be immune and vascularly dominating genes compared to the down regulated genes impacting the infarct zone (cyan). (e-f) All differentially expressed genes in the ECM hydrogel zone (red) and infarct only zone were subjected to GO enrichment.

Journal: bioRxiv

Article Title: Uncovering the Regional and Cell Specific Bioactivity of Injectable Extracellular Matrix Biomaterials in Myocardial Infarction through Spatial and Single Nucleus Transcriptomics

doi: 10.1101/2025.06.25.661525

Figure Lengend Snippet: (a) MI was induced followed by an intramyocardial injection of ECM hydrogel or saline 7 days post-MI. Hearts were then harvested for either snRNAseq or spatial transcriptomics 7 days post-injection (14 days post-MI). Sample size: n = 2 ECM hydrogel replicates, 7658 spots. (b) Myocardium (green) was labelled with anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue). (c) The adjacent cryosection was used for spatial transcriptomics via 10X Visium, where the infarct containing ECM hydrogel (red) was found to cluster separately from the infarct alone (cyan). (d) The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) were found to be immune and vascularly dominating genes compared to the down regulated genes impacting the infarct zone (cyan). (e-f) All differentially expressed genes in the ECM hydrogel zone (red) and infarct only zone were subjected to GO enrichment.

Article Snippet: Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide.

Techniques: Injection, Saline

(a) MI is induced followed by an intramyocardial injection of ECM hydrogel or saline 8 weeks post-MI. Hearts are then harvested for either snRNAseq or spatial transcriptomics 7 days post-injection. Sample size: n = 3 ECM hydrogel replicates, 9594 spots. (b) Myocardium (green) was labelled with an anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue). (c) An adjacent cryosection to the immunofluorescence image in b was used for spatial transcriptomics via 10X Visium, where the infarct containing ECM hydrogel (red) was found to cluster separately from the normal infarct zone (cyan). (d) Top differentially expressed genes for both ECM within infarct (red) and infarct alone (cyan) are shown. (e-f) A comparison of the two zones reflects the ECM hydrogel activates fibroblasts and is responsible for further vascular development, as demonstrated through GO enrichment.

Journal: bioRxiv

Article Title: Uncovering the Regional and Cell Specific Bioactivity of Injectable Extracellular Matrix Biomaterials in Myocardial Infarction through Spatial and Single Nucleus Transcriptomics

doi: 10.1101/2025.06.25.661525

Figure Lengend Snippet: (a) MI is induced followed by an intramyocardial injection of ECM hydrogel or saline 8 weeks post-MI. Hearts are then harvested for either snRNAseq or spatial transcriptomics 7 days post-injection. Sample size: n = 3 ECM hydrogel replicates, 9594 spots. (b) Myocardium (green) was labelled with an anti-alpha-actinin antibody alongside fluorescently tagged ECM hydrogel (light blue). (c) An adjacent cryosection to the immunofluorescence image in b was used for spatial transcriptomics via 10X Visium, where the infarct containing ECM hydrogel (red) was found to cluster separately from the normal infarct zone (cyan). (d) Top differentially expressed genes for both ECM within infarct (red) and infarct alone (cyan) are shown. (e-f) A comparison of the two zones reflects the ECM hydrogel activates fibroblasts and is responsible for further vascular development, as demonstrated through GO enrichment.

Article Snippet: Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide.

Techniques: Injection, Saline, Immunofluorescence, Comparison

(a) The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) with integrated subacute and chronic Visium were found to be immune, fibroblast, and vascularly dominating genes compared to the downregulated genes impacting the infarct zone (cyan). Sample size: n = 2 for subacute ECM hydrogel (7658 spots); n = 3 for chronic ECM hydrogel (9594 spots) (b) The ECM zones in both subacute and chronic models of MI have higher expression of the matrix specific genes relative to the infarct zone. (c-f) Macrophages (c) , endothelial cells (d) , cardiomyocytes (e) , and fibroblasts (f) treated with ECM hydrogel in subacute and chronic MI were subsetted, reclustered and compared with respect to MI timepoint. Sample size: n = 2 subacute ECM hydrogel (downsampled to 3000 cells), n = 2 chronic ECM hydrogel (downsampled to 3000 cells). Top differentially expressed genes were displayed via Volcano Plot, and the differentially expressed genes were subjected to GO enrichment. (g) Comparison of transcriptomic findings between subacute and chronic MI.

