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10X Genomics visium mouse brain section coronal
PHD-MS identifies stable brain structures in a <t>Visium</t> <t>mouse</t> brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
Visium Mouse Brain Section Coronal, 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
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visium mouse brain section coronal - by Bioz Stars, 2026-07
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1) Product Images from "Multiscale domain identification for spatial transcriptomics via persistent homology"

Article Title: Multiscale domain identification for spatial transcriptomics via persistent homology

Journal: Cell Reports Methods

doi: 10.1016/j.crmeth.2026.101376

PHD-MS identifies stable brain structures in a Visium mouse brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
Figure Legend Snippet: PHD-MS identifies stable brain structures in a Visium mouse brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.

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PHD-MS identifies stable brain structures in a <t>Visium</t> <t>mouse</t> brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
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10X Genomics 10x visium mouse brain coronal section data
PHD-MS identifies stable brain structures in a <t>Visium</t> <t>mouse</t> brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
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PHD-MS identifies stable brain structures in a <t>Visium</t> <t>mouse</t> brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
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10X Genomics 10x visium coronal section of the mouse brain dataset
PHD-MS identifies stable brain structures in a <t>Visium</t> <t>mouse</t> brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
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PHD-MS identifies stable brain structures in a <t>Visium</t> <t>mouse</t> brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.
Visium Dataset Mouse Brain Coronal Section 1 (Ffpe), 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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10X Genomics visium mouse brain section (coronal
A-C) Multi-scale analysis. A) Pictogram depicting the hierarchy of multiple biological scales. B) Sankeyplot showing the hierarchical relationships between different spatial units in Giotto Suite. C) Overlay of multi-scale annotations of a MERFISH dataset; depicting nuclear (magenta) and cytoplasmic (cyan) enriched transcripts for all genes in GSEA terms related to “programmed cell death” and “COPII-coated ER to Golgi transport vesicle”, respectively. The nuclear boundary is defined with a yellow border, and the cell body is filled in with dark green. D-F) Registration and segmentation. D) Pictogram showing multi-modal co-registration from serial tissue sections. E) Aligned Xenium (Black), <t>Visium</t> (Orange), and immunofluorescence (Red and Green) spatial datasets from a single breast cancer <t>sample</t> <t>(10X</t> Genomics). F) Overlay of HER2 protein (rasterized intensity, blue gradient) and ERBB2 transcripts (points, red) after co-registration, inset shows zoomed-in region. G-H ) Multi-modal data analysis. G) Pictogram depicting multi-modal data analysis from two different modalities obtained from the same tissue slice. H) Integrated clustering results (RNA + Protein) from the 10X Genomics CytAassist Visium Human Tonsil dataset. I-L) Scalable data analysis. I) Pictograms depicting on-disk backends, parallelization, and projection to improve scalability within Giotto Suite. J) Stereo-seq datasets processed at bin1 and analyzed through multiple levels of hexagon aggregation, the inset depicts a zoomed-in subset and visualization of niche clustering on Leiden annotations and associated selected transcripts with random jitter. K-L) Tiling and pseudo-spatial data creation K) Schematic pictograms for different tiling options and tunable parameters. L) Spatial deconvolution plot showing the percentage of individual brain cell types for the pseudo-visium dataset generated from the stereo-seq subset in J.
Visium Mouse Brain Section (Coronal, 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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10X Genomics visium datasets (mouse brain coronal section 2 (ffpe
A-C) Multi-scale analysis. A) Pictogram depicting the hierarchy of multiple biological scales. B) Sankeyplot showing the hierarchical relationships between different spatial units in Giotto Suite. C) Overlay of multi-scale annotations of a MERFISH dataset; depicting nuclear (magenta) and cytoplasmic (cyan) enriched transcripts for all genes in GSEA terms related to “programmed cell death” and “COPII-coated ER to Golgi transport vesicle”, respectively. The nuclear boundary is defined with a yellow border, and the cell body is filled in with dark green. D-F) Registration and segmentation. D) Pictogram showing multi-modal co-registration from serial tissue sections. E) Aligned Xenium (Black), <t>Visium</t> (Orange), and immunofluorescence (Red and Green) spatial datasets from a single breast cancer <t>sample</t> <t>(10X</t> Genomics). F) Overlay of HER2 protein (rasterized intensity, blue gradient) and ERBB2 transcripts (points, red) after co-registration, inset shows zoomed-in region. G-H ) Multi-modal data analysis. G) Pictogram