Review



digital spatial profiling spatial transcriptomics sequencing  (Spatial Transcriptomics Inc)

 
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 86
      Buy from Supplier

    Structured Review

    Spatial Transcriptomics Inc digital spatial profiling spatial transcriptomics sequencing
    Digital Spatial Profiling Spatial Transcriptomics Sequencing, 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+transcriptomic+profiles/sequencing+spatial+transcriptomics/pm40946801-64-0-3
    Average 86 stars, based on 1 article reviews
    digital spatial profiling spatial transcriptomics sequencing - by Bioz Stars, 2026-09
    86/100 stars

    Images

    Related Articles

    Spatial Transcriptomics:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. Spatial transcriptomics sequencing and data analysis Human biopsy samples were used for RNA extraction on frozen embedded tissues stored at − 80 ◦ C to obtain RNA which has good integrity for future spatial transcription experiments. ..

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Article Title: Single-Cell and Spatial Transcriptomics-Based Research Reveals Association Between M2a Macrophages and Tumor Spread through Air Spaces in Lung Adenocarcinoma.
    Article Snippet: Address correspondence to Daqiang Sun, M.D., Department of Thoracic Surgery, Tianjin Chest Hospital, No. 261, Taierzhuang South Rd., Jinnan District, Tianjin, 300222, China.. E-mail: sdqmdsr@163.com.. Tumor spread through air spaces (STAS) is a pathologic feature of lung cancer with prognostic significance, and it is also a cutting-edge hotspot in the clinical field of lung cancer.

    Article Title: Single-cell multi-omics analysis revealed the expansion of age-associated B cells in the pancreas of type 1 autoimmune pancreatitis patients.
    Article Snippet: .. Spatial transcriptomics sequencing and data processing Formalin-fixed paraffin-embedded (FFPE) 5-μm pancreatic lesion tissue sections from a representative AIP patient were used. ..

    Sequencing:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. Spatial transcriptomics sequencing and data analysis Human biopsy samples were used for RNA extraction on frozen embedded tissues stored at − 80 ◦ C to obtain RNA which has good integrity for future spatial transcription experiments. ..

    Article Title: The molecular mechanisms and therapeutic implications of PANoptosis in ischemic diseases.
    Article Snippet: .. Spatial transcriptomics sequencing technology allows for the precise analysis of the spatial distribution patterns of PANoptosis-related gene expression at the tissue level in situ, revealing the spatially specific modes of PANoptosis regulation exhibited by different cell types within the tissue microenvironment. ..

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Article Title: Single-Cell and Spatial Transcriptomics-Based Research Reveals Association Between M2a Macrophages and Tumor Spread through Air Spaces in Lung Adenocarcinoma.
    Article Snippet: Address correspondence to Daqiang Sun, M.D., Department of Thoracic Surgery, Tianjin Chest Hospital, No. 261, Taierzhuang South Rd., Jinnan District, Tianjin, 300222, China.. E-mail: sdqmdsr@163.com.. Tumor spread through air spaces (STAS) is a pathologic feature of lung cancer with prognostic significance, and it is also a cutting-edge hotspot in the clinical field of lung cancer.

    Article Title: Association of Single-Nucleotide Polymorphisms on FURIN and EPHA2 Genes with the Risk and Prognosis of Undifferentiated Nasopharyngeal Cancer.
    Article Snippet: .. This becomes even more insightful when we know that APP has significant effects on cancer cell proliferation, migration, and invasion, potentially contributing to tumor progression in cervical squamous cell carcinoma, as demonstrated recently using a novel biotechnology called Spatial Transcriptomics Sequencing [68]. ..

    Article Title: Single-cell multi-omics analysis revealed the expansion of age-associated B cells in the pancreas of type 1 autoimmune pancreatitis patients.
    Article Snippet: .. Spatial transcriptomics sequencing and data processing Formalin-fixed paraffin-embedded (FFPE) 5-μm pancreatic lesion tissue sections from a representative AIP patient were used. ..

