spatial transcriptomics visium data  (Spatial Transcriptomics Inc)

Journal: Cell Reports Medicine

Article Title: Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

doi: 10.1016/j.xcrm.2025.102188

Figure Lengend Snippet: EAC primary and metastatic samples show a diverse landscape of TME and malignant cells in transcriptomic and epigenetic data (A) Schematic representation of the study workflow. Biopsies from 10 patients in our discovery cohort, including normal adjacent tissue (NAT), primary tissue, and metastatic samples, were subjected to single-nuclei RNA and ATAC sequencing using 10X Chromium technology. For a subset of these patients as well as three additional patients, matched primary and metastatic samples were profiled with 10X Visium and 10X Xenium spatial transcriptomics (ST) technologies. For single-nuclei data, cells were annotated by cell type and categorized into malignant and TME components. TME subtypes were linked to metastasis, with validation against an external pan-cancer fibroblast atlas. The malignant cell components underwent analysis using consensus non-negative matrix factorization (cNMF) to uncover malignant programs, which were further characterized for transcriptional and epigenetic heterogeneity at a single-cell and spatial level and candidate master transcription factors. External validation was performed in two single-cell validation cohorts, , and associations with clinical and molecular characteristics, as well as survival, were assessed in three bulk validation cohorts. , , (B) Uniform manifold approximation and projection (UMAP) representation of the full cohort in Harmony-corrected integrated transcriptomic data, with major cell type compartments labeled and cell counts indicated. (C) Proportion of major cell types in each sample based on transcriptomic data, with percentages for compartments representing over 5% of the total sample composition. (D) UMAP representation of the full cohort in Harmony-corrected integrated ATAC data, with cell type annotations transferred from the RNA annotations. “NA” denotes cells without paired associated RNA information. (E) Proportion of major cell types in each sample based on ATAC data, with percentages for compartments representing over 5% of the total sample composition.

Article Snippet: Raw and processed spatial transcriptomics Visium data , This paper , Zenodo: 10.5281/zenodo.15341263.

Techniques: Sequencing, Biomarker Discovery, Labeling

Journal: Cell Reports Medicine

Article Title: Cell states and neighborhoods in distinct clinical stages of primary and metastatic esophageal adenocarcinoma

doi: 10.1016/j.xcrm.2025.102188

Figure Lengend Snippet: Single-nuclei-derived transcriptional programs highlight different spatial regions of EAC tumors (A) Spatial transcriptomics (ST) slides of P8 primary tumor A, colored according to cNMF program score and the CNV-derived label. For each spot, we infer the CNV profile with inferCNV and assign spots to tumor, mixed, and normal status. cNMF scores are computed as the average Z score of signature genes using the deconvolved carcinoma-specific gene expression profile of spots derived with Cell2Location. (B) Average cNMF score according to the position of the spots compared to the tumor-leading edge. For each tumor spot, we compute the distance to the edge as the shortest path to a normal or mixed spot. The distribution of cNMF scores with standard error is represented for normal spots, mixed spots, and spots of a certain distance to the edge. (C) cNMF scores for carcinoma cells and cell type annotations in a subset of Xenium-profiled samples (P4_A, P11_B, and P12_D). cNMF scores are computed as the average Z score across all carcinoma cells of signature genes included in the Xenium panel. (D) CellCharter cluster assignments for a subset of Xenium-profiled samples (P4_A, P11_B, and P12_D). (E) CellCharter cluster cell type proportion: each cell is assigned a cluster and we represent the proportion of the different cell types in each of the CellCharter clusters. (F) Distribution of cNMF scores of carcinoma cells belonging to the CellCharter clusters with a substantial amount of carcinoma cells (>5%), CC1, CC2, CC3, and CC4. For all comparisons, Mann-Whitney U p < 0.000005.

Article Snippet: Raw and processed spatial transcriptomics Visium data , This paper , Zenodo: 10.5281/zenodo.15341263.

Techniques: Derivative Assay, Gene Expression, MANN-WHITNEY

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Schema representation of STaCker. The workflow ( a ) takes as inputs the tissue images from a pair of reference and moving spatial transcriptome slices, combined with the contour maps generated upon the gene expression profiles from the respective slices. The resulting composite images are subsequently aligned through a deep neural network-based registration module. The registration module outputs the inferred deformation field to align the spatial coordinates of the spots/cells in the moving slice. The architecture of the registration module ( b ) takes a four-level contracting path and a four-level expanding path with skip connections at all levels. The final layer of the decoder is further convoluted to generate the spatial velocity field followed by a vector integration to output the deformation field for the alignment. Synthetic images with segmentation label maps (Methods) are used to train the module. The moved label map, after applying the deformation field to the moving label map, is compared to the reference label map. The difference constitutes the key component in the loss function.