depicting multi-modal data analysis from two different modalities obtained from the same tissue slice. H) Integrated clustering results (RNA + Protein) from the 10X Genomics CytAassist Visium Human Tonsil dataset. I-L) Scalable data analysis. I) Pictograms depicting on-disk backends, parallelization, and projection to improve scalability within Giotto Suite. J) Stereo-seq datasets processed at bin1 and analyzed through multiple levels of hexagon aggregation, the inset depicts a zoomed-in subset and visualization of niche clustering on Leiden annotations and associated selected transcripts with random jitter. K-L) Tiling and pseudo-spatial data creation K) Schematic pictograms for different tiling options and tunable parameters. L) Spatial deconvolution plot showing the percentage of individual brain cell types for the pseudo-visium dataset generated from the stereo-seq subset in J.
Visium Datasets (Mouse Brain Coronal Section 2 (Ffpe, 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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10X Genomics 10x visium dataset of mouse brain coronal sections
A-C) Multi-scale analysis. A) Pictogram depicting the hierarchy of multiple biological scales. B) Sankeyplot showing the hierarchical relationships between different spatial units in Giotto Suite. C) Overlay of multi-scale annotations of a MERFISH dataset; depicting nuclear (magenta) and cytoplasmic (cyan) enriched transcripts for all genes in GSEA terms related to “programmed cell death” and “COPII-coated ER to Golgi transport vesicle”, respectively. The nuclear boundary is defined with a yellow border, and the cell body is filled in with dark green. D-F) Registration and segmentation. D) Pictogram showing multi-modal co-registration from serial tissue sections. E) Aligned Xenium (Black), <t>Visium</t> (Orange), and immunofluorescence (Red and Green) spatial datasets from a single breast cancer <t>sample</t> <t>(10X</t> Genomics). F) Overlay of HER2 protein (rasterized intensity, blue gradient) and ERBB2 transcripts (points, red) after co-registration, inset shows zoomed-in region. G-H ) Multi-modal data analysis. G) Pictogram depicting multi-modal data analysis from two different modalities obtained from the same tissue slice. H) Integrated clustering results (RNA + Protein) from the 10X Genomics CytAassist Visium Human Tonsil dataset. I-L) Scalable data analysis. I) Pictograms depicting on-disk backends, parallelization, and projection to improve scalability within Giotto Suite. J) Stereo-seq datasets processed at bin1 and analyzed through multiple levels of hexagon aggregation, the inset depicts a zoomed-in subset and visualization of niche clustering on Leiden annotations and associated selected transcripts with random jitter. K-L) Tiling and pseudo-spatial data creation K) Schematic pictograms for different tiling options and tunable parameters. L) Spatial deconvolution plot showing the percentage of individual brain cell types for the pseudo-visium dataset generated from the stereo-seq subset in J.
10x Visium Dataset Of Mouse Brain Coronal Sections, 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
https://www.bioz.com/product/visium+mouse+brain+section+coronal/pmc09719477__41467_2022_35233_MOESM3_ESM-307-9-18?v=10X+Genomics
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A-C) Multi-scale analysis. A) Pictogram depicting the hierarchy of multiple biological scales. B) Sankeyplot showing the hierarchical relationships between different spatial units in Giotto Suite. C) Overlay of multi-scale annotations of a MERFISH dataset; depicting nuclear (magenta) and cytoplasmic (cyan) enriched transcripts for all genes in GSEA terms related to “programmed cell death” and “COPII-coated ER to Golgi transport vesicle”, respectively. The nuclear boundary is defined with a yellow border, and the cell body is filled in with dark green. D-F) Registration and segmentation. D) Pictogram showing multi-modal co-registration from serial tissue sections. E) Aligned Xenium (Black), <t>Visium</t> (Orange), and immunofluorescence (Red and Green) spatial datasets from a single breast cancer <t>sample</t> <t>(10X</t> Genomics). F) Overlay of HER2 protein (rasterized intensity, blue gradient) and ERBB2 transcripts (points, red) after co-registration, inset shows zoomed-in region. G-H ) Multi-modal data analysis. G) Pictogram depicting multi-modal data analysis from two different modalities obtained from the same tissue slice. H) Integrated clustering results (RNA + Protein) from the 10X Genomics CytAassist Visium Human Tonsil dataset. I-L) Scalable data analysis. I) Pictograms depicting on-disk backends, parallelization, and projection to improve scalability within Giotto Suite. J) Stereo-seq datasets processed at bin1 and analyzed through multiple levels of hexagon aggregation, the inset depicts a zoomed-in subset and visualization of niche clustering on Leiden annotations and associated selected transcripts with random jitter. K-L) Tiling and pseudo-spatial data creation K) Schematic pictograms for different tiling options and tunable parameters. L) Spatial deconvolution plot showing the percentage of individual brain cell types for the pseudo-visium dataset generated from the stereo-seq subset in J.
10x Genomics Visium H&E Mouse Brain Coronal Section, 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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Image Search Results