    Article Title: Multimodal therapeutic strategies against gastric cancer: from conventional treatments to tumor microenvironment targeting
    Article Snippet: .. Spatial transcriptomics (ST) sequencing technology was designated Technology of the Year in 2020. ..

    Article Title: The molecular mechanisms and therapeutic implications of PANoptosis in ischemic diseases
    Article Snippet: .. Spatial transcriptomics sequencing technology allows for the precise analysis of the spatial distribution patterns of PANoptosis-related gene expression at the tissue level in situ, revealing the spatially specific modes of PANoptosis regulation exhibited by different cell types within the tissue microenvironment. ..

    RNA Extraction:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. Spatial transcriptomics sequencing and data analysis Human biopsy samples were used for RNA extraction on frozen embedded tissues stored at − 80 ◦ C to obtain RNA which has good integrity for future spatial transcription experiments. ..

    Gene Expression:

    Article Title: The molecular mechanisms and therapeutic implications of PANoptosis in ischemic diseases.
    Article Snippet: .. Spatial transcriptomics sequencing technology allows for the precise analysis of the spatial distribution patterns of PANoptosis-related gene expression at the tissue level in situ, revealing the spatially specific modes of PANoptosis regulation exhibited by different cell types within the tissue microenvironment. ..

    Article Title: The molecular mechanisms and therapeutic implications of PANoptosis in ischemic diseases
    Article Snippet: .. Spatial transcriptomics sequencing technology allows for the precise analysis of the spatial distribution patterns of PANoptosis-related gene expression at the tissue level in situ, revealing the spatially specific modes of PANoptosis regulation exhibited by different cell types within the tissue microenvironment. ..

    In Situ:

    Article Title: The molecular mechanisms and therapeutic implications of PANoptosis in ischemic diseases.
    Article Snippet: .. Spatial transcriptomics sequencing technology allows for the precise analysis of the spatial distribution patterns of PANoptosis-related gene expression at the tissue level in situ, revealing the spatially specific modes of PANoptosis regulation exhibited by different cell types within the tissue microenvironment. ..

    Article Title: The molecular mechanisms and therapeutic implications of PANoptosis in ischemic diseases
    Article Snippet: .. Spatial transcriptomics sequencing technology allows for the precise analysis of the spatial distribution patterns of PANoptosis-related gene expression at the tissue level in situ, revealing the spatially specific modes of PANoptosis regulation exhibited by different cell types within the tissue microenvironment. ..

    Cell Culture:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Enzyme-linked Immunosorbent Assay:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Immunohistochemistry:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Quantitative RT-PCR:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Western Blot:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Transmission Assay:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Electron Microscopy:

    Article Title: Therapeutic targeting of interleukin-17C signaling in carcinogenesis of endometriosis.
    Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Sex as a biological variable ○ Human samples ○ Animal experiments ○ Cell culture and treatment ○ Establishment of endometrial organoids • METHOD DETAILS ○ Spatial transcriptomics sequencing and data analysis ○ Trajectory analysis ○ Enzyme-linked immunosorbent assay (ELISA) ○ Adhesion assays ○ Immunohistochemistry and qualification ○ qRT-PCR analysis ○ Western blot analysis ○ Transmission electron microscopy • QUANTIFICATION AND STATISTICAL ANALYSIS SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j. xcrm.2025.102464. ..

    Incubation:

    Article Title: Single-Cell and Spatial Transcriptomics-Based Research Reveals Association Between M2a Macrophages and Tumor Spread through Air Spaces in Lung Adenocarcinoma.
    Article Snippet: Address correspondence to Daqiang Sun, M.D., Department of Thoracic Surgery, Tianjin Chest Hospital, No. 261, Taierzhuang South Rd., Jinnan District, Tianjin, 300222, China.. E-mail: sdqmdsr@163.com.. Tumor spread through air spaces (STAS) is a pathologic feature of lung cancer with prognostic significance, and it is also a cutting-edge hotspot in the clinical field of lung cancer.

