10x visium data of mouse brain cortex (ffpe) (10X Genomics)

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10X Genomics 10x visium data of mouse brain cortex (ffpe)

De-spot identified similar cell-type-specific domains in multiple mouse brain slices (A) Free frozen tissue (slice 1) and <t>FFPE</t> tissue (slice 2). Annotations of anatomic mouse brain structure are from the Allen Brain Atlas. (B) Previously published single-cell profiles, including seven annotated cell types: astrocytes-ependymal, endothelial-mural, interneurons, microglia, oligodendrocytes, pyramidal CA1, and pyramidal SS. (C) 3D Landscapes of slice 1 and slice 2 generated by Giotto. The color of each domain corresponds to the cell types with the same color in (B). (D) 3D Landscapes of slice 1 and slice 2 generated by Seurat. (E) 3D Landscapes of slice 1 and slice 2 generated by CARD. (F) 3D Landscapes of slice 1 generated by De-spot. (G) 3D Landscapes of slice 2 generated by De-spot. (H) F1 score comparison of cell-type-specific domains in slice 1 (bars indicate mean ± SEM). If a method failed to find the cell-type-specific domains of a certain cell, the F1 score bar of this method for the certain cell would not display (e.g., Giotto failed to detect pyramidal SS-specific domain in slice 1, so the F1 score bar of Giotto for pyramidal SS did not display). (I) F1 score comparison of cell-type-specific domains in slice 2 (bars indicate mean ± SEM). (J and K) Cell-type-specific domains of pyramidal CA1, pyramidal SS, interneurons, oligodendrocytes, and the expression of their corresponding upregulated genes ( Wipf3 , Mef2c , Nap1l5 , and Mbp ) in slice 1 (J) and slice 2 (K). The detected cell-type-specific domains are outlined in red contours. (L) Expressions of Wipf3 , Mef2c , Nap1l5 , and Mbp in single-cell profiles.

10x Visium Data Of Mouse Brain Cortex (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 visium data of mouse brain cortex (ffpe) - by Bioz Stars, 2026-10

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1) Product Images from "Precise detection of cell-type-specific domains in spatial transcriptomics"

Article Title: Precise detection of cell-type-specific domains in spatial transcriptomics

Journal: Cell Reports Methods

doi: 10.1016/j.crmeth.2024.100841

De-spot identified similar cell-type-specific domains in multiple mouse brain slices (A) Free frozen tissue (slice 1) and FFPE tissue (slice 2). Annotations of anatomic mouse brain structure are from the Allen Brain Atlas. (B) Previously published single-cell profiles, including seven annotated cell types: astrocytes-ependymal, endothelial-mural, interneurons, microglia, oligodendrocytes, pyramidal CA1, and pyramidal SS. (C) 3D Landscapes of slice 1 and slice 2 generated by Giotto. The color of each domain corresponds to the cell types with the same color in (B). (D) 3D Landscapes of slice 1 and slice 2 generated by Seurat. (E) 3D Landscapes of slice 1 and slice 2 generated by CARD. (F) 3D Landscapes of slice 1 generated by De-spot. (G) 3D Landscapes of slice 2 generated by De-spot. (H) F1 score comparison of cell-type-specific domains in slice 1 (bars indicate mean ± SEM). If a method failed to find the cell-type-specific domains of a certain cell, the F1 score bar of this method for the certain cell would not display (e.g., Giotto failed to detect pyramidal SS-specific domain in slice 1, so the F1 score bar of Giotto for pyramidal SS did not display). (I) F1 score comparison of cell-type-specific domains in slice 2 (bars indicate mean ± SEM). (J and K) Cell-type-specific domains of pyramidal CA1, pyramidal SS, interneurons, oligodendrocytes, and the expression of their corresponding upregulated genes ( Wipf3 , Mef2c , Nap1l5 , and Mbp ) in slice 1 (J) and slice 2 (K). The detected cell-type-specific domains are outlined in red contours. (L) Expressions of Wipf3 , Mef2c , Nap1l5 , and Mbp in single-cell profiles.

