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stomics saw  (Complete Genomics Inc)


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    Structured Review

    Complete Genomics Inc stomics saw
    Stomics Saw, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 97/100, based on 339 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/stomics saw/product/Complete Genomics Inc
    Average 97 stars, based on 339 article reviews
    stomics saw - by Bioz Stars, 2026-04
    97/100 stars

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    Complete Genomics Inc stereo seq whole mouse brain dataset
    Performance of STCS on <t>high-resolution</t> <t>Stereo-seq</t> mouse brain data. A) Tissue images and segmentations. Left: original H&E image; Center: nuclei segmentation mask; Right: Single-cell Segmented slide by STCS (colored by cell class, defined as higher-level groupings of CellTypist-predicted cell types. B) Spatial continuity metrics. Left: Cell-class coherence across neighborhood size. computed as the proportion of spatially nearest neighbors sharing the same cell-class label at each neighborhood size. Higher values indicate greater spatial consistency of cell-class assignments within local tissue contexts. Middle: CHAOS scores computed at the Leiden cluster level. Right: CHAOS scores computed at the cell-class level. Lower CHAOS scores indicate better spatial organization. The center line represents the median CHAOS score and the box spans the interquartile range. The annotated text are µ ± σ . C) Gene Level metrics. Left: Cell-class label-transfer accuracy to a scRNA-seq reference across varying numbers of highly variable genes (HVGs), assessing how reliably reconstructed spatial cells recover reference-defined transcriptional identities and the robustness of predictions based on different selected features. Right: Distribution of gene-expression cosine similarity between reconstructed cells and scRNA-seq reference profiles across cell classes, quantifying transcriptomic agreement. Cosine similarity was computed between each reconstructed cell’s expression profile and the mean expression profile of its assigned cell class in the scRNA-seq reference. Center lines indicate medians and boxes span the interquartile range. The annotated text are µ ± σ . D) Cell-type composition accuracy. Left: Cell-type richness between methods and a single-cell reference data. Right: Absolute error in estimated cellclass proportions compared to the reference. Lower values indicate closer agreement with the cellular composition of the reference data. The annotated text are µ ± σ and center lines indicate median.
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    Complete Genomics Inc stereo seq spatial transcriptomics platform
    Spatial transcriptomic delineation of TPX2 positive epithelial cells and their tumour microenvironmental interactions in UTUC. A. Representative haematoxylin and eosin (H&E)-stained sections (left) and corresponding spatial transcriptomic cell-type annotations (right) from MI (upper) and NMI (lower)-UTUC biopsy, scale bar = 1 mm. Spatial spots were annotated by integrating spatial <t>transcriptomics</t> with single-cell reference datasets, revealing the spatial organisation of epithelial tumour populations and diverse TME components. B. Box plots showing TPX2 expression levels across major spatially defined cell types in MI-UTUC biopsy. TPX2 expression was significantly enriched in basal epithelial tumour cells and specific urothelial tumour subpopulations compared with immune and stromal compartments (∗∗∗∗, P < 0.0001; Wilcoxon rank-sum test). C. Bar plot comparing the proportion of TPX2 positive spots across spatial cell types between MI- and NMI-UTUC samples. TPX2 positive epithelial tumour populations were markedly enriched in MI-UTUC relative to NMI-UTUC. D. Box plots showing average epithelial mesenchymal transition (EMT) signature scores in spatial neighbours of TPX2 positive versus TPX2 negative epithelial tumour cells. Neighbourhoods surrounding TPX2 positive cells exhibited significantly higher EMT associated transcriptional activity (P = 3.33 × 10 −3 ; Wilcoxon rank-sum test), indicating localisation of TPX2 positive tumour cells within invasion-promoting microenvironments. E. Bar plot showing log2 fold changes of EGFR- and EPHA2-associated ligand expression in spatial neighbours of TPX2 positive compared with TPX2 negative epithelial tumour cells.
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    Complete Genomics Inc saw pipeline
    Spatial transcriptomic delineation of TPX2 positive epithelial cells and their tumour microenvironmental interactions in UTUC. A. Representative haematoxylin and eosin (H&E)-stained sections (left) and corresponding spatial transcriptomic cell-type annotations (right) from MI (upper) and NMI (lower)-UTUC biopsy, scale bar = 1 mm. Spatial spots were annotated by integrating spatial <t>transcriptomics</t> with single-cell reference datasets, revealing the spatial organisation of epithelial tumour populations and diverse TME components. B. Box plots showing TPX2 expression levels across major spatially defined cell types in MI-UTUC biopsy. TPX2 expression was significantly enriched in basal epithelial tumour cells and specific urothelial tumour subpopulations compared with immune and stromal compartments (∗∗∗∗, P < 0.0001; Wilcoxon rank-sum test). C. Bar plot comparing the proportion of TPX2 positive spots across spatial cell types between MI- and NMI-UTUC samples. TPX2 positive epithelial tumour populations were markedly enriched in MI-UTUC relative to NMI-UTUC. D. Box plots showing average epithelial mesenchymal transition (EMT) signature scores in spatial neighbours of TPX2 positive versus TPX2 negative epithelial tumour cells. Neighbourhoods surrounding TPX2 positive cells exhibited significantly higher EMT associated transcriptional activity (P = 3.33 × 10 −3 ; Wilcoxon rank-sum test), indicating localisation of TPX2 positive tumour cells within invasion-promoting microenvironments. E. Bar plot showing log2 fold changes of EGFR- and EPHA2-associated ligand expression in spatial neighbours of TPX2 positive compared with TPX2 negative epithelial tumour cells.
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    Image Search Results