    Labeling:

    Article Title: Single-Cell and Spatial Transcriptomics-Based Research Reveals Association Between M2a Macrophages and Tumor Spread through Air Spaces in Lung Adenocarcinoma.
    Article Snippet: Address correspondence to Daqiang Sun, M.D., Department of Thoracic Surgery, Tianjin Chest Hospital, No. 261, Taierzhuang South Rd., Jinnan District, Tianjin, 300222, China.. E-mail: sdqmdsr@163.com.. Tumor spread through air spaces (STAS) is a pathologic feature of lung cancer with prognostic significance, and it is also a cutting-edge hotspot in the clinical field of lung cancer.

    Migration:

    Article Title: Association of Single-Nucleotide Polymorphisms on FURIN and EPHA2 Genes with the Risk and Prognosis of Undifferentiated Nasopharyngeal Cancer.
    Article Snippet: .. This becomes even more insightful when we know that APP has significant effects on cancer cell proliferation, migration, and invasion, potentially contributing to tumor progression in cervical squamous cell carcinoma, as demonstrated recently using a novel biotechnology called Spatial Transcriptomics Sequencing [68]. ..

    Formalin-fixed Paraffin-Embedded:

    Article Title: Single-cell multi-omics analysis revealed the expansion of age-associated B cells in the pancreas of type 1 autoimmune pancreatitis patients.
    Article Snippet: .. Spatial transcriptomics sequencing and data processing Formalin-fixed paraffin-embedded (FFPE) 5-μm pancreatic lesion tissue sections from a representative AIP patient were used. ..



    Similar Products

    760 spatial transcriptomic profiling  (10X Genomics)
    86
    10X Genomics 760 spatial transcriptomic profiling
    760 Spatial Transcriptomic Profiling, supplied by 10X Genomics, 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+transcriptomic+profiles/data+spatial+transcriptomic/pm42167485-330-12-20
    Average 86 stars, based on 1 article reviews
    760 spatial transcriptomic profiling - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    spatial transcriptomic profiles  (10X Genomics)
    86
    10X Genomics spatial transcriptomic profiles
    A Overview of the 294,159 bulk <t>transcriptomic</t> profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.
    Spatial Transcriptomic Profiles, supplied by 10X Genomics, 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+transcriptomic+profiles/data+spatial+transcriptomic/pmc12921006-326-0-7
    Average 86 stars, based on 1 article reviews
    spatial transcriptomic profiles - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    digital spatial profiling spatial transcriptomics sequencing  (Spatial Transcriptomics Inc)
    86
    Spatial Transcriptomics Inc digital spatial profiling spatial transcriptomics sequencing
    A Overview of the 294,159 bulk <t>transcriptomic</t> profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.
    Digital Spatial Profiling Spatial Transcriptomics Sequencing, 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+transcriptomic+profiles/sequencing+spatial+transcriptomics/pm40946801-64-0-3
    Average 86 stars, based on 1 article reviews
    digital spatial profiling spatial transcriptomics sequencing - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    cell spatial transcriptomic profiling  (Spatial Transcriptomics Inc)
    86
    Spatial Transcriptomics Inc cell spatial transcriptomic profiling
    A Overview of the 294,159 bulk <t>transcriptomic</t> profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.
    Cell Spatial Transcriptomic Profiling, 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+transcriptomic+profiles/profiling+transcriptomic/pm40938748-4-2-16
    Average 86 stars, based on 1 article reviews
    cell spatial transcriptomic profiling - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    spatial transcriptomics-mediated profiling  (Spatial Transcriptomics Inc)
    90
    Spatial Transcriptomics Inc spatial transcriptomics-mediated profiling
    A Overview of the 294,159 bulk <t>transcriptomic</t> profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.
    Spatial Transcriptomics Mediated Profiling, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spatial+transcriptomic+profiles/spatial+transcriptomics++st+/pmc12272147-164-0-0
    Average 90 stars, based on 1 article reviews
    spatial transcriptomics-mediated profiling - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    spatial transcriptomics (st) profiles  (Spatial Transcriptomics Inc)
    90
    Spatial Transcriptomics Inc spatial transcriptomics (st) profiles
    A Overview of the 294,159 bulk <t>transcriptomic</t> profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.
    Spatial Transcriptomics (St) Profiles, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spatial+transcriptomic+profiles/spatial+transcriptomics++st+/pm40598539-103-0-0
    Average 90 stars, based on 1 article reviews
    spatial transcriptomics (st) profiles - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    spatial transcriptomics st profiles  (Spatial Transcriptomics Inc)
    86
    Spatial Transcriptomics Inc spatial transcriptomics st profiles
    The expression pattern and tissue localization of PPARG in tumor samples. ( A ) PPARG expression levels in tumor and normal samples of the TCGA dataset. ( B ) PPARG was correlated with pathological grades in the TCGA dataset. ( C ) Survival analysis of OS time between high and low-PPARG groups. ( D ) Survival analysis of DSS time between high and low-PPARG groups. ( E ) Correlation analyses between PPARG expression and tumor phenotypes. ( F , H , J ) PPARG expression in different cell types of spatial <t>transcriptomics.</t> F : LIHC1, H : LIHC2, J : LIHC3. ( G , I , K ) The comparisons of PPARG expression levels between malignant and normal samples. ( L ) The visualizations of the relationship between PPARG expression and various components of TME
    Spatial Transcriptomics St Profiles, 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+transcriptomic+profiles/profiles+spatial+st+transcriptomics/pmc12329936-87-0-0
    Average 86 stars, based on 1 article reviews
    spatial transcriptomics st profiles - by Bioz Stars, 2026-09
    86/100 stars
    		  Buy from Supplier
    seeker spatial transcriptomics profiling  (TaKaRa)
    95
    TaKaRa seeker spatial transcriptomics profiling
    The expression pattern and tissue localization of PPARG in tumor samples. ( A ) PPARG expression levels in tumor and normal samples of the TCGA dataset. ( B ) PPARG was correlated with pathological grades in the TCGA dataset. ( C ) Survival analysis of OS time between high and low-PPARG groups. ( D ) Survival analysis of DSS time between high and low-PPARG groups. ( E ) Correlation analyses between PPARG expression and tumor phenotypes. ( F , H , J ) PPARG expression in different cell types of spatial <t>transcriptomics.</t> F : LIHC1, H : LIHC2, J : LIHC3. ( G , I , K ) The comparisons of PPARG expression levels between malignant and normal samples. ( L ) The visualizations of the relationship between PPARG expression and various components of TME
    Seeker Spatial Transcriptomics Profiling, supplied by TaKaRa, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/spatial+transcriptomic+profiles/Seeker+Spatial+Transcriptomics+Kit/pm40592324-526-4-3
    Average 95 stars, based on 1 article reviews
    seeker spatial transcriptomics profiling - by Bioz Stars, 2026-09
    95/100 stars
    		  Buy from Supplier

