mouse brain sagittal posterior visium data  (10X Genomics)

Journal: Nature Communications

Article Title: Reconstructing single-cell resolution from spatial transcriptomics with CellRefiner

doi: 10.1038/s41467-026-70090-2

Figure Lengend Snippet: a Visium ST data from a slice of the mouse cortex. b The distribution of annotated cell types from the scRNA-seq data on the CellRefiner output. c Segmentation of CellRefiner reconstruction of mouse cortex Visium data, using SpaceFlow, with colors corresponding to clusters. d Ripley’s L for spatial organization on Visium and CellRefiner. e Neighborhood enrichment score on spatial proximity of clusters for CellRefiner output. f ST data from murine lymph node using Visium. Source data are provided as a Source Data file.

Article Snippet: The mouse brain (sagittal posterior) Visium data is available at the 10X Genomics website ( https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-1-sagittal-anterior-1-standard-1-1-0 ).

Techniques:

Journal: Nature Communications

Article Title: Reconstructing single-cell resolution from spatial transcriptomics with CellRefiner

doi: 10.1038/s41467-026-70090-2

Figure Lengend Snippet: a The single-cell resolution spatial map of cells reconstructed by CellRefiner using a paired Visium data and scRNA-seq data. The analysis rediscovered several contact-based signaling activities confirmed by prior knowledge, including EPHB, NOTCH, ICAM, and CDH. b CellRefiner also identified several highly active junction-related signaling including EPHA, MPZ, CD39, CD46, DESMOSOME, and JAM. Source data are provided as a Source Data file.

Article Snippet: The mouse brain (sagittal posterior) Visium data is available at the 10X Genomics website ( https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-1-sagittal-anterior-1-standard-1-1-0 ).

Techniques: Single Cell

Journal: Nature Cell Biology

Article Title: The interpretable multimodal dimension reduction framework SpaHDmap enhances resolution in spatial transcriptomics

doi: 10.1038/s41556-025-01838-z

Figure Lengend Snippet: a . A Xenium ST data from human breast carcinoma with single-cell level gene expression of 313 genes in 167,780 cells and an H&E image. Standard NMF is applied to derive a single-cell level embedding as the silver standard high-resolution embedding in the simulation. b . Generation of spots and spot-level gene expression. Spots of radius r are first generated based on a 10x Visium-style mesh grid, and spot-level gene expression is generated by summing cell expressions within spots. A proportion ρ of the spots are randomly excluded to increase the spatial sparsity. c . Error bar plots of MAEs between the silver standard and inferred embedding intensities at the pixel-wise level when varying the exclusion rate and radius of spots with n = 30 (replicates). Error bars: mean ± SD. d . Left panel: a tumour-associated embedding dimension in the single-cell level silver standard. Right panel: Zoomed-in views of three ROIs in the left panel. e . Zoomed-in views of the inferred embedding dimensions by different methods from a simulation dataset (spot radius: 30 pixels) in the ROIs under whole-spots and spots-masking scenarios. The whole-spots scenario means that expressions of all spots of the simulation dataset are used for embedding learning, and the spots-masking scenario means that the ST expressions in the light blue boxes are masked for embedding learning. Scale bars: 200 μm.

Article Snippet: 10x Visium mouse posterior brain sagittal section data are available for MPBS-01 at https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-1-sagittal-posterior-1-standard-1-1-0 and for MPBS-02 at https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-2-sagittal-posterior-1-standard-1-1-0 .

Techniques: Single Cell, Gene Expression, Generated