Journal: bioRxiv

Article Title: Uncovering the Regional and Cell Specific Bioactivity of Injectable Extracellular Matrix Biomaterials in Myocardial Infarction through Spatial and Single Nucleus Transcriptomics

doi: 10.1101/2025.06.25.661525

Figure Lengend Snippet: (a) The top upregulated differentially expressed genes defining the ECM hydrogel zone (red) with integrated subacute and chronic Visium were found to be immune, fibroblast, and vascularly dominating genes compared to the downregulated genes impacting the infarct zone (cyan). Sample size: n = 2 for subacute ECM hydrogel (7658 spots); n = 3 for chronic ECM hydrogel (9594 spots) (b) The ECM zones in both subacute and chronic models of MI have higher expression of the matrix specific genes relative to the infarct zone. (c-f) Macrophages (c) , endothelial cells (d) , cardiomyocytes (e) , and fibroblasts (f) treated with ECM hydrogel in subacute and chronic MI were subsetted, reclustered and compared with respect to MI timepoint. Sample size: n = 2 subacute ECM hydrogel (downsampled to 3000 cells), n = 2 chronic ECM hydrogel (downsampled to 3000 cells). Top differentially expressed genes were displayed via Volcano Plot, and the differentially expressed genes were subjected to GO enrichment. (g) Comparison of transcriptomic findings between subacute and chronic MI.

Article Snippet: Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide.

Techniques: Expressing, Comparison

EAC primary and metastatic samples show a diverse landscape of TME and malignant cells in transcriptomic and epigenetic data (A) Schematic representation of the study workflow. Biopsies from 10 patients in our discovery cohort, including normal adjacent tissue (NAT), primary tissue, and metastatic samples, were subjected to single-nuclei RNA and ATAC sequencing using 10X Chromium technology. For a subset of these patients as well as three additional patients, matched primary and metastatic samples were profiled with 10X Visium and 10X Xenium spatial transcriptomics (ST) technologies. For single-nuclei data, cells were annotated by cell type and categorized into malignant and TME components. TME subtypes were linked to metastasis, with validation against an external pan-cancer fibroblast atlas. The malignant cell components underwent analysis using consensus non-negative matrix factorization (cNMF) to uncover malignant programs, which were further characterized for transcriptional and epigenetic heterogeneity at a single-cell and spatial level and candidate master transcription factors. External validation was performed in two single-cell validation cohorts, , and associations with clinical and molecular characteristics, as well as survival, were assessed in three bulk validation cohorts. , , (B) Uniform manifold approximation and projection (UMAP) representation of the full cohort in Harmony-corrected integrated transcriptomic data, with major cell type compartments labeled and cell counts indicated. (C) Proportion of major cell types in each sample based on transcriptomic data, with percentages for compartments representing over 5% of the total sample composition. (D) UMAP representation of the full cohort in Harmony-corrected integrated ATAC data, with cell type annotations transferred from the RNA annotations. “NA” denotes cells without paired associated RNA information. (E) Proportion of major cell types in each sample based on ATAC data, with percentages for compartments representing over 5% of the total sample composition.

Journal: Cell Reports Medicine

Article Title: Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

doi: 10.1016/j.xcrm.2025.102188

Figure Lengend Snippet: EAC primary and metastatic samples show a diverse landscape of TME and malignant cells in transcriptomic and epigenetic data (A) Schematic representation of the study workflow. Biopsies from 10 patients in our discovery cohort, including normal adjacent tissue (NAT), primary tissue, and metastatic samples, were subjected to single-nuclei RNA and ATAC sequencing using 10X Chromium technology. For a subset of these patients as well as three additional patients, matched primary and metastatic samples were profiled with 10X Visium and 10X Xenium spatial transcriptomics (ST) technologies. For single-nuclei data, cells were annotated by cell type and categorized into malignant and TME components. TME subtypes were linked to metastasis, with validation against an external pan-cancer fibroblast atlas. The malignant cell components underwent analysis using consensus non-negative matrix factorization (cNMF) to uncover malignant programs, which were further characterized for transcriptional and epigenetic heterogeneity at a single-cell and spatial level and candidate master transcription factors. External validation was performed in two single-cell validation cohorts, , and associations with clinical and molecular characteristics, as well as survival, were assessed in three bulk validation cohorts. , , (B) Uniform manifold approximation and projection (UMAP) representation of the full cohort in Harmony-corrected integrated transcriptomic data, with major cell type compartments labeled and cell counts indicated. (C) Proportion of major cell types in each sample based on transcriptomic data, with percentages for compartments representing over 5% of the total sample composition. (D) UMAP representation of the full cohort in Harmony-corrected integrated ATAC data, with cell type annotations transferred from the RNA annotations. “NA” denotes cells without paired associated RNA information. (E) Proportion of major cell types in each sample based on ATAC data, with percentages for compartments representing over 5% of the total sample composition.

