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10X Genomics mouse brain visium hd dataset
Overview of the SpNeigh workflow. ( a ) Input includes a spatial coordinate data frame ( x, y , cell, cluster) and a normalized expression matrix. Data can originate from platforms such as Xenium, <t>Visium</t> <t>HD,</t> MERFISH, or others. ( b ) Spatial boundary detection and neighborhood extraction. Left: Cluster boundaries are identified after removing spatial outliers based on local k-nearest neighbor density. Right: Ring regions are constructed by buffering outward from the cluster boundaries. Black lines denote cluster boundaries; blue lines indicate outer ring boundaries. ( c ) Spatial weight computation. Cells are assigned weights based on their distance to either the boundary (left) or the centroid (right) of the cluster using inverse distance decay. Weights range from 0 (far) to 1 (close), reflecting proximity. ( d ) Neighborhood composition and interaction analysis. Top: Pie chart showing the proportion of neighboring cell types within the rings. Bottom: Heatmap of spatial interaction scores between focal and neighboring clusters. ( e ) Downstream analyses enabled by SpNeigh. Left: Differential expression analysis between cells of the same cluster in the inner region versus the ring. Middle: Spatial differential expression analysis using smooth functions of distance-based weights. Right: Spatial enrichment analysis quantifying expression bias relative to spatial proximity.
Mouse Brain Visium Hd Dataset, 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
https://www.bioz.com/result/mouse brain visium hd dataset/product/10X Genomics
Average 86 stars, based on 1 article reviews
mouse brain visium hd dataset - by Bioz Stars, 2026-05
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86
10X Genomics mouse embryo visium hd dataset
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Mouse Embryo Visium Hd Dataset, 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
https://www.bioz.com/result/mouse embryo visium hd dataset/product/10X Genomics
Average 86 stars, based on 1 article reviews
mouse embryo visium hd dataset - by Bioz Stars, 2026-05
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86
10X Genomics ovarian cancer visium hd dataset
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Ovarian Cancer Visium Hd Dataset, 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
https://www.bioz.com/result/ovarian cancer visium hd dataset/product/10X Genomics
Average 86 stars, based on 1 article reviews
ovarian cancer visium hd dataset - by Bioz Stars, 2026-05
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86
10X Genomics visium hd
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Visium Hd, 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
https://www.bioz.com/result/visium hd/product/10X Genomics
Average 86 stars, based on 1 article reviews
visium hd - by Bioz Stars, 2026-05
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86
10X Genomics visium hd platform
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Visium Hd Platform, 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
https://www.bioz.com/result/visium hd platform/product/10X Genomics
Average 86 stars, based on 1 article reviews
visium hd platform - by Bioz Stars, 2026-05
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86
10X Genomics ovarian cancer visium hd ataset
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Ovarian Cancer Visium Hd Ataset, 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
https://www.bioz.com/result/ovarian cancer visium hd ataset/product/10X Genomics
Average 86 stars, based on 1 article reviews
ovarian cancer visium hd ataset - by Bioz Stars, 2026-05
86/100 stars
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86
10X Genomics mouse embryo visium hd ataset
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Mouse Embryo Visium Hd Ataset, 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
https://www.bioz.com/result/mouse embryo visium hd ataset/product/10X Genomics
Average 86 stars, based on 1 article reviews
mouse embryo visium hd ataset - by Bioz Stars, 2026-05
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86
10X Genomics space ranger aligned visium hd data
Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated <t>Visium</t> <t>HD-like</t> and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.
Space Ranger Aligned Visium Hd Data, 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
https://www.bioz.com/result/space ranger aligned visium hd data/product/10X Genomics
Average 86 stars, based on 1 article reviews
space ranger aligned visium hd data - by Bioz Stars, 2026-05
86/100 stars
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86
10X Genomics visium hd mouse brain dataset
(a) sST: <t>Visium</t> <t>HD</t> mouse brain, grid expression over H&E. (b) iST: Xenium human breast cancer; DAPI/IF morphology (left) and cluster-colored centroids (right). (c) SP: CODEX human intestine with protein-defined clusters. (d) scRNA-seq: honey bee brain, 3D UMAP. (e, f) Lasso-defined inner (e) and large (f) Kenyon cell (KC) ROIs (left); linked embedding confirms molecular coherence (right). (g) Differential expression between inner and large KCs (left: Dop3 -colored spatial view; right: DEG heatmap). (h) Spatially varying gene CHIT1 expression: whole tissue (left), ROI1 (middle), ROI2 (right). (i) Same layout as h, CD83 . (j) Spatially resolved ROI1 cell-type clusters (left) and TAMs (cluster 11) sub-clusters (right). (k) Spatially resolved ROI2 cell-type clusters. (l) Cell type composition of ROI1 and ROI2. (m) Volcano of ROI1-core-specific TAMs (11.1) vs other TAMs (11.0 and 11.2).
Visium Hd Mouse Brain Dataset, 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
https://www.bioz.com/result/visium hd mouse brain dataset/product/10X Genomics
Average 86 stars, based on 1 article reviews
visium hd mouse brain dataset - by Bioz Stars, 2026-05
86/100 stars
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Overview of the SpNeigh workflow. ( a ) Input includes a spatial coordinate data frame ( x, y , cell, cluster) and a normalized expression matrix. Data can originate from platforms such as Xenium, Visium HD, MERFISH, or others. ( b ) Spatial boundary detection and neighborhood extraction. Left: Cluster boundaries are identified after removing spatial outliers based on local k-nearest neighbor density. Right: Ring regions are constructed by buffering outward from the cluster boundaries. Black lines denote cluster boundaries; blue lines indicate outer ring boundaries. ( c ) Spatial weight computation. Cells are assigned weights based on their distance to either the boundary (left) or the centroid (right) of the cluster using inverse distance decay. Weights range from 0 (far) to 1 (close), reflecting proximity. ( d ) Neighborhood composition and interaction analysis. Top: Pie chart showing the proportion of neighboring cell types within the rings. Bottom: Heatmap of spatial interaction scores between focal and neighboring clusters. ( e ) Downstream analyses enabled by SpNeigh. Left: Differential expression analysis between cells of the same cluster in the inner region versus the ring. Middle: Spatial differential expression analysis using smooth functions of distance-based weights. Right: Spatial enrichment analysis quantifying expression bias relative to spatial proximity.

Journal: NAR Genomics and Bioinformatics

Article Title: SpNeigh: spatial neighborhood and differential expression analysis for high-resolution spatial transcriptomics

doi: 10.1093/nargab/lqag039

Figure Lengend Snippet: Overview of the SpNeigh workflow. ( a ) Input includes a spatial coordinate data frame ( x, y , cell, cluster) and a normalized expression matrix. Data can originate from platforms such as Xenium, Visium HD, MERFISH, or others. ( b ) Spatial boundary detection and neighborhood extraction. Left: Cluster boundaries are identified after removing spatial outliers based on local k-nearest neighbor density. Right: Ring regions are constructed by buffering outward from the cluster boundaries. Black lines denote cluster boundaries; blue lines indicate outer ring boundaries. ( c ) Spatial weight computation. Cells are assigned weights based on their distance to either the boundary (left) or the centroid (right) of the cluster using inverse distance decay. Weights range from 0 (far) to 1 (close), reflecting proximity. ( d ) Neighborhood composition and interaction analysis. Top: Pie chart showing the proportion of neighboring cell types within the rings. Bottom: Heatmap of spatial interaction scores between focal and neighboring clusters. ( e ) Downstream analyses enabled by SpNeigh. Left: Differential expression analysis between cells of the same cluster in the inner region versus the ring. Middle: Spatial differential expression analysis using smooth functions of distance-based weights. Right: Spatial enrichment analysis quantifying expression bias relative to spatial proximity.

Article Snippet: Mouse brain Visium HD dataset: https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-mouse-brain-fresh-frozen .

Techniques: Expressing, Extraction, Construct, Quantitative Proteomics

Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated Visium HD-like and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.

Journal: Nucleic Acids Research

Article Title: Benchmarking sketching methods on spatial transcriptomics data

doi: 10.1093/nar/gkag434

Figure Lengend Snippet: Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated Visium HD-like and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.

Article Snippet: Mouse embryo: We downloaded the whole mouse embryo Visium HD dataset from the publicly available datasets on the 10x website https://www.10xgenomics.com/datasets/visium-hd-three-prime-mouse-embryo-fresh-frozen (last accessed date: 12 February 2025).