PHD-MS identifies stable brain structures in a Visium mouse brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.

Journal: Cell Reports Methods

Article Title: Multiscale domain identification for spatial transcriptomics via persistent homology

doi: 10.1016/j.crmeth.2026.101376

Figure Lengend Snippet: PHD-MS identifies stable brain structures in a Visium mouse brain (A) An annotated coronal section from Allen Brain Atlas as the ground truth. (B) NeST coexpression hotspots of the Visium mouse brain data. NeST identifies 5 relevant layers of structure, color coded by layer (bottom), matched to the annotated regions of Allen Atlas (right). (C) Nested PHD-MS domains with layer labels, color coded with matched regions in Allen Atlas. Top layer represents the domain at its broadest scale, including low-coreness spots. Middle layer includes medium-coreness spots, and core layer forms the domain’s stable core.

Article Snippet: Visium mouse brain section (coronal) , 10x Genomics , https://squidpy.readthedocs.io/en/stable/api/squidpy.datasets.visium_hne_adata.html#squidpy.datasets.visium_hne_adata.

Techniques:

A-C) Multi-scale analysis. A) Pictogram depicting the hierarchy of multiple biological scales. B) Sankeyplot showing the hierarchical relationships between different spatial units in Giotto Suite. C) Overlay of multi-scale annotations of a MERFISH dataset; depicting nuclear (magenta) and cytoplasmic (cyan) enriched transcripts for all genes in GSEA terms related to “programmed cell death” and “COPII-coated ER to Golgi transport vesicle”, respectively. The nuclear boundary is defined with a yellow border, and the cell body is filled in with dark green. D-F) Registration and segmentation. D) Pictogram showing multi-modal co-registration from serial tissue sections. E) Aligned Xenium (Black), Visium (Orange), and immunofluorescence (Red and Green) spatial datasets from a single breast cancer sample (10X Genomics). F) Overlay of HER2 protein (rasterized intensity, blue gradient) and ERBB2 transcripts (points, red) after co-registration, inset shows zoomed-in region. G-H ) Multi-modal data analysis. G) Pictogram depicting multi-modal data analysis from two different modalities obtained from the same tissue slice. H) Integrated clustering results (RNA + Protein) from the 10X Genomics CytAassist Visium Human Tonsil dataset. I-L) Scalable data analysis. I) Pictograms depicting on-disk backends, parallelization, and projection to improve scalability within Giotto Suite. J) Stereo-seq datasets processed at bin1 and analyzed through multiple levels of hexagon aggregation, the inset depicts a zoomed-in subset and visualization of niche clustering on Leiden annotations and associated selected transcripts with random jitter. K-L) Tiling and pseudo-spatial data creation K) Schematic pictograms for different tiling options and tunable parameters. L) Spatial deconvolution plot showing the percentage of individual brain cell types for the pseudo-visium dataset generated from the stereo-seq subset in J.

Journal: bioRxiv

Article Title: Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem

doi: 10.1101/2023.11.26.568752

Figure Lengend Snippet: A-C) Multi-scale analysis. A) Pictogram depicting the hierarchy of multiple biological scales. B) Sankeyplot showing the hierarchical relationships between different spatial units in Giotto Suite. C) Overlay of multi-scale annotations of a MERFISH dataset; depicting nuclear (magenta) and cytoplasmic (cyan) enriched transcripts for all genes in GSEA terms related to “programmed cell death” and “COPII-coated ER to Golgi transport vesicle”, respectively. The nuclear boundary is defined with a yellow border, and the cell body is filled in with dark green. D-F) Registration and segmentation. D) Pictogram showing multi-modal co-registration from serial tissue sections. E) Aligned Xenium (Black), Visium (Orange), and immunofluorescence (Red and Green) spatial datasets from a single breast cancer sample (10X Genomics). F) Overlay of HER2 protein (rasterized intensity, blue gradient) and ERBB2 transcripts (points, red) after co-registration, inset shows zoomed-in region. G-H ) Multi-modal data analysis. G) Pictogram depicting multi-modal data analysis from two different modalities obtained from the same tissue slice. H) Integrated clustering results (RNA + Protein) from the 10X Genomics CytAassist Visium Human Tonsil dataset. I-L) Scalable data analysis. I) Pictograms depicting on-disk backends, parallelization, and projection to improve scalability within Giotto Suite. J) Stereo-seq datasets processed at bin1 and analyzed through multiple levels of hexagon aggregation, the inset depicts a zoomed-in subset and visualization of niche clustering on Leiden annotations and associated selected transcripts with random jitter. K-L) Tiling and pseudo-spatial data creation K) Schematic pictograms for different tiling options and tunable parameters. L) Spatial deconvolution plot showing the percentage of individual brain cell types for the pseudo-visium dataset generated from the stereo-seq subset in J.

Article Snippet: 10X Genomics Visium Mouse Brain Section (Coronal) dataset.

Techniques: Immunofluorescence, Generated

A ) A schematic workflow of the co-registration step for the 10X Genomics Xenium pre-release breast cancer dataset. B ) Rasterized CD20 intensity data (left) and rasterized MS4A1 transcript counts (right). Pearson’s r is shown. C ) Rasterized HER2 intensity data (left) and rasterized ERBB2 transcript counts (right). Pearson’s r is shown. Rank of correlation scores between overlapping genes expressed in Visium and registered Xenium data. D) LOESS regression (solid curves) of log expression against ranked correlation scores from (D) . F-G ) Spatial feature expression plots for registered Xenium and Visium data for genes FASN ( F ) and HDC ( G ).

Journal: bioRxiv

Article Title: Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem

doi: 10.1101/2023.11.26.568752

Figure Lengend Snippet: A ) A schematic workflow of the co-registration step for the 10X Genomics Xenium pre-release breast cancer dataset. B ) Rasterized CD20 intensity data (left) and rasterized MS4A1 transcript counts (right). Pearson’s r is shown. C ) Rasterized HER2 intensity data (left) and rasterized ERBB2 transcript counts (right). Pearson’s r is shown. Rank of correlation scores between overlapping genes expressed in Visium and registered Xenium data. D) LOESS regression (solid curves) of log expression against ranked correlation scores from (D) . F-G ) Spatial feature expression plots for registered Xenium and Visium data for genes FASN ( F ) and HDC ( G ).

Article Snippet: 10X Genomics Visium Mouse Brain Section (Coronal) dataset.

Techniques: Expressing