Article Snippet: Raw and processed spatial transcriptomics Visium data , This paper , Zenodo: 10.5281/zenodo.15341263.

Techniques: Sequencing, Biomarker Discovery, Labeling

Single-nuclei-derived transcriptional programs highlight different spatial regions of EAC tumors (A) Spatial transcriptomics (ST) slides of P8 primary tumor A, colored according to cNMF program score and the CNV-derived label. For each spot, we infer the CNV profile with inferCNV and assign spots to tumor, mixed, and normal status. cNMF scores are computed as the average Z score of signature genes using the deconvolved carcinoma-specific gene expression profile of spots derived with Cell2Location. (B) Average cNMF score according to the position of the spots compared to the tumor-leading edge. For each tumor spot, we compute the distance to the edge as the shortest path to a normal or mixed spot. The distribution of cNMF scores with standard error is represented for normal spots, mixed spots, and spots of a certain distance to the edge. (C) cNMF scores for carcinoma cells and cell type annotations in a subset of Xenium-profiled samples (P4_A, P11_B, and P12_D). cNMF scores are computed as the average Z score across all carcinoma cells of signature genes included in the Xenium panel. (D) CellCharter cluster assignments for a subset of Xenium-profiled samples (P4_A, P11_B, and P12_D). (E) CellCharter cluster cell type proportion: each cell is assigned a cluster and we represent the proportion of the different cell types in each of the CellCharter clusters. (F) Distribution of cNMF scores of carcinoma cells belonging to the CellCharter clusters with a substantial amount of carcinoma cells (>5%), CC1, CC2, CC3, and CC4. For all comparisons, Mann-Whitney U p < 0.000005.

Journal: Cell Reports Medicine

Article Title: Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

doi: 10.1016/j.xcrm.2025.102188

Figure Lengend Snippet: Single-nuclei-derived transcriptional programs highlight different spatial regions of EAC tumors (A) Spatial transcriptomics (ST) slides of P8 primary tumor A, colored according to cNMF program score and the CNV-derived label. For each spot, we infer the CNV profile with inferCNV and assign spots to tumor, mixed, and normal status. cNMF scores are computed as the average Z score of signature genes using the deconvolved carcinoma-specific gene expression profile of spots derived with Cell2Location. (B) Average cNMF score according to the position of the spots compared to the tumor-leading edge. For each tumor spot, we compute the distance to the edge as the shortest path to a normal or mixed spot. The distribution of cNMF scores with standard error is represented for normal spots, mixed spots, and spots of a certain distance to the edge. (C) cNMF scores for carcinoma cells and cell type annotations in a subset of Xenium-profiled samples (P4_A, P11_B, and P12_D). cNMF scores are computed as the average Z score across all carcinoma cells of signature genes included in the Xenium panel. (D) CellCharter cluster assignments for a subset of Xenium-profiled samples (P4_A, P11_B, and P12_D). (E) CellCharter cluster cell type proportion: each cell is assigned a cluster and we represent the proportion of the different cell types in each of the CellCharter clusters. (F) Distribution of cNMF scores of carcinoma cells belonging to the CellCharter clusters with a substantial amount of carcinoma cells (>5%), CC1, CC2, CC3, and CC4. For all comparisons, Mann-Whitney U p < 0.000005.

Article Snippet: Raw and processed spatial transcriptomics Visium data , This paper , Zenodo: 10.5281/zenodo.15341263.

Techniques: Derivative Assay, Gene Expression, MANN-WHITNEY