Techniques: Sampling

Retained cell type/cluster label proportions at 0.10 sketching fraction for ( A ) Merfish mouse ovary; ( B ) Merfish sagittal mouse brain; ( C ) Xenium human breast cancer; ( D ) Xenium human lung; ( E ) Xenium whole mouse pup; ( F ) Visium HD coronal mouse brain; ( G ) Visium HD mouse embryo; ( H ) Visium HD ovarian cancer.

Journal: Nucleic Acids Research

Article Title: Benchmarking sketching methods on spatial transcriptomics data

doi: 10.1093/nar/gkag434

Figure Lengend Snippet: Retained cell type/cluster label proportions at 0.10 sketching fraction for ( A ) Merfish mouse ovary; ( B ) Merfish sagittal mouse brain; ( C ) Xenium human breast cancer; ( D ) Xenium human lung; ( E ) Xenium whole mouse pup; ( F ) Visium HD coronal mouse brain; ( G ) Visium HD mouse embryo; ( H ) Visium HD ovarian cancer.

Article Snippet: Mouse embryo: We downloaded the whole mouse embryo Visium HD dataset from the publicly available datasets on the 10x website https://www.10xgenomics.com/datasets/visium-hd-three-prime-mouse-embryo-fresh-frozen (last accessed date: 12 February 2025).

Techniques:

Quantification of transcriptomic and coordinate Hausdorff distance at 0.10 sampling fraction for real datasets. ( A ) Quantification of imaging based (Merfish, Xenium) dataset’s Hausdorff distances. ( B ) Quntification of sequencing/spot based (Visium HD) dataset’s Hausdorff distances. Each boxplot represents one sketching method, with individual points corresponding to results from 10 independent runs with different random seeds.

Journal: Nucleic Acids Research

Article Title: Benchmarking sketching methods on spatial transcriptomics data

doi: 10.1093/nar/gkag434

Figure Lengend Snippet: Quantification of transcriptomic and coordinate Hausdorff distance at 0.10 sampling fraction for real datasets. ( A ) Quantification of imaging based (Merfish, Xenium) dataset’s Hausdorff distances. ( B ) Quntification of sequencing/spot based (Visium HD) dataset’s Hausdorff distances. Each boxplot represents one sketching method, with individual points corresponding to results from 10 independent runs with different random seeds.

Article Snippet: Mouse embryo: We downloaded the whole mouse embryo Visium HD dataset from the publicly available datasets on the 10x website https://www.10xgenomics.com/datasets/visium-hd-three-prime-mouse-embryo-fresh-frozen (last accessed date: 12 February 2025).

Techniques: Sampling, Imaging, Sequencing

Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated Visium HD-like and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.

Journal: Nucleic Acids Research

Article Title: Benchmarking sketching methods on spatial transcriptomics data

doi: 10.1093/nar/gkag434

Figure Lengend Snippet: Overall sketching performance for 0.10 sampling fraction across datasets. ( A ) Spatial scatter plots of real datasets colored by cell type or cluster label. ( B ) Heatmap of rank-sums for each method aggregated by metric across all real world datasets. Low rank indicates best performance for that metric. ( C ) Spatial scatter plots of simulated Visium HD-like and Xenium like datasets. ( D ) Heatmap of rank-sums for each method aggregated by metric across all simulated datasets. Low rank indicates best performance for that metric.

Article Snippet: Human ovarian cancer: We downloaded the human ovarian cancer Visium HD dataset from the publicly avaiable datasets on the 10x website https://www.10xgenomics.com/datasets/visium-hd-three-prime-ovarian-cancer-discovery-fresh-frozen (last accessed date: 12 February 2025).

Techniques: Sampling

Retained cell type/cluster label proportions at 0.10 sketching fraction for ( A ) Merfish mouse ovary; ( B ) Merfish sagittal mouse brain; ( C ) Xenium human breast cancer; ( D ) Xenium human lung; ( E ) Xenium whole mouse pup; ( F ) Visium HD coronal mouse brain; ( G ) Visium HD mouse embryo; ( H ) Visium HD ovarian cancer.

Journal: Nucleic Acids Research

Article Title: Benchmarking sketching methods on spatial transcriptomics data

doi: 10.1093/nar/gkag434

Figure Lengend Snippet: Retained cell type/cluster label proportions at 0.10 sketching fraction for ( A ) Merfish mouse ovary; ( B ) Merfish sagittal mouse brain; ( C ) Xenium human breast cancer; ( D ) Xenium human lung; ( E ) Xenium whole mouse pup; ( F ) Visium HD coronal mouse brain; ( G ) Visium HD mouse embryo; ( H ) Visium HD ovarian cancer.