    Performance of STCS on high-resolution Stereo-seq mouse brain data. A) Tissue images and segmentations. Left: original H&E image; Center: nuclei segmentation mask; Right: Single-cell Segmented slide by STCS (colored by cell class, defined as higher-level groupings of CellTypist-predicted cell types. B) Spatial continuity metrics. Left: Cell-class coherence across neighborhood size. computed as the proportion of spatially nearest neighbors sharing the same cell-class label at each neighborhood size. Higher values indicate greater spatial consistency of cell-class assignments within local tissue contexts. Middle: CHAOS scores computed at the Leiden cluster level. Right: CHAOS scores computed at the cell-class level. Lower CHAOS scores indicate better spatial organization. The center line represents the median CHAOS score and the box spans the interquartile range. The annotated text are µ ± σ . C) Gene Level metrics. Left: Cell-class label-transfer accuracy to a scRNA-seq reference across varying numbers of highly variable genes (HVGs), assessing how reliably reconstructed spatial cells recover reference-defined transcriptional identities and the robustness of predictions based on different selected features. Right: Distribution of gene-expression cosine similarity between reconstructed cells and scRNA-seq reference profiles across cell classes, quantifying transcriptomic agreement. Cosine similarity was computed between each reconstructed cell’s expression profile and the mean expression profile of its assigned cell class in the scRNA-seq reference. Center lines indicate medians and boxes span the interquartile range. The annotated text are µ ± σ . D) Cell-type composition accuracy. Left: Cell-type richness between methods and a single-cell reference data. Right: Absolute error in estimated cellclass proportions compared to the reference. Lower values indicate closer agreement with the cellular composition of the reference data. The annotated text are µ ± σ and center lines indicate median.

    Journal: bioRxiv

    Article Title: STCS: A Platform-Agnostic Framework for Cell-Level Reconstruction in Sequencing-Based Spatial Transcriptomics

    doi: 10.64898/2026.02.26.708370

    Figure Lengend Snippet: Performance of STCS on high-resolution Stereo-seq mouse brain data. A) Tissue images and segmentations. Left: original H&E image; Center: nuclei segmentation mask; Right: Single-cell Segmented slide by STCS (colored by cell class, defined as higher-level groupings of CellTypist-predicted cell types. B) Spatial continuity metrics. Left: Cell-class coherence across neighborhood size. computed as the proportion of spatially nearest neighbors sharing the same cell-class label at each neighborhood size. Higher values indicate greater spatial consistency of cell-class assignments within local tissue contexts. Middle: CHAOS scores computed at the Leiden cluster level. Right: CHAOS scores computed at the cell-class level. Lower CHAOS scores indicate better spatial organization. The center line represents the median CHAOS score and the box spans the interquartile range. The annotated text are µ ± σ . C) Gene Level metrics. Left: Cell-class label-transfer accuracy to a scRNA-seq reference across varying numbers of highly variable genes (HVGs), assessing how reliably reconstructed spatial cells recover reference-defined transcriptional identities and the robustness of predictions based on different selected features. Right: Distribution of gene-expression cosine similarity between reconstructed cells and scRNA-seq reference profiles across cell classes, quantifying transcriptomic agreement. Cosine similarity was computed between each reconstructed cell’s expression profile and the mean expression profile of its assigned cell class in the scRNA-seq reference. Center lines indicate medians and boxes span the interquartile range. The annotated text are µ ± σ . D) Cell-type composition accuracy. Left: Cell-type richness between methods and a single-cell reference data. Right: Absolute error in estimated cellclass proportions compared to the reference. Lower values indicate closer agreement with the cellular composition of the reference data. The annotated text are µ ± σ and center lines indicate median.