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques: Generated, Gene Expression, Plasmid Preparation

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Evaluation of STaCker in aligning digitally warped spatial transcriptome slices of mouse brain. ( a ) The reference is a mouse sagittal posterior brain slice profiled by 10 × Genomics Visium platform. It was digitally warped using Simplex noises to a low (noise amplitude = 5, NCC of the deformed image = 0.61), medium (noise amplitude = 10, NCC of the deformed image = 0.57), or high (noise amplitude = 15, NCC of the deformed image = 0.54 level to generate a series of moving slices (noise frequency remains 1 for all warping). ( b ) The discordance between the spatial coordinates of the spots in each moving slice and those in the reference slice is quantified by the MSE (Methods) shown in the bar plots. STaCker, together with previously published methods STUtility, PASTE, and GPSA, was applied to align each of the moving spatial transcriptome slices to the reference. The spots’ coordinates before (blue crosses) or after the alignment (red crosses) are displayed together with the reference spot coordinates (gray dots) to aid the visual comparison. The post-alignment MSEs from each method are illustrated in the bar plots. Value from STaCker is the mean over five runs, shown together with the standard errors as error bars. STaCker’s MSE is significantly lower than that of all other programs (one sample t-test p -values < = 1e-3).

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques: Slice Preparation, Comparison

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Performance of STaCker in the de novo alignment of spatial transcriptome slices. The top row displays four moving spatial transcriptome slices that were independently warped from a reference slice taken from the mouse posterior brain used in Fig. , with the spot coordinates shown as crosses over the tissue images (slice 1: red, slice 2: green, slice 3: blue, slice 4: orange). The warping was conducted using random-seeded Simplex noises with an amplitude of 15 and a frequency of 1. The mean pairwise NCCs among the tissue images of the moving slices is 0.198. The average pairwise MSE among the spot coordinates in the moving slices is 0.10. The bottom row illustrates the spot coordinates from four slices before the alignment (“Unaligned coordinates”) and after the alignment by STaCker, STUtility, PASTE, GPSA, respectively, using the same colors and cross symbols as shown in the top row. The post-alignment average MSE over all six pairs of slices is 0.043, 0.119, 0.098, 0.601 for STaCker, STUtility, PASTE, and GPSA, respectively.

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques:

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Coordinate consolidation of real spatial transcriptome slices from a human dorsolateral prefrontal cortex (DLPFC). ( a ): Four serial dissections of the dorsolateral prefrontal cortex. ( b ): Superimposed spatial coordinates of the QC-validated tissue spots from four DLPFC slices before and after alignment by different methods, color-coded by their tissue domain annotations in the original publication. ( c - d ): Quantitative evaluation of tissue domain consistency across the four slices before and after alignment, using Spatial Coherence Score ( c ) and Mean Pairwise Adjusted Rand Index ( d ). STUtility does not offer de novo alignments so their values are averaged over four alignments, each using a different slice as the fixed template, with error bars marking the standard errors. ( e ): Spatial patterns of representative genes before and after alignment by STaCker and other programs. The displayed expression values are the natural logarithm transformation of the normalized UMI count (10 4 total UMI counts per spot). ( f ): Comparison of Moran’s I spatial autocorrelations of representative genes before and after alignment by various programs.

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques: Expressing, Transformation Assay, Comparison

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Coordinate consolidation of real spatial transcriptome slices from independent replicates of mouse olfactory bulbs. ( a ): Four biological replicates of dissected mouse olfactory bulbs. ( b ): Superimposed spatial coordinates of the QC-validated tissue spots from four slices before and after alignment by different methods, color-coded by the tissue domain annotations derived upon the transcriptome of the spots. ( c - d ): Quantitative evaluation of tissue domain consistency across the four slices before and after alignment, using Spatial Coherence Score ( c ) and Mean Pairwise Adjusted Rand Index ( d ). STUtility does not offer de novo alignments so their values are averaged over four alignments, each using a different slice as the fixed template. The standard errors are shown as error bars. ( e ): Spatial patterns of representative genes before and after alignment by STaCker and the other programs. The displayed expression is after the natural logarithm transformation of the normalized UMI count (10 4 total UMI counts per spot). ( f ): Comparison of Moran’s I spatial autocorrelations of representative genes before and after alignment by various programs.

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques: Derivative Assay, Expressing, Transformation Assay, Comparison

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Alignment of ISH-based spatial transcriptome slices. ( a ) MERFISH slices from three mouse brain samples, illustrated using the DAPI staining images. ( b ) Superimposed spatial coordinates of cells in the three slices before and after alignment by different methods. Cells are color-coded by their niches, defined based on the gene profiling of the cells (see Methods). ( c ) Quantitative evaluation of tissue domain consistency across the three slices before and after alignment, using Spatial Coherence Score and Mean Pairwise Adjusted Rand Index. STUtility and STalign do not offer de novo alignments so their values are averaged over three alignments each with a different slice as the fixed template, with standard errors shown as error bars. ( d ) Spatial patterns of four representative genes before and after alignment by STaCker, STUtility and STalign. The displayed expression is after the natural logarithm transformation of the normalized UMI count (10 4 total UMI counts per cell). ( e ) Comparison of Moran’s I autocorrelation (left panel) and Gene Coherence Score (right panel) of the four representative genes from the slices aligned by STaCker, STUtility or STalign. Values from STUtility and STalign are the average over three alignments each using a different slice as the fixed template, with standard errors shown as error bars. ( f ) Boxplots of the Moran’s I autocorrelation (left panel) and Gene Coherence Score (right panel) of all non-randomly distributed genes (Moran’s I p -value < = 0.01) over the slices aligned by STaCker, STUtility or STalign. The top and bottom edges of the box represent the 3rd and 1st quantiles, with the horizontal line inside denoting the median. The ends of the whisker mark the 1.5 times interquartile range, calculated as the difference between the 3rd and 1st quartiles, from the box edges. Data points beyond the whisker range are represented as dots. STalign was executed using the same parameters applied to the same MERFISH dataset in the original publication. ( g ) Comparison of the spatial coherence in gene expressions after the alignment by STaCker and STalign. Genes that show significantly higher Moran’s I correlation (left panel) or Gene Coherence Score (GCS, right panel) after alignment with STaCker are marked with orange dots, while genes with significantly elevated values for these metrics following STalign alignment are indicated by blue dots. The dashed line represents the significance cutoff (0.05) for the two-sided Student’s t-test p -value.

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques: Staining, Expressing, Transformation Assay, Comparison, Whisker Assay

Journal: Scientific Reports

Article Title: Image guided construction of a common coordinate framework for spatial transcriptome data

doi: 10.1038/s41598-025-01862-x

Figure Lengend Snippet: Alignment across different spatial transcriptome platforms. ( a ) Two mouse brain hemispheres profiled using 10 × Genomics Visium and Xenium, shown as the acquired H&E and DAPI images, respectively. ( b ) Superimposed spatial coordinates of spots (red circles, Visium slice) or cells (blue crosses, Xenium slice) before and after alignment by different methods. ( c ) Spatial patterns of the representative genes before and after alignment by STaCker, STUtility or STalign. The positions of the spots in the Visium slice (red) and the 55-micron × 55-micron pseudo-spots in the Xenium slice (blue) are displayed. At each spot or pseudo-spot, the expression of a gene is divided by the maximum expression of that gene on the slice, converting it to a value within 0 and 1. The scaled gene expressions are comparable across platforms and thus used for visualization and quantitative evaluation. ( d ) Moran’s I autocorrelation (upper panel) and the Gene Coherence Score (lower panel) of the representative genes from the slices aligned by STaCker, STUtility or STalign. Values for STUtility and STalign that do not offer de novo alignment are the average over alignments each using one of the slices as the reference, with the standard errors shown as error bars. ( e ) Boxplots of the Moran’s I autocorrelation score (upper panel) and the Gene Coherence Score (lower panel) of all non-randomly distributed genes (Moran’s I p -value < = 0.01) over the slices aligned by STaCker, STUtility or STalign. For both metrics, the mean of the distribution in STaCker is significantly higher than that in STalign (two-sided student t-test p -value < = 6e-5) and in STUtility (two-sided student t-test p -value < = 2e-3). In all boxplots, the top and bottom edges of the box represent the 3rd and 1st quantiles with the horizontal line inside to denote the median. The whiskers extend to 1.5 times the interquartile range (IQR), which is the difference between the 3rd and 1st quantiles, from the box edges. Data points outside the whisker range are displayed as dots. ( f ) Comparison of spatial coherence in gene expressions following alignment using STaCker and STalign. Genes exhibiting significantly higher Moran’s I correlation (left panel) or Gene Coherence Score (right panel) after alignment with STaCker are depicted with orange dots. Genes with significantly increased values for the two metrics after alignment with STalign are shown with blue dots. The dashed line indicates the significance cutoff (0.05) for the two-sided Student’s t-test p -value.

Article Snippet: The Visium spatial transcriptome data of a human lymph node sample were obtained from 10 × Genomics website [ https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_filtered_feature_bc_matrix.h5 ; https://cf.10xgenomics.com/samples/spatial-exp/1.1.0/V1_Human_Lymph_Node/V1_Human_Lymph_Node_spatial.tar.gz ].

Techniques: Expressing, Whisker Assay, Comparison