visium hd spatial transcriptomics  (Spatial Transcriptomics Inc)

Journal: bioRxiv

Article Title: fastCNV: Fast and accurate copy number variation prediction from High-Definition Spatial Transcriptomics and scRNA-Seq Data

doi: 10.1101/2025.10.22.683855

Figure Lengend Snippet:

Article Snippet: Notably, fastCNV enables, for the first time, the analysis of CNVs from the Visium HD spatial transcriptomics technology.

Techniques:

Journal: bioRxiv

Article Title: fastCNV: Fast and accurate copy number variation prediction from High-Definition Spatial Transcriptomics and scRNA-Seq Data

doi: 10.1101/2025.10.22.683855

Figure Lengend Snippet: Illustration of subclonal heterogeneity in Spatial Transcriptomics colon cancer data. Analysis of the SN048_A121573_Rep1 colon cancer Visium ST sample from Valdeolivas et al series. (a) H&E coloration of the tissue slide. (b) Spots of the Visium ST slide are colored according to the histological annotation (tumor: red, non-tumor: blue, immune cells: green). (c) Pangenomic heatmap showing the (spots x genomic regions) matrix of fastCNV denoised CNV scores, with spots ordered according to CNV clusters (1 to 3). The histological annotations per spot are given on the right. (d) Heatmap displaying discretized CNV events by chromosome arm (copy gain: red, copy loss: blue, diploid status: white) across CNV clusters after curation. (e) Phylogenetic tree based on CNV clusters 1 to 3. Branches are annotated using curated CNV events. Spots of the Visium ST slide are colored according to (f) CNV clusters (1: red, 2: green, 3: blue) and (g) pangenomic CNV fraction (low: white, high: blue).

Article Snippet: Notably, fastCNV enables, for the first time, the analysis of CNVs from the Visium HD spatial transcriptomics technology.

Techniques:

Journal: bioRxiv

Article Title: fastCNV: Fast and accurate copy number variation prediction from High-Definition Spatial Transcriptomics and scRNA-Seq Data

doi: 10.1101/2025.10.22.683855

Figure Lengend Snippet: Illustration of subclonal heterogenetity prior to CNV curation on colon cancer ST sample. Analysis of the SN048_A121573_Rep1 colon cancer Visium ST sample from Valdeolivas et al series. (a) Heatmap displaying discretized CNV events per chromosome arm (copy gain: red, copy loss: blue, diploid status: white) across CNV clusters (1 to 3) before curation. (b) Phylogenetic tree based on CNV clusters 1 to 3, with branches annotated using discretized chromosome arm level CNV events, before curation.

Article Snippet: Notably, fastCNV enables, for the first time, the analysis of CNVs from the Visium HD spatial transcriptomics technology.

Techniques:

Journal: bioRxiv

Article Title: fastCNV: Fast and accurate copy number variation prediction from High-Definition Spatial Transcriptomics and scRNA-Seq Data

doi: 10.1101/2025.10.22.683855

Figure Lengend Snippet: Illustration of subclonal heterogeneity in Visium HD Breast cancer data Analysis of the Visium_HD_FF_Human_Breast_Cancer Visium HD sample from the 10x Genomics database. (a) Spots of the Visium HD slide are colored according to tumor status (tumor: blue, non-tumor: pink). (b) Pangenomic heatmap showing the (spots x genomic regions) matrix of fastCNV denoised CNV scores, with spots ordered according to CNV clusters (1 to 6). The histological annotations per spot are given on the right. (c) Boxplots showing the pangenomic CNV fraction per CNV cluster. (d) Spots of the Visium HD slide are colored according to the CNV clusters (1 to 6). (e) H&E-stained slide, with contours focusing on regions related to distinct histologies. Spots of the Visium HD slide are colored according to (f) the pangenomic CNV fraction and (g) the CNV status for chromosome 11 arm q. (h) Phylogenetic tree based on CNV clusters 1 to 6. Branches are annotated using curated CNV events at the chromosome arm level.

Article Snippet: Notably, fastCNV enables, for the first time, the analysis of CNVs from the Visium HD spatial transcriptomics technology.

Techniques: Staining

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: Healthy human skin scRNA-seq datasets were collected and curated. Datasets were divided into PSU-containing and PSU-free samples. PSU-containing datasets underwent standardized reanalysis and processing, and integration performance was benchmarked. The most suitable tool was used to integrate these datasets into the HSCA core, followed by cell type annotation. Through transfer learning, 21 additional PSU-free datasets were incorporated, resulting in the HSCA extended (160 subjects, 177 samples, 110 cell types, >800,000 cells). Gene marker signatures were validated and refined using Visium HD spatial transcriptomics. Downstream analyses included the identification of novel and rare cell types, functional enrichment, and cell–cell communication analysis.

