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10X Genomics mouse brain st data

a Schematic of semi-supervised <t>data</t> acquisition and cortical tissue characteristics, exhibiting the laminar structure (layers L1–L6). scRNA-seq data were obtained from layer-enriched dissections (mono- or multi-layer), with layer-specific annotations. Spatial data were obtained from the frontal cortex. b Comparison of cell mapping results across methods in <t>mouse</t> <t>brain</t> tissue. Astro astrocyte, Endo endothelial cell, IT intratelencephalic, CT corticothalamic, NP near-projecting, PT pyramidal tract; L2/3 IT, L4, L5 IT, L5 PT, L6 CT, L6 IT, and L6b are subclasses of Glutamatergic neurons; Lamp5 , Pvalb , Sncg , Sst , and Vip types are subclasses of GABAergic neurons. c Mapping accuracy across methods. In real world, unlike the simulated datasets, cells within the same cluster may have similar identities due to the recognition of clusters. Thus, the accuracy of cell mapping here includes replicates without considering the rate of cell loss. Mono-layer, only statistics on cells dissected from single layers. Multi-layer, statistics on cells dissected from both single and multiple layers. d , e Heatmaps of cell-type enrichment scores across layers for smFISH ( d ) and cell mapping results ( e ), cell-type ordered by CMAP results. Enrichment score is defined as the fold change in cell density within a layer relative to the entire cortex. f Schematic of the mapping strategy for proximal primitive streak cells from an E7.0 mouse embryo onto Geo-seq data. g Comparison of cell mapping results in Geo-seq data. h Schematic of sample collection for Slide-seq and single-cell datasets. ExE, Extraembryonic ectoderm; Troph, Differentiated trophoblasts. i Comparison of cell mapping results in Slide-seq sample. j Bar plots displaying the number of extraembryonic cells: Left, in single-cell data; Right, in mapping results. k Boxplots of Moran’s I values for 30 spatially variable genes in Slide-seq (ground truth) and reconstructed data. Box plots display the median (center line), the first and third quartiles (box limits), and whiskers indicating the minimum and maximum values within 1.5 times the interquartile range. P values were calculated using a two-sided Wilcoxon rank-sum test. Source data are provided as a Source Data file.

Mouse Brain St Data, supplied by 10X Genomics, 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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mouse brain st data - by Bioz Stars, 2026-05

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1) Product Images from "High-resolution mapping of single cells in spatial context"

Article Title: High-resolution mapping of single cells in spatial context

Journal: Nature Communications

doi: 10.1038/s41467-025-61667-4

a Schematic of semi-supervised data acquisition and cortical tissue characteristics, exhibiting the laminar structure (layers L1–L6). scRNA-seq data were obtained from layer-enriched dissections (mono- or multi-layer), with layer-specific annotations. Spatial data were obtained from the frontal cortex. b Comparison of cell mapping results across methods in mouse brain tissue. Astro astrocyte, Endo endothelial cell, IT intratelencephalic, CT corticothalamic, NP near-projecting, PT pyramidal tract; L2/3 IT, L4, L5 IT, L5 PT, L6 CT, L6 IT, and L6b are subclasses of Glutamatergic neurons; Lamp5 , Pvalb , Sncg , Sst , and Vip types are subclasses of GABAergic neurons. c Mapping accuracy across methods. In real world, unlike the simulated datasets, cells within the same cluster may have similar identities due to the recognition of clusters. Thus, the accuracy of cell mapping here includes replicates without considering the rate of cell loss. Mono-layer, only statistics on cells dissected from single layers. Multi-layer, statistics on cells dissected from both single and multiple layers. d , e Heatmaps of cell-type enrichment scores across layers for smFISH ( d ) and cell mapping results ( e ), cell-type ordered by CMAP results. Enrichment score is defined as the fold change in cell density within a layer relative to the entire cortex. f Schematic of the mapping strategy for proximal primitive streak cells from an E7.0 mouse embryo onto Geo-seq data. g Comparison of cell mapping results in Geo-seq data. h Schematic of sample collection for Slide-seq and single-cell datasets. ExE, Extraembryonic ectoderm; Troph, Differentiated trophoblasts. i Comparison of cell mapping results in Slide-seq sample. j Bar plots displaying the number of extraembryonic cells: Left, in single-cell data; Right, in mapping results. k Boxplots of Moran’s I values for 30 spatially variable genes in Slide-seq (ground truth) and reconstructed data. Box plots display the median (center line), the first and third quartiles (box limits), and whiskers indicating the minimum and maximum values within 1.5 times the interquartile range. P values were calculated using a two-sided Wilcoxon rank-sum test. Source data are provided as a Source Data file.