    Image Search Results


    A Overview of the 294,159 bulk transcriptomic profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.

    Journal: NPJ Systems Biology and Applications

    Article Title: Association of copy number alterations with the immune transcriptomic landscape in cancer

    doi: 10.1038/s41540-026-00649-8

    Figure Lengend Snippet: A Overview of the 294,159 bulk transcriptomic profiles collected from the three datasets: GPL570 , ARCHS4, and TCGA. Consensus independent component analysis (c-ICA) was applied to each dataset to disentangle the bulk transcriptomic profiles into statistically independent transcriptional components (TCs). The TCs were then classified as CNA-TCs if they captured the effect of copy number alterations (CNA) based on the transcriptional adaptation to CNA profiling (TACNA). Additionally, TCs that capture immune-related processes using gene set enrichment analysis (GSEA) were defined as immune-TCs. B Heatmaps showing CNA regions captured by the CNA-TCs. Each column corresponds to a CNA-TC, with genes arranged in genomic order. For each CNA-TC, regions where many genes have high gene weights—indicating a CNA effect as determined by TACNA—are marked in red (see inset example). Only the red-marked regions, which represent the specific CNA effect captured by the corresponding CNA-TC, are shown. The CNA-TCs are sorted based on the position of the CNA region they capture. C Heatmap showing the z-value of GSEA for each immune-TC across all immune-related gene sets from Gene Ontology—Biological Process and REACTOME.

