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single cell rna sequencing scrna seq data  (Broad Clinical Labs)


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    Broad Clinical Labs single cell rna sequencing scrna seq data
    Single Cell Rna Sequencing Scrna Seq Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 719 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/single+cell+rna+seq+data/pmc13065274-182-12-25?v=Broad+Clinical+Labs
    Average 96 stars, based on 719 article reviews
    single cell rna sequencing scrna seq data - by Bioz Stars, 2026-07
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    (A) UMAP visualization of malignant GBM cells colored by inferred cell state (MES = mesenchymal, 76.4%; AC = astrocyte-like; OPC = oligodendrocyte progenitor-like; NPC = neural progenitor-like) based on Neftel 2019 meta-module gene signatures. (B) Dot plot showing the expression of 16 iron metabolism and ferroptosis genes across cell states. Dot size represents the percentage of cells expressing each gene; color intensity represents the mean log-normalized expression. (C) Ferroptosis vulnerability score (15 driver genes − 20 suppressor genes) across cell states. MES exhibited the highest vulnerability (−0.400 vs. AC −0.526, OPC −0.493, NPC −0.492; all P<0.001). Universally negative scores reflect dominant GPX4/SLC7A11 suppressor expression. <t>(D)</t> <t>Single-cell</t> NEO1 vs. HAMP correlation (Spearman ρ = +0.27, P = 0.135). The lack of significant correlation at the transcriptional level is consistent with the protein-level mode of NEO1/BMP/HAMP signaling regulation.
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    A) A UMAP plot is generated from <t>the</t> <t>single-cell</t> data, processed by the STAR-MAPS framework. Cells are colored by dissected brain region. B) The same UMAP, colored by cell-type label from the initial description of the dataset. C) A heatmap showing the degree of enrichment for 185 ASD-associated genes in the cells from Panels A and B, in data corrected for sample, batch, and developmental stage. Shade represents the magnitude of positive odds ratios; stars represent the P-value.
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    A) A UMAP plot is generated from <t>the</t> <t>single-cell</t> data, processed by the STAR-MAPS framework. Cells are colored by dissected brain region. B) The same UMAP, colored by cell-type label from the initial description of the dataset. C) A heatmap showing the degree of enrichment for 185 ASD-associated genes in the cells from Panels A and B, in data corrected for sample, batch, and developmental stage. Shade represents the magnitude of positive odds ratios; stars represent the P-value.
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    Image Search Results


    (A) UMAP visualization of malignant GBM cells colored by inferred cell state (MES = mesenchymal, 76.4%; AC = astrocyte-like; OPC = oligodendrocyte progenitor-like; NPC = neural progenitor-like) based on Neftel 2019 meta-module gene signatures. (B) Dot plot showing the expression of 16 iron metabolism and ferroptosis genes across cell states. Dot size represents the percentage of cells expressing each gene; color intensity represents the mean log-normalized expression. (C) Ferroptosis vulnerability score (15 driver genes − 20 suppressor genes) across cell states. MES exhibited the highest vulnerability (−0.400 vs. AC −0.526, OPC −0.493, NPC −0.492; all P<0.001). Universally negative scores reflect dominant GPX4/SLC7A11 suppressor expression. (D) Single-cell NEO1 vs. HAMP correlation (Spearman ρ = +0.27, P = 0.135). The lack of significant correlation at the transcriptional level is consistent with the protein-level mode of NEO1/BMP/HAMP signaling regulation.

    Journal: medRxiv

    Article Title: Multi-Omics Integrative Analysis of the Aspirin-Gut-Brain-Glioma Axis: Transcriptomic, Proteomic, Epigenetic, Mendelian Randomization, and Single-Cell Transcriptomic Evidence Converges on NEO1/Hepcidin Iron Reprogramming and Ferroptosis Vulnerability

    doi: 10.64898/2026.06.01.26354602

    Figure Lengend Snippet: (A) UMAP visualization of malignant GBM cells colored by inferred cell state (MES = mesenchymal, 76.4%; AC = astrocyte-like; OPC = oligodendrocyte progenitor-like; NPC = neural progenitor-like) based on Neftel 2019 meta-module gene signatures. (B) Dot plot showing the expression of 16 iron metabolism and ferroptosis genes across cell states. Dot size represents the percentage of cells expressing each gene; color intensity represents the mean log-normalized expression. (C) Ferroptosis vulnerability score (15 driver genes − 20 suppressor genes) across cell states. MES exhibited the highest vulnerability (−0.400 vs. AC −0.526, OPC −0.493, NPC −0.492; all P<0.001). Universally negative scores reflect dominant GPX4/SLC7A11 suppressor expression. (D) Single-cell NEO1 vs. HAMP correlation (Spearman ρ = +0.27, P = 0.135). The lack of significant correlation at the transcriptional level is consistent with the protein-level mode of NEO1/BMP/HAMP signaling regulation.