Article Snippet: Human ovarian cancer: We downloaded the human ovarian cancer Visium HD dataset from the publicly avaiable datasets on the 10x website https://www.10xgenomics.com/datasets/visium-hd-three-prime-ovarian-cancer-discovery-fresh-frozen (last accessed date: 12 February 2025).

Techniques:

Quantification of transcriptomic and coordinate Hausdorff distance at 0.10 sampling fraction for real datasets. ( A ) Quantification of imaging based (Merfish, Xenium) dataset’s Hausdorff distances. ( B ) Quntification of sequencing/spot based (Visium HD) dataset’s Hausdorff distances. Each boxplot represents one sketching method, with individual points corresponding to results from 10 independent runs with different random seeds.

Journal: Nucleic Acids Research

Article Title: Benchmarking sketching methods on spatial transcriptomics data

doi: 10.1093/nar/gkag434

Figure Lengend Snippet: Quantification of transcriptomic and coordinate Hausdorff distance at 0.10 sampling fraction for real datasets. ( A ) Quantification of imaging based (Merfish, Xenium) dataset’s Hausdorff distances. ( B ) Quntification of sequencing/spot based (Visium HD) dataset’s Hausdorff distances. Each boxplot represents one sketching method, with individual points corresponding to results from 10 independent runs with different random seeds.

Article Snippet: Human ovarian cancer: We downloaded the human ovarian cancer Visium HD dataset from the publicly avaiable datasets on the 10x website https://www.10xgenomics.com/datasets/visium-hd-three-prime-ovarian-cancer-discovery-fresh-frozen (last accessed date: 12 February 2025).

Techniques: Sampling, Imaging, Sequencing

(a) sST: Visium HD mouse brain, grid expression over H&E. (b) iST: Xenium human breast cancer; DAPI/IF morphology (left) and cluster-colored centroids (right). (c) SP: CODEX human intestine with protein-defined clusters. (d) scRNA-seq: honey bee brain, 3D UMAP. (e, f) Lasso-defined inner (e) and large (f) Kenyon cell (KC) ROIs (left); linked embedding confirms molecular coherence (right). (g) Differential expression between inner and large KCs (left: Dop3 -colored spatial view; right: DEG heatmap). (h) Spatially varying gene CHIT1 expression: whole tissue (left), ROI1 (middle), ROI2 (right). (i) Same layout as h, CD83 . (j) Spatially resolved ROI1 cell-type clusters (left) and TAMs (cluster 11) sub-clusters (right). (k) Spatially resolved ROI2 cell-type clusters. (l) Cell type composition of ROI1 and ROI2. (m) Volcano of ROI1-core-specific TAMs (11.1) vs other TAMs (11.0 and 11.2).

Journal: bioRxiv

Article Title: MilliMap: interactive closed-loop analysis for spatial omics

doi: 10.64898/2026.05.01.722104

Figure Lengend Snippet: (a) sST: Visium HD mouse brain, grid expression over H&E. (b) iST: Xenium human breast cancer; DAPI/IF morphology (left) and cluster-colored centroids (right). (c) SP: CODEX human intestine with protein-defined clusters. (d) scRNA-seq: honey bee brain, 3D UMAP. (e, f) Lasso-defined inner (e) and large (f) Kenyon cell (KC) ROIs (left); linked embedding confirms molecular coherence (right). (g) Differential expression between inner and large KCs (left: Dop3 -colored spatial view; right: DEG heatmap). (h) Spatially varying gene CHIT1 expression: whole tissue (left), ROI1 (middle), ROI2 (right). (i) Same layout as h, CD83 . (j) Spatially resolved ROI1 cell-type clusters (left) and TAMs (cluster 11) sub-clusters (right). (k) Spatially resolved ROI2 cell-type clusters. (l) Cell type composition of ROI1 and ROI2. (m) Volcano of ROI1-core-specific TAMs (11.1) vs other TAMs (11.0 and 11.2).

Article Snippet: The Visium HD Mouse Brain dataset (FFPE; C57BL/6; Space Ranger v3.0.0) is available from 10x Genomics at https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-libraries-of-mouse-brain-he , licensed under CC BY 4.0.

Techniques: Expressing, Quantitative Proteomics