Figure Legend Snippet: a Schematic of semi-supervised data acquisition and cortical tissue characteristics, exhibiting the laminar structure (layers L1–L6). scRNA-seq data were obtained from layer-enriched dissections (mono- or multi-layer), with layer-specific annotations. Spatial data were obtained from the frontal cortex. b Comparison of cell mapping results across methods in mouse brain tissue. Astro astrocyte, Endo endothelial cell, IT intratelencephalic, CT corticothalamic, NP near-projecting, PT pyramidal tract; L2/3 IT, L4, L5 IT, L5 PT, L6 CT, L6 IT, and L6b are subclasses of Glutamatergic neurons; Lamp5 , Pvalb , Sncg , Sst , and Vip types are subclasses of GABAergic neurons. c Mapping accuracy across methods. In real world, unlike the simulated datasets, cells within the same cluster may have similar identities due to the recognition of clusters. Thus, the accuracy of cell mapping here includes replicates without considering the rate of cell loss. Mono-layer, only statistics on cells dissected from single layers. Multi-layer, statistics on cells dissected from both single and multiple layers. d , e Heatmaps of cell-type enrichment scores across layers for smFISH ( d ) and cell mapping results ( e ), cell-type ordered by CMAP results. Enrichment score is defined as the fold change in cell density within a layer relative to the entire cortex. f Schematic of the mapping strategy for proximal primitive streak cells from an E7.0 mouse embryo onto Geo-seq data. g Comparison of cell mapping results in Geo-seq data. h Schematic of sample collection for Slide-seq and single-cell datasets. ExE, Extraembryonic ectoderm; Troph, Differentiated trophoblasts. i Comparison of cell mapping results in Slide-seq sample. j Bar plots displaying the number of extraembryonic cells: Left, in single-cell data; Right, in mapping results. k Boxplots of Moran’s I values for 30 spatially variable genes in Slide-seq (ground truth) and reconstructed data. Box plots display the median (center line), the first and third quartiles (box limits), and whiskers indicating the minimum and maximum values within 1.5 times the interquartile range. P values were calculated using a two-sided Wilcoxon rank-sum test. Source data are provided as a Source Data file.

Techniques Used: Comparison

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Journal: Nature Communications

Article Title: High-resolution mapping of single cells in spatial context

doi: 10.1038/s41467-025-61667-4

Figure Lengend Snippet: a Schematic of semi-supervised data acquisition and cortical tissue characteristics, exhibiting the laminar structure (layers L1–L6). scRNA-seq data were obtained from layer-enriched dissections (mono- or multi-layer), with layer-specific annotations. Spatial data were obtained from the frontal cortex. b Comparison of cell mapping results across methods in mouse brain tissue. Astro astrocyte, Endo endothelial cell, IT intratelencephalic, CT corticothalamic, NP near-projecting, PT pyramidal tract; L2/3 IT, L4, L5 IT, L5 PT, L6 CT, L6 IT, and L6b are subclasses of Glutamatergic neurons; Lamp5 , Pvalb , Sncg , Sst , and Vip types are subclasses of GABAergic neurons. c Mapping accuracy across methods. In real world, unlike the simulated datasets, cells within the same cluster may have similar identities due to the recognition of clusters. Thus, the accuracy of cell mapping here includes replicates without considering the rate of cell loss. Mono-layer, only statistics on cells dissected from single layers. Multi-layer, statistics on cells dissected from both single and multiple layers. d , e Heatmaps of cell-type enrichment scores across layers for smFISH ( d ) and cell mapping results ( e ), cell-type ordered by CMAP results. Enrichment score is defined as the fold change in cell density within a layer relative to the entire cortex. f Schematic of the mapping strategy for proximal primitive streak cells from an E7.0 mouse embryo onto Geo-seq data. g Comparison of cell mapping results in Geo-seq data. h Schematic of sample collection for Slide-seq and single-cell datasets. ExE, Extraembryonic ectoderm; Troph, Differentiated trophoblasts. i Comparison of cell mapping results in Slide-seq sample. j Bar plots displaying the number of extraembryonic cells: Left, in single-cell data; Right, in mapping results. k Boxplots of Moran’s I values for 30 spatially variable genes in Slide-seq (ground truth) and reconstructed data. Box plots display the median (center line), the first and third quartiles (box limits), and whiskers indicating the minimum and maximum values within 1.5 times the interquartile range. P values were calculated using a two-sided Wilcoxon rank-sum test. Source data are provided as a Source Data file.