    Article Snippet: The Stereo-seq whole mouse brain dataset is available from STOmics ( https://en.stomics.tech/col1241/index.html ).

    Techniques: Single Cell, Gene Expression, Expressing

    Spatial transcriptomic delineation of TPX2 positive epithelial cells and their tumour microenvironmental interactions in UTUC. A. Representative haematoxylin and eosin (H&E)-stained sections (left) and corresponding spatial transcriptomic cell-type annotations (right) from MI (upper) and NMI (lower)-UTUC biopsy, scale bar = 1 mm. Spatial spots were annotated by integrating spatial transcriptomics with single-cell reference datasets, revealing the spatial organisation of epithelial tumour populations and diverse TME components. B. Box plots showing TPX2 expression levels across major spatially defined cell types in MI-UTUC biopsy. TPX2 expression was significantly enriched in basal epithelial tumour cells and specific urothelial tumour subpopulations compared with immune and stromal compartments (∗∗∗∗, P < 0.0001; Wilcoxon rank-sum test). C. Bar plot comparing the proportion of TPX2 positive spots across spatial cell types between MI- and NMI-UTUC samples. TPX2 positive epithelial tumour populations were markedly enriched in MI-UTUC relative to NMI-UTUC. D. Box plots showing average epithelial mesenchymal transition (EMT) signature scores in spatial neighbours of TPX2 positive versus TPX2 negative epithelial tumour cells. Neighbourhoods surrounding TPX2 positive cells exhibited significantly higher EMT associated transcriptional activity (P = 3.33 × 10 −3 ; Wilcoxon rank-sum test), indicating localisation of TPX2 positive tumour cells within invasion-promoting microenvironments. E. Bar plot showing log2 fold changes of EGFR- and EPHA2-associated ligand expression in spatial neighbours of TPX2 positive compared with TPX2 negative epithelial tumour cells.

    Journal: eBioMedicine

    Article Title: Somatic structural variants drive upper tract urothelial carcinoma muscle invasiveness via activation of TPX2 transcription

    doi: 10.1016/j.ebiom.2026.106182

    Figure Lengend Snippet: Spatial transcriptomic delineation of TPX2 positive epithelial cells and their tumour microenvironmental interactions in UTUC. A. Representative haematoxylin and eosin (H&E)-stained sections (left) and corresponding spatial transcriptomic cell-type annotations (right) from MI (upper) and NMI (lower)-UTUC biopsy, scale bar = 1 mm. Spatial spots were annotated by integrating spatial transcriptomics with single-cell reference datasets, revealing the spatial organisation of epithelial tumour populations and diverse TME components. B. Box plots showing TPX2 expression levels across major spatially defined cell types in MI-UTUC biopsy. TPX2 expression was significantly enriched in basal epithelial tumour cells and specific urothelial tumour subpopulations compared with immune and stromal compartments (∗∗∗∗, P < 0.0001; Wilcoxon rank-sum test). C. Bar plot comparing the proportion of TPX2 positive spots across spatial cell types between MI- and NMI-UTUC samples. TPX2 positive epithelial tumour populations were markedly enriched in MI-UTUC relative to NMI-UTUC. D. Box plots showing average epithelial mesenchymal transition (EMT) signature scores in spatial neighbours of TPX2 positive versus TPX2 negative epithelial tumour cells. Neighbourhoods surrounding TPX2 positive cells exhibited significantly higher EMT associated transcriptional activity (P = 3.33 × 10 −3 ; Wilcoxon rank-sum test), indicating localisation of TPX2 positive tumour cells within invasion-promoting microenvironments. E. Bar plot showing log2 fold changes of EGFR- and EPHA2-associated ligand expression in spatial neighbours of TPX2 positive compared with TPX2 negative epithelial tumour cells.

    Article Snippet: Formalin-fixed paraffin-embedded (FFPE) urothelial carcinoma tissue sections were profiled using the Stereo-seq spatial transcriptomics platform (MGI, China) according to the manufacturer's protocols.

    Techniques: Staining, Spatial Transcriptomics, Single Cell, Expressing, Activity Assay