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mouse olfactory bulb bgi stomics  (Complete Genomics Inc)


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    Structured Review

    Complete Genomics Inc mouse olfactory bulb bgi stomics
    Mouse Olfactory Bulb Bgi Stomics, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 484 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mouse+transcriptome/Stereo-seq+Transcriptomics+Set+for+FFPE/pm41895283-288-63-66
    Average 99 stars, based on 484 article reviews
    mouse olfactory bulb bgi stomics - by Bioz Stars, 2026-10
    99/100 stars

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    Related Articles

    Spatial Transcriptomics:

    Article Title: A pan cancer multi omics analysis of OLR1 reveals its association with tumor immunity metabolic pathways and clinical prognosis
    Article Snippet: .. Spatial transcriptomics datasets were obtained from the STOmics database (https://db.cngb.org/stomics/) and the GEO database (https://www.ncbi.nlm.nih.gov/geo/), including STDS0000027, STDS0000033, STDS0000046, GSM5924031, and GSM6505133. ..

    Article Title: Spi1-Soat1 Transcriptional axis drives microglial lipid droplet accumulation and secondary brain injury after intracerebral hemorrhage
    Article Snippet: .. Cholesterol metabolic pathway activation and microglia-specific upregulation of Soat1 are tightly associated with lipid droplet accumulation after ICH To define the core metabolic pathways and key regulators driving microglial LD accumulation after ICH, we analyzed the day 7 perihematomal tissue subset of a spatial transcriptomics dataset (STOmics DB, ID:STT0000047), with a focus on lipid metabolic cascades underlying LD biogenesis (Fig. 3A). ..

    Analysis:

    Article Title: Diverse infections transcriptionally reprogram the intestinal epithelium and epithelial-immune cell interactions.
    Article Snippet: .. Indeed, using Stereo-seq (STOmics) spatial transcriptomic analysis, which profiles host and microbial RNA, we found that Yersinia transcripts were localized to the basal region of the PG and did not extend to the enterocytes overlaying the PG (Supplementary Fig. 10g). ..

    Sequencing:

    Article Title: Multi-omics integration and machine learning identify an ACKR1 + endothelial cell-based lactate-immune signature associated with carotid plaque vulnerability and progression.
    Article Snippet: .. The internal singlecell and spatial transcriptomes were deposited with our previous study (Lai et al., Nat Cardiovasc Res, 2025) in the Genome Sequence Archive for Human at the National Genomics Data Center under accession HRA006030 (https://ngdc.cncb.ac.cn/gsa-human), with backups in the China National GeneBank: spatial transcriptomes in the STOmics Database (STT0000052, https://db.cngb.org/stomics/) and single-cell data in the China National Sequence Archive (CNP0004894, https:// db.cngb.org/cnsa/). ..

    Single Cell:

    Article Title: Multi-omics integration and machine learning identify an ACKR1 + endothelial cell-based lactate-immune signature associated with carotid plaque vulnerability and progression.
    Article Snippet: .. The internal singlecell and spatial transcriptomes were deposited with our previous study (Lai et al., Nat Cardiovasc Res, 2025) in the Genome Sequence Archive for Human at the National Genomics Data Center under accession HRA006030 (https://ngdc.cncb.ac.cn/gsa-human), with backups in the China National GeneBank: spatial transcriptomes in the STOmics Database (STT0000052, https://db.cngb.org/stomics/) and single-cell data in the China National Sequence Archive (CNP0004894, https:// db.cngb.org/cnsa/). ..

    Activation Assay:

    Article Title: Spi1-Soat1 Transcriptional axis drives microglial lipid droplet accumulation and secondary brain injury after intracerebral hemorrhage
    Article Snippet: .. Cholesterol metabolic pathway activation and microglia-specific upregulation of Soat1 are tightly associated with lipid droplet accumulation after ICH To define the core metabolic pathways and key regulators driving microglial LD accumulation after ICH, we analyzed the day 7 perihematomal tissue subset of a spatial transcriptomics dataset (STOmics DB, ID:STT0000047), with a focus on lipid metabolic cascades underlying LD biogenesis (Fig. 3A). ..

    Tissue:

    Article Title: Spi1-Soat1 Transcriptional axis drives microglial lipid droplet accumulation and secondary brain injury after intracerebral hemorrhage
    Article Snippet: .. Cholesterol metabolic pathway activation and microglia-specific upregulation of Soat1 are tightly associated with lipid droplet accumulation after ICH To define the core metabolic pathways and key regulators driving microglial LD accumulation after ICH, we analyzed the day 7 perihematomal tissue subset of a spatial transcriptomics dataset (STOmics DB, ID:STT0000047), with a focus on lipid metabolic cascades underlying LD biogenesis (Fig. 3A). ..

    H&E Stain:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: .. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). .. Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N Kit V1.0 (Cat. No. 211KN114) and Stereo-seq 16 Barcode Library Preparation Kit V1.0 (Cat. No. 111KL160).