Figure Legend Snippet: De-spot identified similar cell-type-specific domains in multiple mouse brain slices (A) Free frozen tissue (slice 1) and FFPE tissue (slice 2). Annotations of anatomic mouse brain structure are from the Allen Brain Atlas. (B) Previously published single-cell profiles, including seven annotated cell types: astrocytes-ependymal, endothelial-mural, interneurons, microglia, oligodendrocytes, pyramidal CA1, and pyramidal SS. (C) 3D Landscapes of slice 1 and slice 2 generated by Giotto. The color of each domain corresponds to the cell types with the same color in (B). (D) 3D Landscapes of slice 1 and slice 2 generated by Seurat. (E) 3D Landscapes of slice 1 and slice 2 generated by CARD. (F) 3D Landscapes of slice 1 generated by De-spot. (G) 3D Landscapes of slice 2 generated by De-spot. (H) F1 score comparison of cell-type-specific domains in slice 1 (bars indicate mean ± SEM). If a method failed to find the cell-type-specific domains of a certain cell, the F1 score bar of this method for the certain cell would not display (e.g., Giotto failed to detect pyramidal SS-specific domain in slice 1, so the F1 score bar of Giotto for pyramidal SS did not display). (I) F1 score comparison of cell-type-specific domains in slice 2 (bars indicate mean ± SEM). (J and K) Cell-type-specific domains of pyramidal CA1, pyramidal SS, interneurons, oligodendrocytes, and the expression of their corresponding upregulated genes ( Wipf3 , Mef2c , Nap1l5 , and Mbp ) in slice 1 (J) and slice 2 (K). The detected cell-type-specific domains are outlined in red contours. (L) Expressions of Wipf3 , Mef2c , Nap1l5 , and Mbp in single-cell profiles.

Techniques Used: Generated, Comparison, Expressing

De-spot detected co-localized cell-type-specific domains using multiple profiles (A) FFPE tissue of the mouse kidney. The slice is histologically annotated to the renal cortex, renal medulla 1, renal medulla 2, and pelvis. (B) Previously published mouse kidney profiles generated by scRNA-seq and small nuclear RNA sequencing, containing 13 cell types annotated by Wu et al. CD-PC, collecting duct principal cells; CNT, connecting tubule; DCT, distal convoluted tubules; EC, endothelial cells; IC, intercalated cells; LHAL, the loop of Henle ascending loop; LHDL, the loop of Henle descending loop; MC, mesangial cells; MØ, macrophages; PT, proximal tubules; Pod, podocytes. (C) Correlation heatmap of pairwise cell type proportion between single-nucleus profiles (rows) and single-cell profiles (columns). Non-significant correlations ( p < 0.05) are shown in gray; the color bar indicates Pearson’s r values; the Pearson’s r values among cell types greater than zero are marked in elements of the heatmap. (D) 3D Landscapes of cell-type-specific domains generated by Giotto according to single-cell and single-nucleus profiles. The color of each domain corresponds to the color of cell types in (B). (E) 3D Landscapes of cell-type-specific domains generated by Seurat. (F) 3D Landscapes of cell-type-specific domains generated by CARD. (G) 3D Landscapes of cell-type-specific domains generated by De-spot using single-cell profiles. (H) 3D Landscapes of cell-type-specific domains generated by De-spot using single-nucleus profiles. (I) F1 score comparison of the cell-type-specific domains when using single-cell profiles (bars indicate mean ± SEM). (J) F1 score comparison of the cell-type-specific domains when using single-nucleus profiles (bars indicate mean ± SEM). (K) Proportions of De-spot’s seven common cell types: CD-PC, CNT, DCT, LHAL, LHDL, PT(S1–S2), and PT(S3) and their corresponding upregulated genes.

Figure Legend Snippet: De-spot detected co-localized cell-type-specific domains using multiple profiles (A) FFPE tissue of the mouse kidney. The slice is histologically annotated to the renal cortex, renal medulla 1, renal medulla 2, and pelvis. (B) Previously published mouse kidney profiles generated by scRNA-seq and small nuclear RNA sequencing, containing 13 cell types annotated by Wu et al. CD-PC, collecting duct principal cells; CNT, connecting tubule; DCT, distal convoluted tubules; EC, endothelial cells; IC, intercalated cells; LHAL, the loop of Henle ascending loop; LHDL, the loop of Henle descending loop; MC, mesangial cells; MØ, macrophages; PT, proximal tubules; Pod, podocytes. (C) Correlation heatmap of pairwise cell type proportion between single-nucleus profiles (rows) and single-cell profiles (columns). Non-significant correlations ( p < 0.05) are shown in gray; the color bar indicates Pearson’s r values; the Pearson’s r values among cell types greater than zero are marked in elements of the heatmap. (D) 3D Landscapes of cell-type-specific domains generated by Giotto according to single-cell and single-nucleus profiles. The color of each domain corresponds to the color of cell types in (B). (E) 3D Landscapes of cell-type-specific domains generated by Seurat. (F) 3D Landscapes of cell-type-specific domains generated by CARD. (G) 3D Landscapes of cell-type-specific domains generated by De-spot using single-cell profiles. (H) 3D Landscapes of cell-type-specific domains generated by De-spot using single-nucleus profiles. (I) F1 score comparison of the cell-type-specific domains when using single-cell profiles (bars indicate mean ± SEM). (J) F1 score comparison of the cell-type-specific domains when using single-nucleus profiles (bars indicate mean ± SEM). (K) Proportions of De-spot’s seven common cell types: CD-PC, CNT, DCT, LHAL, LHDL, PT(S1–S2), and PT(S3) and their corresponding upregulated genes.

