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: Nucleic Acids Research

Article Title: Microenvironment-aware spatial modeling for accurate inference of cell identity

doi: 10.1093/nar/gkaf1477

Figure Lengend Snippet: MEcell improves cell clustering in CosMx mouse brain data. ( A ) Clustering results of MEcell, BNAKSY, SPICEMIX, and Seurat, with cells colored by the cluster. ( B ) Pairwise ARI comparison among MEcell, BANKSY, SPICEMIX, and Seurat. ( C ) Anatomic structure in the hippocampus region. ( D ) MEcell successfully distinguished CA3 from CA1 regions, whereas BANKSY ( E ), SPICEMIX ( F ), and Seurat ( G ) failed to do so. ( H ) Heatmap showing genes differentially expressed among DG, CA1, and CA3 regions. ( I ) Prkcb is more highly expressed in the CA1 than in the CA3. ( J ) Kcnq5 is more highly expressed in CA3 than CA1. ( K ) Heatmap showing correlation between MEcell clusters and single-cell RNA-seq data from Habib et al. ( L ) Heatmap showing correlation between MEcell clusters and single-cell RNA-seq data from the mouse brain atlas.

Article Snippet: The Vizgen mouse brain data were downloaded from https://info.vizgen.com/mouse-brain-data .

Techniques: Comparison, RNA Sequencing

Journal: Nucleic Acids Research

Article Title: Microenvironment-aware spatial modeling for accurate inference of cell identity

doi: 10.1093/nar/gkaf1477

Figure Lengend Snippet: MEcell identifies cell types with different spatial patterns in Vizgen data. ( A ) Clustering results of MEcell, BNAKSY, SPICEMIX, and Seurat, with cells colored by the cluster. ( B ) Pairwise ARI comparisons among MEcell, BANKSY, SPICEMIX, and Seurat. ( C–F ) MEcell (C) and BANKSY (D) successfully distinguish DG, CA1, and CA3 regions with spatially continuous patterns, whereas SPICEMIX (E) and Seurat (F) fail to do so. ( G–P ) MEcell (G and L) and Seurat (J and O) identify VSMC and microglia cells with spatially scattered patterns, consistent with the averaged expression of top VSMC and microglia marker genes from scRNA-seq data (K and P). In contrast, BANKSY (H and M) and SPICEMIX (I and N) fail to recover these cell types. ( Q ) The VSMC and microglia clusters identified by MEcell highly express top marker genes from the scRNAseq data.

Article Snippet: The Vizgen mouse brain data were downloaded from https://info.vizgen.com/mouse-brain-data .

Techniques: Expressing, Marker

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

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 brain coronal section data are available for MBC-01 at https://www.10xgenomics.com/resources/datasets/adult-mouse-brain-section-2-coronal-stains-dapi-anti-gfap-anti-neu-n-1-standard-1-1-0 , for MBC-02 at https://www.10xgenomics.com/resources/datasets/adult-mouse-brain-section-1-coronal-stains-dapi-anti-neu-n-1-standard-1-1-0 and for MBC-03 at https://www.10xgenomics.com/resources/datasets/mouse-brain-section-coronal-1-standard-1-0-0 .

Techniques: Single Cell, Gene Expression, Generated