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    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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    Image Search Results


    Changes in the abundance and gene expression profile of leukocytes in Nodal Δ/Δ females. (A) t-SNE of all Ptprc + cells at the Nodal loxP/loxP (n=2) and Nodal Δ/Δ (n=2) maternal-fetal interface. (B) Proportion of cell types in each sample. Notably, the proportion of maternal neutrophils, non-classical monocytes and PAMM1a cells was significantly decreased in Nodal Δ/Δ females, while the proportion of M2 and PAMM2 cells was increased (FDR<0.05). (C) The number of significant differentially expressed genes (DEGs) (adjusted P-value<0.1) in all immune cell clusters at the d10.5 maternal-fetal interface between Nodal loxP/loxP and Nodal Δ/Δ females.

    Journal: Frontiers in Immunology

    Article Title: Single-cell RNA sequencing of leukocytes at the maternal-fetal interface in physiological and pathological Nodal-deficient pregnancies

    doi: 10.3389/fimmu.2026.1611813

    Figure Lengend Snippet: Changes in the abundance and gene expression profile of leukocytes in Nodal Δ/Δ females. (A) t-SNE of all Ptprc + cells at the Nodal loxP/loxP (n=2) and Nodal Δ/Δ (n=2) maternal-fetal interface. (B) Proportion of cell types in each sample. Notably, the proportion of maternal neutrophils, non-classical monocytes and PAMM1a cells was significantly decreased in Nodal Δ/Δ females, while the proportion of M2 and PAMM2 cells was increased (FDR<0.05). (C) The number of significant differentially expressed genes (DEGs) (adjusted P-value<0.1) in all immune cell clusters at the d10.5 maternal-fetal interface between Nodal loxP/loxP and Nodal Δ/Δ females.

    Article Snippet: Probe hybridization was performed on approximately 500,000 cells/sample using the Chromium Fixed RNA Mouse Transcriptome Kit (10X Genomics Cat. No. PN-1000497) following protocol # CG000527 .

    Techniques: Gene Expression

    a , UMAP of GCs, colored by seven GC subtypes (Progenitor, Preantral 1, Preantral 2, Mitotic 1, Mitotic 2, Antral Mural and Atretic). b , Feature plots of representative subtype markers on the UMAP. c , Monocle3 pseudotime trajectory inferred for GCs, with the principal graph overlaid and direction indicated from progenitor toward antral mural cells. d , Heatmap of representative genes showing coordinated expression changes along the progenitor-to-mural trajectory (expression shown as z-scores). e , Heatmap of Hallmark ssGSEA scores across granulosa subtypes (z-scored per gene set). f , H&E image of a Stereo-seq FF V1.3 mouse ovary section (6-8 weeks old), with representative regions (α–θ) indicated. Scale bar, 100 μm. g , Cell2location-based spatial mapping of GC subtypes at cell-bin resolution. h , Zoom-in views of representative regions (α, β, γ, and θ) showing H&E morphology and spatial expression of selected marker genes. Scale bar, 50 μm.

    Journal: bioRxiv

    Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

    doi: 10.64898/2026.03.11.710939

    Figure Lengend Snippet: a , UMAP of GCs, colored by seven GC subtypes (Progenitor, Preantral 1, Preantral 2, Mitotic 1, Mitotic 2, Antral Mural and Atretic). b , Feature plots of representative subtype markers on the UMAP. c , Monocle3 pseudotime trajectory inferred for GCs, with the principal graph overlaid and direction indicated from progenitor toward antral mural cells. d , Heatmap of representative genes showing coordinated expression changes along the progenitor-to-mural trajectory (expression shown as z-scores). e , Heatmap of Hallmark ssGSEA scores across granulosa subtypes (z-scored per gene set). f , H&E image of a Stereo-seq FF V1.3 mouse ovary section (6-8 weeks old), with representative regions (α–θ) indicated. Scale bar, 100 μm. g , Cell2location-based spatial mapping of GC subtypes at cell-bin resolution. h , Zoom-in views of representative regions (α, β, γ, and θ) showing H&E morphology and spatial expression of selected marker genes. Scale bar, 50 μm.

    Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

    Techniques: Expressing, Marker

    Spatial maps showing cell2location-predicted localization of each annotated cell subtype on the Stereo-seq FF V1.3 ovary section (6–8 weeks old), displayed separately by subtype. Scale bar, 100 μm

    Journal: bioRxiv

    Article Title: Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

    doi: 10.64898/2026.03.11.710939

    Figure Lengend Snippet: Spatial maps showing cell2location-predicted localization of each annotated cell subtype on the Stereo-seq FF V1.3 ovary section (6–8 weeks old), displayed separately by subtype. Scale bar, 100 μm

    Article Snippet: Publicly available mouse ovary Stereo-seq Transcriptomics FF v1.3 demo data were obtained from the STOmics website ( https://www.stomics.tech/col1347 ).

    Techniques:

    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