Article Snippet: Mouse brain ST data are available from https://www.10xgenomics.com/datasets/mouse-brain-serial-section-1-sagittal-anterior-1-standard-1-0-0 .

Techniques: Comparison

Utilization of scRank for identifying neuronal subtypes targeted by fluoxetine in MDD (A) Top image displays snRNA-seq dataset of the dorsolateral prefrontal cortex (DLPFC) in Brodmann area 9 (BA9) derived from 17 patients with MDD. The lower image shows a schematic diagram of the mechanism of fluoxetine for MDD. scRNA-seq data for the MDD condition and the fluoxetine target gene were input data for scRank. (B) UMAP visualizations of data with 25 cell types colored based on the predicted rank for drug response. Bar plot shows the scaled perturbation score for each cell type. Ex, excitatory neurons; Inhib, inhibitory neurons; Oligos, oligodendrocytes; Endo, endothelial; Astro, astrocytes; OPC, oligodendrocyte precursor cells. (C) Heatmap of the GRN in excitatory neuron cluster 9 (Ex_9) with 205 MDD risk genes, which were separated into four modules. The top right heatmap represents the subnetwork of modules 2–4 for Ex_9, while the bottom right heatmap represents the network for inhibitory neuron cluster 5 (Inhib_5). Both heatmaps represent the GRN in untreated samples. The graphs to the right of the heatmap provide the network visualizations for module 2 in corresponding cell types, where gene nodes are colored based on their module. (D) Significantly enriched biological processes and pathways for module genes determined using the Metascape web tool. (E) Average module 2 activity for each neuron subtype in MDD. Data are presented as boxplots (minima, 25th percentile; median, 75th percentile; and maxima). The number of data points is 26 for each group. The comparison of the drug-target-related module for Ex_9 between the control group and MDD group is shown on the right, with respect to the averaged edge weight of 26 module 2 genes evaluated via a paired two-sided Wilcoxon test. (F) Averaged log fold change of MDD risk genes between healthy state and disease state. (G) Significantly activated pathways in Ex_9 determined via GSEA of the differentially expressed MDD risk genes. (H and I) Spatial mapping of Ex_9 using CellTrek. The images on the left in both (H) and (I) represent the layer annotation for each spatial spot in mouse anterior brain tissue (H) or human dorsolateral prefrontal cortex tissue (I). The images on the right in (H) and (I) represent the spatial distribution of Ex_9, where red pixels specifically mark the location of these neurons. The deeper layers (layers 5 and 6) are particularly highlighted. The subsequent bar plot shows the relative proportion of cells in each layer.

Journal: Cell Reports Medicine

Article Title: scRank infers drug-responsive cell types from untreated scRNA-seq data using a target-perturbed gene regulatory network