    Article Snippet: Spatial transcriptomic profiles were obtained from the 10x Genomics website ( https://www.10xgenomics.com ).

    Techniques: Capture-C

    A Three examples of immune-TC activity across cell types are shown. Single-cell RNA sequencing included 114,253 cells from 181 patients with 13 different cancer types from the single-cell tumor immune atlas for precision oncology. The transcriptomic profile of each cell was projected onto the GPL570 immune-TCs. Cell annotation was based on the labels defined in the immune atlas. Box plot colors represent major cell type groups. The boxplot displays the median as the central line, with box hinges representing the second and third quartiles, whiskers extending by half the interquartile range, and outliers shown as individual dots. B Three examples of tumor spatial transcriptomic datasets from 10x Genomics Visium are shown. The transcriptomic profile of each spatial spot was projected onto the GPL570 CNA- and immune-TCs, and CNA burden was inferred. The spatial organization of the activity of three immune-TCs is shown for each tumor.

    Journal: NPJ Systems Biology and Applications

    Article Title: Association of copy number alterations with the immune transcriptomic landscape in cancer

    doi: 10.1038/s41540-026-00649-8

    Figure Lengend Snippet: A Three examples of immune-TC activity across cell types are shown. Single-cell RNA sequencing included 114,253 cells from 181 patients with 13 different cancer types from the single-cell tumor immune atlas for precision oncology. The transcriptomic profile of each cell was projected onto the GPL570 immune-TCs. Cell annotation was based on the labels defined in the immune atlas. Box plot colors represent major cell type groups. The boxplot displays the median as the central line, with box hinges representing the second and third quartiles, whiskers extending by half the interquartile range, and outliers shown as individual dots. B Three examples of tumor spatial transcriptomic datasets from 10x Genomics Visium are shown. The transcriptomic profile of each spatial spot was projected onto the GPL570 CNA- and immune-TCs, and CNA burden was inferred. The spatial organization of the activity of three immune-TCs is shown for each tumor.

    Article Snippet: Spatial transcriptomic profiles were obtained from the 10x Genomics website ( https://www.10xgenomics.com ).

    Techniques: Activity Assay, Single Cell, RNA Sequencing

    The expression pattern and tissue localization of PPARG in tumor samples. ( A ) PPARG expression levels in tumor and normal samples of the TCGA dataset. ( B ) PPARG was correlated with pathological grades in the TCGA dataset. ( C ) Survival analysis of OS time between high and low-PPARG groups. ( D ) Survival analysis of DSS time between high and low-PPARG groups. ( E ) Correlation analyses between PPARG expression and tumor phenotypes. ( F , H , J ) PPARG expression in different cell types of spatial transcriptomics. F : LIHC1, H : LIHC2, J : LIHC3. ( G , I , K ) The comparisons of PPARG expression levels between malignant and normal samples. ( L ) The visualizations of the relationship between PPARG expression and various components of TME

    Journal: Journal of Translational Medicine

    Article Title: Identification of matrix stiffness-related molecular subtypes in HCC via integrating multi-omics analysis and machine learning algorithms

    doi: 10.1186/s12967-025-06733-7

    Figure Lengend Snippet: The expression pattern and tissue localization of PPARG in tumor samples. ( A ) PPARG expression levels in tumor and normal samples of the TCGA dataset. ( B ) PPARG was correlated with pathological grades in the TCGA dataset. ( C ) Survival analysis of OS time between high and low-PPARG groups. ( D ) Survival analysis of DSS time between high and low-PPARG groups. ( E ) Correlation analyses between PPARG expression and tumor phenotypes. ( F , H , J ) PPARG expression in different cell types of spatial transcriptomics. F : LIHC1, H : LIHC2, J : LIHC3. ( G , I , K ) The comparisons of PPARG expression levels between malignant and normal samples. ( L ) The visualizations of the relationship between PPARG expression and various components of TME

    Article Snippet: Spatial transcriptomics (ST) profiles were obtained from Mendeley Data (skrx2fz79n) [ ].

    Techniques: Expressing