    Article Snippet: To validate our bulk transcriptomic findings at single-cell resolution and assess the heterogeneity of iron metabolism gene expression across GBM malignant cell states, we analyzed single-cell RNA-seq data from 28 GBM patients (GSE131928, Neftel et al. [ ]), comprising 15,112 cells profiled by 10X Genomics.

    Techniques: Expressing, Single Cell

    A) A UMAP plot is generated from the single-cell data, processed by the STAR-MAPS framework. Cells are colored by dissected brain region. B) The same UMAP, colored by cell-type label from the initial description of the dataset. C) A heatmap showing the degree of enrichment for 185 ASD-associated genes in the cells from Panels A and B, in data corrected for sample, batch, and developmental stage. Shade represents the magnitude of positive odds ratios; stars represent the P-value.

    Journal: bioRxiv

    Article Title: Spatiotemporal analysis of autism gene enrichment implicates cortex, thalamus, and hypothalamus

    doi: 10.64898/2026.05.14.724487

    Figure Lengend Snippet: A) A UMAP plot is generated from the single-cell data, processed by the STAR-MAPS framework. Cells are colored by dissected brain region. B) The same UMAP, colored by cell-type label from the initial description of the dataset. C) A heatmap showing the degree of enrichment for 185 ASD-associated genes in the cells from Panels A and B, in data corrected for sample, batch, and developmental stage. Shade represents the magnitude of positive odds ratios; stars represent the P-value.

    Article Snippet: Bhaduri et al . also describes 10X Genomics Chromium single-cell RNA-seq data but from eleven individual brains in the second trimester (12-23 PCW).

    Techniques: Generated, Single Cell

    Single-cell analysis of HCC TME and hepatocyte metabolic reprogramming. (A) UMAP dimensionality reduction plot showing 22 initial cell clusters. (B) Annotation of 7 major cell populations based on established marker genes. (C) Expression patterns of CD274 (PD-L1) and CTLA4 in various cell types before and after immunotherapy. (D) Cellular composition across samples. Sample H68 exhibits the highest proportion of Hepatocytes. (E) UMAP plot of hepatocyte subclustering analysis based on metabolic-related gene expression profiles, identifying 5 subpopulations (clusters 0-4). Cluster 1 is significantly enriched in post-treatment samples. (F) KEGG pathway enrichment analysis reveals functional clustering of hepatocyte subpopulations (clusters 0-4). (G) Hierarchical clustering of significantly enriched pathways within these clusters. (H) Expression patterns of core genes within the Pyruvate metabolism pathway across the five hepatocyte subpopulations. Genes in this pathway exhibit significantly elevated expression in Cluster 1.

    Journal: Frontiers in Immunology

    Article Title: The inhibitory effect of hepatic cancer energy metabolism on immune checkpoint therapy: perspectives from single-cell multi-omics analysis

    doi: 10.3389/fimmu.2026.1753670

    Figure Lengend Snippet: Single-cell analysis of HCC TME and hepatocyte metabolic reprogramming. (A) UMAP dimensionality reduction plot showing 22 initial cell clusters. (B) Annotation of 7 major cell populations based on established marker genes. (C) Expression patterns of CD274 (PD-L1) and CTLA4 in various cell types before and after immunotherapy. (D) Cellular composition across samples. Sample H68 exhibits the highest proportion of Hepatocytes. (E) UMAP plot of hepatocyte subclustering analysis based on metabolic-related gene expression profiles, identifying 5 subpopulations (clusters 0-4). Cluster 1 is significantly enriched in post-treatment samples. (F) KEGG pathway enrichment analysis reveals functional clustering of hepatocyte subpopulations (clusters 0-4). (G) Hierarchical clustering of significantly enriched pathways within these clusters. (H) Expression patterns of core genes within the Pyruvate metabolism pathway across the five hepatocyte subpopulations. Genes in this pathway exhibit significantly elevated expression in Cluster 1.

    Article Snippet: Integrated single-cell RNA-seq data (GEO, Mendeley) were analyzed using Seurat, AUCell, pySCENIC, CellChat, and Monocle.

    Techniques: Single-cell Analysis, Marker, Expressing, Gene Expression, Functional Assay