doi: 10.1016/j.xcrm.2024.101568

Figure Lengend Snippet: Utilization of scRank for identifying neuronal subtypes targeted by fluoxetine in MDD (A) Top image displays snRNA-seq dataset of the dorsolateral prefrontal cortex (DLPFC) in Brodmann area 9 (BA9) derived from 17 patients with MDD. The lower image shows a schematic diagram of the mechanism of fluoxetine for MDD. scRNA-seq data for the MDD condition and the fluoxetine target gene were input data for scRank. (B) UMAP visualizations of data with 25 cell types colored based on the predicted rank for drug response. Bar plot shows the scaled perturbation score for each cell type. Ex, excitatory neurons; Inhib, inhibitory neurons; Oligos, oligodendrocytes; Endo, endothelial; Astro, astrocytes; OPC, oligodendrocyte precursor cells. (C) Heatmap of the GRN in excitatory neuron cluster 9 (Ex_9) with 205 MDD risk genes, which were separated into four modules. The top right heatmap represents the subnetwork of modules 2–4 for Ex_9, while the bottom right heatmap represents the network for inhibitory neuron cluster 5 (Inhib_5). Both heatmaps represent the GRN in untreated samples. The graphs to the right of the heatmap provide the network visualizations for module 2 in corresponding cell types, where gene nodes are colored based on their module. (D) Significantly enriched biological processes and pathways for module genes determined using the Metascape web tool. (E) Average module 2 activity for each neuron subtype in MDD. Data are presented as boxplots (minima, 25th percentile; median, 75th percentile; and maxima). The number of data points is 26 for each group. The comparison of the drug-target-related module for Ex_9 between the control group and MDD group is shown on the right, with respect to the averaged edge weight of 26 module 2 genes evaluated via a paired two-sided Wilcoxon test. (F) Averaged log fold change of MDD risk genes between healthy state and disease state. (G) Significantly activated pathways in Ex_9 determined via GSEA of the differentially expressed MDD risk genes. (H and I) Spatial mapping of Ex_9 using CellTrek. The images on the left in both (H) and (I) represent the layer annotation for each spatial spot in mouse anterior brain tissue (H) or human dorsolateral prefrontal cortex tissue (I). The images on the right in (H) and (I) represent the spatial distribution of Ex_9, where red pixels specifically mark the location of these neurons. The deeper layers (layers 5 and 6) are particularly highlighted. The subsequent bar plot shows the relative proportion of cells in each layer.

Article Snippet: For mouse brain ST data (10X Genomics Visium), we downloaded Seurat objects from ( https://satijalab.org/seurat/articles/spatial_vignette.html ).

Techniques: Derivative Assay, Inhibition, Activity Assay, Comparison, Control

Analysis of four anterior and posterior sections of mouse brain tissue on sagittal plane with MUSTANG (A) Paired anterior-posterior slices placed on the 10X Visium gene expression slides. (B) Spot-based spatial pie charts of MUSTANG-inferred brain region proportions for all four mouse brain tissue sections. (C) Left: MUSTANG-inferred cell numbers for brain region 5 matching the spatial pattern of the cortex anatomical brain region. Middle: spot-level expression visualization of the known cortex layer marker gene Tbr1. Right: the ISH images of this marker gene from the Allen Brain Atlas. (D) Left: MUSTANG-inferred cell numbers for brain region 3 matching the spatial pattern of the hypothalamus anatomical brain region. Middle: spot-level expression visualization of the known hypothalamus layer marker gene Zcchc12. Right: the ISH images of this marker gene from the Allen Brain Atlas.

Journal: Patterns

Article Title: MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

doi: 10.1016/j.patter.2024.100986

Figure Lengend Snippet: Analysis of four anterior and posterior sections of mouse brain tissue on sagittal plane with MUSTANG (A) Paired anterior-posterior slices placed on the 10X Visium gene expression slides. (B) Spot-based spatial pie charts of MUSTANG-inferred brain region proportions for all four mouse brain tissue sections. (C) Left: MUSTANG-inferred cell numbers for brain region 5 matching the spatial pattern of the cortex anatomical brain region. Middle: spot-level expression visualization of the known cortex layer marker gene Tbr1. Right: the ISH images of this marker gene from the Allen Brain Atlas. (D) Left: MUSTANG-inferred cell numbers for brain region 3 matching the spatial pattern of the hypothalamus anatomical brain region. Middle: spot-level expression visualization of the known hypothalamus layer marker gene Zcchc12. Right: the ISH images of this marker gene from the Allen Brain Atlas.

Article Snippet: Specifically, the sagittal mouse brain ST data are accessible on the 10X Genomics website at https://support.10xgenomics.com/spatial-gene-expression/datasets .

Techniques: Gene Expression, Expressing, Marker

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