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scatac seq  (Spatial Transcriptomics Inc)

 
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    Structured Review

    Spatial Transcriptomics Inc scatac seq
    Scatac Seq, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spatial+transcriptomics+(st)+methods/seq+st/pmc12492631-1-5-7
    Average 86 stars, based on 1 article reviews
    scatac seq - by Bioz Stars, 2026-09
    86/100 stars

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    Related Articles

    Spatial Transcriptomics:

    Article Title: AEBP1 drives fibroblast-mediated T cell dysfunction in tumors.
    Article Snippet: .. Spatial transcriptomics data analysis The stRNA-seq slides of two human COAD samples were printed with two identical capture regions. ..

    Article Title: Integrating multi-modal transcriptomics identifies cellular subtypes with distinct roles in PDAC progression.
    Article Snippet: .. Spatial transcriptomics (ST-seq) data, including the HTANPDAC and GEO datasets GSE233293 and GSE202740, totaling 20 ST-seq samples, were jointly analyzed via the R packages Seurat and BayesSpace in R4.1.1 [41]. ..

    Article Title: Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment
    Article Snippet: Spatial Transcriptomics , 2016 , corrFISH , Single-cell , [ ] . .. Spatial Transcriptomics , 2017 , Geo-seq , Single-cell , [ ] . .. Spatial Transcriptomics , 2018 , Visium , 55 μm , [ ] .

    Article Title: Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment
    Article Snippet: Spatial Transcriptomics , 2019 , HDST , 2 μm , [ ] . .. Spatial Transcriptomics + Proteomics , 2020 , DBiT-seq , 10–50 μm , [ ] . .. Spatial Transcriptomics + Proteomics , 2020 , GeoMx DSP , Single-cell , [ ] .

    Article Title: Biology-driven insights into the power of single-cell foundation models
    Article Snippet: .. scGPT [ ] , scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics , 50 M , 33 M , 1200 HVGs , 512 , Value binning , Lookup Table (512d) , × , Encoder with attention mask , Iterative MGM with MSE loss (gene-prompt + cell-prompt), generative pretraining. .. UCE [ ] , scRNA-Seq , 650 M , 36 M , 1024 non-unique genes sampled (with replacement) by expression and ordered by genomic positions , 1280 , / , ESM-2 [ ] based protein embedding (5120d) , ✓ , Encoder , Modified MGM: binary CE loss for predicting whether a gene is expressed or not.

    Gene Expression:

    Article Title: Application of transcriptomics techniques in skin cancer
    Article Snippet: Single-cell RNA sequencing technology (scRNA-seq) , Gene expression profiles in single cell samples , Gene expression abundance and cell type , 1. Revealing cellular heterogeneity. 2. Building cell atlases. 3. Inferring differentiation trajectories. 4. Resolving the cellular composition of complex tissues. , 1. Loss of original spatial location information. 2. Dissociation process may result in the loss of specific cells. 3. High cost. 4. Complex data analysis.. .. Spatial Transcriptomics (ST-seq) , Organization of gene expression profiles retaining spatial location information , Gene expression abundance, cell type and spatial location information , 1. Preserve and interpret the spatial context of gene expression. 2. Locate specific gene types within tissues. 3. Study tissue microenvironments and link molecular phenotypes to tissue morphology. , 1. Data analysis is more complex and requires the integration of images and multi-omics. 2. The cost of technology is extremely high. 3. The number of genes covered may be limited.. .. MM , RNA-seq , MITF, AXL , BRAF/MEK, anti-PD-1 antibody , ( ) .

    Biomarker Discovery:

    Article Title: Application of transcriptomics techniques in skin cancer
    Article Snippet: Single-cell RNA sequencing technology (scRNA-seq) , Gene expression profiles in single cell samples , Gene expression abundance and cell type , 1. Revealing cellular heterogeneity. 2. Building cell atlases. 3. Inferring differentiation trajectories. 4. Resolving the cellular composition of complex tissues. , 1. Loss of original spatial location information. 2. Dissociation process may result in the loss of specific cells. 3. High cost. 4. Complex data analysis.. .. Spatial Transcriptomics (ST-seq) , Organization of gene expression profiles retaining spatial location information , Gene expression abundance, cell type and spatial location information , 1. Preserve and interpret the spatial context of gene expression. 2. Locate specific gene types within tissues. 3. Study tissue microenvironments and link molecular phenotypes to tissue morphology. , 1. Data analysis is more complex and requires the integration of images and multi-omics. 2. The cost of technology is extremely high. 3. The number of genes covered may be limited.. .. MM , RNA-seq , MITF, AXL , BRAF/MEK, anti-PD-1 antibody , ( ) .

    Sequencing:

    Article Title: Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics
    Article Snippet: .. Spatial transcriptomics sequencing (ST-seq) enables the identification of distinct cell populations while preserving their spatial context, offering essential insights into cell function, phenotype, and positional relationships within the tissue microenvironment [ , ]. ..

    Preserving:

    Article Title: Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics
    Article Snippet: .. Spatial transcriptomics sequencing (ST-seq) enables the identification of distinct cell populations while preserving their spatial context, offering essential insights into cell function, phenotype, and positional relationships within the tissue microenvironment [ , ]. ..

    Cell Function Assay:

    Article Title: Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics
    Article Snippet: .. Spatial transcriptomics sequencing (ST-seq) enables the identification of distinct cell populations while preserving their spatial context, offering essential insights into cell function, phenotype, and positional relationships within the tissue microenvironment [ , ]. ..

    Single Cell:

    Article Title: Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment
    Article Snippet: Spatial Transcriptomics , 2016 , corrFISH , Single-cell , [ ] . .. Spatial Transcriptomics , 2017 , Geo-seq , Single-cell , [ ] . .. Spatial Transcriptomics , 2018 , Visium , 55 μm , [ ] .



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