Article Snippet: To validate the spatial organization of the PSU defined in our core atlas and to assess additional relevant cell types, we generated two 10X Visium HD spatial transcriptomics sections (8 μm spot diameter) derived from healthy facial skin of a 48-year-old White female donor ( ).

Techniques: Marker, Functional Assay

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: ( a , b ) Two 10X Genomics Visium HD spatial transcriptomic sections (8 µm spot diameter) derived from healthy facial skin of a 48-year-old White female donor (temporal region). Spots were annotated with marker gene expression, and the derived cell types are overlaid on the H&E sections. The bottom-right inset of each panel displays the number of detected genes per spot (maximum 3,683 in D1 and 3,199 in D2). Bar = 250 µm. Abbreviations: see Supplementary Table 3.

Article Snippet: To validate the spatial organization of the PSU defined in our core atlas and to assess additional relevant cell types, we generated two 10X Visium HD spatial transcriptomics sections (8 μm spot diameter) derived from healthy facial skin of a 48-year-old White female donor ( ).

Techniques: Derivative Assay, Marker, Gene Expression

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: (a) Illustrative schematic of hair bulb anatomy. (b) Visium HD spots corresponding to the hair bulb overlaid on the tissue section. ( c ) Spatial feature plot of Dermal papilla markers. ( d ) Dot plot showing marker gene expression across major bulb cell types. ( e ) Catagen hair follicle section (D2) highlighting cell clustering. ( f ) Violin plots of gene expression in the catagen follicle cluster, reflecting hair-cycle-specific transcriptional dynamics. ( g ) Heatmap of spatial ligand-receptor crosstalk between follicular compartments inferred by CellChat. Bar = 8 µm. Abbreviations: see Supplementary Table 3.

Article Snippet: To validate the spatial organization of the PSU defined in our core atlas and to assess additional relevant cell types, we generated two 10X Visium HD spatial transcriptomics sections (8 μm spot diameter) derived from healthy facial skin of a 48-year-old White female donor ( ).

Techniques: Marker, Gene Expression

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: ( a ) UMAP of the HSCA core restricted to 8,572 cells from lower follicular compartments. ( b ) RCTD deconvolution of Visium HD data (from ) using the HSCA core, showing concordant cell type gene signatures. ( c , d ) Violin plots of marker gene expression for the SHG in the HSCA core (c) and in Visium HD (d). ( e ) PHATE embedding of sebaceous gland cells illustrating differentiation trajectories. ( f ) Pie chart summarizing the relative abundance of sebocyte maturation stages in the HSCA core. ( g ) Pie chart showing dataset origin of sebaceous cells across maturation stages. ( h ) Violin plots of PTN and C1QTNF12 expression in sebaceous progenitors and the JZ in the HSCA core. ( i ) Independent spatial validation of PTN and C1QTNF12 expression in Visium HD sections. Abbreviations: see Supplementary Table 3.

Article Snippet: To validate the spatial organization of the PSU defined in our core atlas and to assess additional relevant cell types, we generated two 10X Visium HD spatial transcriptomics sections (8 μm spot diameter) derived from healthy facial skin of a 48-year-old White female donor ( ).

Techniques: Marker, Gene Expression, Expressing, Biomarker Discovery

Journal: bioRxiv

Article Title: Development of an Integrated Single-Cell and Spatial Transcriptomics Atlas of Healthy Human Skin Focusing on the Pilosebaceous Unit

doi: 10.1101/2025.09.09.675235

Figure Lengend Snippet: (a) Feature plot of CCER2 expression highlighting the Merkel cell cluster in the HSCA core. (b) Gene signature of the cluster, including the characteristic KRT20 marker for Merkel cells. (c) Functional enrichment analysis of the Merkel cell gene signature, visualized as a dot plot. ( d , e ) Spatial visualization of CCER2 expression in the bulge region of hair follicles in Visium HD sections.

Article Snippet: To validate the spatial organization of the PSU defined in our core atlas and to assess additional relevant cell types, we generated two 10X Visium HD spatial transcriptomics sections (8 μm spot diameter) derived from healthy facial skin of a 48-year-old White female donor ( ).

Techniques: Expressing, Marker, Functional Assay