Techniques Used: Generated, RNA Sequencing, Comparison

Figure Legend Snippet:

Techniques Used: Software

Formalin-fixed Paraffin-Embedded:

Article Title: Precise detection of cell-type-specific domains in spatial transcriptomics.
Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Deposited data scRNA-seq data of mouse brain cortex Zeisel et al.39 GEO: GSE60361 10x Visium data of mouse brain cortex (free frozen) 10x Genomics https://www.10xgenomics.com/resources/ datasets/mouse-brain-section-coronal-1standard-1-0-0 10x Visium data of mouse brain cortex (FFPE) 10x Genomics https://www.10xgenomics.com/resources/ datasets/adult-mouse-brain-ffpe-1standard-1-3-0 scRNA-seq data of mouse kidney Wu et al.47 GEO: GSE119531 SRT data of mouse kidney (FFPE) 10x Genomics https://www.10xgenomics.com/resources/ datasets/adult-mouse-kidney-ffpe-1standard-1-3-0 ST and paired scRNA-seq data of PDAC Moncada et al.30 GEO: GSE111672 MERFISH data of mouse brain cortex Zhuang et al.68 https://cellxgene.cziscience.com/ collections/31937775-06024e52-a799b6acdd2bac2e Stereo-seq data of mouse brain cortex STOmicsDB70 https://db.cngb.org/stomics/datasets/ STDS0000234 10x Visium data of human breast cancer Wu et al.58 GEO: GSE176078 Software and algorithms R (v4.1.3) R Core Team https://www.r-project.org/ Python (v3.9.7) Python Software Foundation https://www.python.org/ CARD (v1.0) Ma et al.31 https://github.com/YMa-lab/CARD Seurat (v4.3.0) Butler et al.24 https://satijalab.org/seurat Giotto (v1.1.0) Dries et al.25 https://github.com/RubD/Giotto/ Squidpy (v1.2.2) Palla et al.26 https://squidpy.readthedocs.io/en/stable/ Scanpy (v1.9.1) Wolf et al.27 https://scanpy.readthedocs.io/en/stable/ Cell2Location (v0.1) Kleshchevnikov et al.16 https://github.com/BayraktarLab/ cell2location Stlearn (v0.4.6) Pham et al.14 https://github.com/ BiomedicalMachineLearning/stLearn SpaGCN (v1.2.2) Hu et al.12 https://github.com/jianhuupenn/SpaGCN BayesSpace (v1.4.1) Zhao et al.11 https://github.com/edward130603/ BayesSpace SEDR (v1.0.0) Fu et al.13 https://github.com/JinmiaoChenLab/SEDR MENDER (v1.1) Yuan25 https://github.com/yuanzhiyuan/MENDER BASS (v1.1.0.016) Li and Zhou24 https://github.com/zhengli09/BASS SPOTlight (v0.99.8) Elosua-Bayes et al.19 https://github.com/MarcElosua/SPOTlight StereoScope (v0.3) Andersson et al.18 https://github.com/almaan/stereoscope RCTD (v2.0.0) Cable et al.17 https://github.com/dmcable/spacexr SPROD (v1.0) Wang et al.34 https://github.com/yunguan-wang/SPROD SPCS (inline) Liu et al.36 https://github.com/Usos/SPCS SpotClean (v0.99.2) Ni et al.33 https://github.com/zijianni/SpotClean SCDD (v1.0.0) Liu et al.35 https://github.com/lyotvincent/SCDD Matplotlib (v3.5.1) Matplotlib development team https://matplotlib.org De-spot (v1.0.0) This paper https://zenodo.org/doi/10.5281/zenodo. ..

Software:

other:

Article Title: WEST is an ensemble method for spatial transcriptomics analysis
Article Snippet: 10X Genomics Visium data of human dorsolateral prefrontal cortex , Maynard et al. , http://research.libd.org/spatialLIBD/.

Article Title: Precise detection of cell-type-specific domains in spatial transcriptomics
Article Snippet: 10x Visium data of mouse brain cortex (FFPE) , 10x Genomics , https://www.10xgenomics.com/resources/datasets/adult-mouse-brain-ffpe-1-standard-1-3-0.

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