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RStudio st transcriptome data
Isolation and cluster analysis of single-cell <t>transcriptomes</t> from four glioma samples derived from two patients. (A) Workflow of experimental strategy: isolation of human glioma tissues during clinical surgery, followed by parallel scRNA-seq and Spatial Transcriptomic (ST) analysis profiling using with the 10x Genomics Chromium platform and subsequent validation by H&E and IHC staining. (B) Uniform Manifold Approximation and Projection (UMAP) plot showing 16 major clusters. (C) Clusters are annotated for their cell types as predicted using canonical markers and signature-based annotation using Garnett. (D) Heatmap showing clustering with top 30 highly expressed genes. (E, F) Feature UMAP plots depicting cluster-specific expression of cell clusters markers including SOX2 (SRY-Box Transcription Factor 2) and EGFR (Epidermal growth factor receptor) to indicate the major malignant cell clusters.
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1) Product Images from "Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations"

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations

Journal: Frontiers in Immunology

doi: 10.3389/fimmu.2024.1452172

Isolation and cluster analysis of single-cell transcriptomes from four glioma samples derived from two patients. (A) Workflow of experimental strategy: isolation of human glioma tissues during clinical surgery, followed by parallel scRNA-seq and Spatial Transcriptomic (ST) analysis profiling using with the 10x Genomics Chromium platform and subsequent validation by H&E and IHC staining. (B) Uniform Manifold Approximation and Projection (UMAP) plot showing 16 major clusters. (C) Clusters are annotated for their cell types as predicted using canonical markers and signature-based annotation using Garnett. (D) Heatmap showing clustering with top 30 highly expressed genes. (E, F) Feature UMAP plots depicting cluster-specific expression of cell clusters markers including SOX2 (SRY-Box Transcription Factor 2) and EGFR (Epidermal growth factor receptor) to indicate the major malignant cell clusters.
Figure Legend Snippet: Isolation and cluster analysis of single-cell transcriptomes from four glioma samples derived from two patients. (A) Workflow of experimental strategy: isolation of human glioma tissues during clinical surgery, followed by parallel scRNA-seq and Spatial Transcriptomic (ST) analysis profiling using with the 10x Genomics Chromium platform and subsequent validation by H&E and IHC staining. (B) Uniform Manifold Approximation and Projection (UMAP) plot showing 16 major clusters. (C) Clusters are annotated for their cell types as predicted using canonical markers and signature-based annotation using Garnett. (D) Heatmap showing clustering with top 30 highly expressed genes. (E, F) Feature UMAP plots depicting cluster-specific expression of cell clusters markers including SOX2 (SRY-Box Transcription Factor 2) and EGFR (Epidermal growth factor receptor) to indicate the major malignant cell clusters.

Techniques Used: Isolation, Derivative Assay, Biomarker Discovery, Immunohistochemistry, Expressing

Cluster analysis and annotations of spatial transcriptomes from four glioma samples derived from two patients. (A) t-distributed stochastic neighbor embedding (tSNE) projection of spots showing 9 major ST clusters. (B) The spatial relationship among 9 major ST clusters in four different samples. (C) Heatmap showing clustering with top 30 highly expressed genes from each ST clusters. (D) Heatmap showing the correlation matrix generated from 8 major ST Clusters and 7 major cell types from scRNA-seq calculated through MIA (Multimodal intersection analysis).
Figure Legend Snippet: Cluster analysis and annotations of spatial transcriptomes from four glioma samples derived from two patients. (A) t-distributed stochastic neighbor embedding (tSNE) projection of spots showing 9 major ST clusters. (B) The spatial relationship among 9 major ST clusters in four different samples. (C) Heatmap showing clustering with top 30 highly expressed genes from each ST clusters. (D) Heatmap showing the correlation matrix generated from 8 major ST Clusters and 7 major cell types from scRNA-seq calculated through MIA (Multimodal intersection analysis).

Techniques Used: Derivative Assay, Generated

Related Articles

Isolation:

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations
Article Snippet: For both HG1 and HG2, we used the ST transcriptome data and an enrichment study in R studio using the SPATA package (version 1.0.1).

Derivative Assay:

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations
Article Snippet: For both HG1 and HG2, we used the ST transcriptome data and an enrichment study in R studio using the SPATA package (version 1.0.1).

Biomarker Discovery:

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations
Article Snippet: For both HG1 and HG2, we used the ST transcriptome data and an enrichment study in R studio using the SPATA package (version 1.0.1).

Immunohistochemistry:

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations
Article Snippet: For both HG1 and HG2, we used the ST transcriptome data and an enrichment study in R studio using the SPATA package (version 1.0.1).

Expressing:

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations
Article Snippet: For both HG1 and HG2, we used the ST transcriptome data and an enrichment study in R studio using the SPATA package (version 1.0.1).

Generated:

Article Title: Single-cell and spatial transcriptome assays reveal heterogeneity in gliomas through stress responses and pathway alterations
Article Snippet: For both HG1 and HG2, we used the ST transcriptome data and an enrichment study in R studio using the SPATA package (version 1.0.1).



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Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.

Journal: Frontiers in Oncology

Article Title: Spatial transcriptome and single-cell sequencing reveal the role of nucleotide metabolism in breast cancer progression and tumor microenvironment

doi: 10.3389/fonc.2025.1703778

Figure Lengend Snippet: Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.

Article Snippet: Breast cancer spatial transcriptomics (ST) data were acquired from the GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and 10x Genomics official website ( https://www.10xgenomics.com/ ).

Techniques: