st-seq Search Results


visium st-seq  (10X Genomics)
90
10X Genomics visium st-seq
The patient characteristics ( a ) of the six ccRCC patients ( n = 3 LG and n = 3 HG) include: patient LG_2 with a vena cava thrombus (VCT) for which we collected primary tumour microenvironment (TME) and thrombi separately but processed in the one capture array for ST-seq; patient HG_1 that we collected and processed tissues from para-TME (pTME) and TME; and patient HG_3 that we collected tissues from pTME and TME. For this experimental workflow ( b ), ten tissue regions were sampled from pTME, TME and VCT that excluded fibrotic and necrotic regions. ST-seq was completed using 10x Genomics <t>Visium</t> Gene Expression microarrayed glass slides with unique spatially barcoded ST-spots that captured the mRNA released from the overlaying thin ccRCC tissue sections. Annotation of immune ST-spots was completed with data integration of six published single-cell RNA-sequencing (scRNA-seq) datasets. Further immune cell sub-typing was completed with a scRNA and T-cell receptor (TCR) sequencing dataset. Integrated analysis was completed on CD8 + T cells, TAM and monocytes.
Visium St Seq, supplied by 10X Genomics, 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/result/visium st-seq/product/10X Genomics
Average 90 stars, based on 1 article reviews
visium st-seq - by Bioz Stars, 2026-04
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st-seq visium platform  (10X Genomics)
90
10X Genomics st-seq visium platform
The patient characteristics ( a ) of the six ccRCC patients ( n = 3 LG and n = 3 HG) include: patient LG_2 with a vena cava thrombus (VCT) for which we collected primary tumour microenvironment (TME) and thrombi separately but processed in the one capture array for ST-seq; patient HG_1 that we collected and processed tissues from para-TME (pTME) and TME; and patient HG_3 that we collected tissues from pTME and TME. For this experimental workflow ( b ), ten tissue regions were sampled from pTME, TME and VCT that excluded fibrotic and necrotic regions. ST-seq was completed using 10x Genomics <t>Visium</t> Gene Expression microarrayed glass slides with unique spatially barcoded ST-spots that captured the mRNA released from the overlaying thin ccRCC tissue sections. Annotation of immune ST-spots was completed with data integration of six published single-cell RNA-sequencing (scRNA-seq) datasets. Further immune cell sub-typing was completed with a scRNA and T-cell receptor (TCR) sequencing dataset. Integrated analysis was completed on CD8 + T cells, TAM and monocytes.
St Seq Visium Platform, supplied by 10X Genomics, 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/result/st-seq visium platform/product/10X Genomics
Average 90 stars, based on 1 article reviews
st-seq visium platform - by Bioz Stars, 2026-04
90/100 stars
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st-seq libraries  (Illumina Inc)
90
Illumina Inc st-seq libraries
The patient characteristics ( a ) of the six ccRCC patients ( n = 3 LG and n = 3 HG) include: patient LG_2 with a vena cava thrombus (VCT) for which we collected primary tumour microenvironment (TME) and thrombi separately but processed in the one capture array for ST-seq; patient HG_1 that we collected and processed tissues from para-TME (pTME) and TME; and patient HG_3 that we collected tissues from pTME and TME. For this experimental workflow ( b ), ten tissue regions were sampled from pTME, TME and VCT that excluded fibrotic and necrotic regions. ST-seq was completed using 10x Genomics <t>Visium</t> Gene Expression microarrayed glass slides with unique spatially barcoded ST-spots that captured the mRNA released from the overlaying thin ccRCC tissue sections. Annotation of immune ST-spots was completed with data integration of six published single-cell RNA-sequencing (scRNA-seq) datasets. Further immune cell sub-typing was completed with a scRNA and T-cell receptor (TCR) sequencing dataset. Integrated analysis was completed on CD8 + T cells, TAM and monocytes.
St Seq Libraries, supplied by Illumina 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/result/st-seq libraries/product/Illumina Inc
Average 90 stars, based on 1 article reviews
st-seq libraries - by Bioz Stars, 2026-04
90/100 stars
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st-seq samples  (Spatial Transcriptomics Inc)
90
Spatial Transcriptomics Inc st-seq samples
The patient characteristics ( a ) of the six ccRCC patients ( n = 3 LG and n = 3 HG) include: patient LG_2 with a vena cava thrombus (VCT) for which we collected primary tumour microenvironment (TME) and thrombi separately but processed in the one capture array for ST-seq; patient HG_1 that we collected and processed tissues from para-TME (pTME) and TME; and patient HG_3 that we collected tissues from pTME and TME. For this experimental workflow ( b ), ten tissue regions were sampled from pTME, TME and VCT that excluded fibrotic and necrotic regions. ST-seq was completed using 10x Genomics <t>Visium</t> Gene Expression microarrayed glass slides with unique spatially barcoded ST-spots that captured the mRNA released from the overlaying thin ccRCC tissue sections. Annotation of immune ST-spots was completed with data integration of six published single-cell RNA-sequencing (scRNA-seq) datasets. Further immune cell sub-typing was completed with a scRNA and T-cell receptor (TCR) sequencing dataset. Integrated analysis was completed on CD8 + T cells, TAM and monocytes.
St Seq Samples, 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/result/st-seq samples/product/Spatial Transcriptomics Inc
Average 90 stars, based on 1 article reviews
st-seq samples - by Bioz Stars, 2026-04
90/100 stars
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st-seq  (Spatial Transcriptomics Inc)
90
Spatial Transcriptomics Inc st-seq
Applications of single-cell transcriptome sequencing in different fields. ( a ) Large-scale cell mapping construction, the first whole-body organellar transcriptome mapping in a non-human primate, the rhesus macaque . ( b ) Oncology research: pan-cancer analyses on bone marrow cells from 210 patients with 15 different human cancer types using single-cell transcriptome sequencing . ( c ) Neuroscience research: hippocampus of humans, rhesus monkeys, and pigs . ( d ) Developmental biology: human prefrontal cortex gene expression from gestation to adulthood , embryo and Arabidopsis leaves . ( e ) Cell subpopulation refinement and rare cell type identification: liver and kidney . ( f ) Stem cells research: resurrection stem cells in the mouse intestine, which can be activated through injury . ( g ) Applications in microbiology: protocols for bacterial single-cell <t>transcriptomics</t> . ( h ). Single-cell transcriptome reveals drug resistance in cancer cells. ( i ) Integration and utilization of single-cell datasets: “anchor” different datasets together, which not only integrates single-cell sequencing data with different scRNA-seq technologies, but also integrates single-cell sequencing data with different modalities .
St Seq, 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/result/st-seq/product/Spatial Transcriptomics Inc
Average 90 stars, based on 1 article reviews
st-seq - by Bioz Stars, 2026-04
90/100 stars
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raw count matrix data of the st-seq dataset  (10X Genomics)
90
10X Genomics raw count matrix data of the st-seq dataset
Applications of single-cell transcriptome sequencing in different fields. ( a ) Large-scale cell mapping construction, the first whole-body organellar transcriptome mapping in a non-human primate, the rhesus macaque . ( b ) Oncology research: pan-cancer analyses on bone marrow cells from 210 patients with 15 different human cancer types using single-cell transcriptome sequencing . ( c ) Neuroscience research: hippocampus of humans, rhesus monkeys, and pigs . ( d ) Developmental biology: human prefrontal cortex gene expression from gestation to adulthood , embryo and Arabidopsis leaves . ( e ) Cell subpopulation refinement and rare cell type identification: liver and kidney . ( f ) Stem cells research: resurrection stem cells in the mouse intestine, which can be activated through injury . ( g ) Applications in microbiology: protocols for bacterial single-cell <t>transcriptomics</t> . ( h ). Single-cell transcriptome reveals drug resistance in cancer cells. ( i ) Integration and utilization of single-cell datasets: “anchor” different datasets together, which not only integrates single-cell sequencing data with different scRNA-seq technologies, but also integrates single-cell sequencing data with different modalities .
Raw Count Matrix Data Of The St Seq Dataset, supplied by 10X Genomics, 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/result/raw count matrix data of the st-seq dataset/product/10X Genomics
Average 90 stars, based on 1 article reviews
raw count matrix data of the st-seq dataset - by Bioz Stars, 2026-04
90/100 stars
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st-seq dataset  (10X Genomics)
90
10X Genomics st-seq dataset
Applications of single-cell transcriptome sequencing in different fields. ( a ) Large-scale cell mapping construction, the first whole-body organellar transcriptome mapping in a non-human primate, the rhesus macaque . ( b ) Oncology research: pan-cancer analyses on bone marrow cells from 210 patients with 15 different human cancer types using single-cell transcriptome sequencing . ( c ) Neuroscience research: hippocampus of humans, rhesus monkeys, and pigs . ( d ) Developmental biology: human prefrontal cortex gene expression from gestation to adulthood , embryo and Arabidopsis leaves . ( e ) Cell subpopulation refinement and rare cell type identification: liver and kidney . ( f ) Stem cells research: resurrection stem cells in the mouse intestine, which can be activated through injury . ( g ) Applications in microbiology: protocols for bacterial single-cell <t>transcriptomics</t> . ( h ). Single-cell transcriptome reveals drug resistance in cancer cells. ( i ) Integration and utilization of single-cell datasets: “anchor” different datasets together, which not only integrates single-cell sequencing data with different scRNA-seq technologies, but also integrates single-cell sequencing data with different modalities .
St Seq Dataset, supplied by 10X Genomics, 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/result/st-seq dataset/product/10X Genomics
Average 90 stars, based on 1 article reviews
st-seq dataset - by Bioz Stars, 2026-04
90/100 stars
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st-seq data sets  (10X Genomics)
90
10X Genomics st-seq data sets
Applications of single-cell transcriptome sequencing in different fields. ( a ) Large-scale cell mapping construction, the first whole-body organellar transcriptome mapping in a non-human primate, the rhesus macaque . ( b ) Oncology research: pan-cancer analyses on bone marrow cells from 210 patients with 15 different human cancer types using single-cell transcriptome sequencing . ( c ) Neuroscience research: hippocampus of humans, rhesus monkeys, and pigs . ( d ) Developmental biology: human prefrontal cortex gene expression from gestation to adulthood , embryo and Arabidopsis leaves . ( e ) Cell subpopulation refinement and rare cell type identification: liver and kidney . ( f ) Stem cells research: resurrection stem cells in the mouse intestine, which can be activated through injury . ( g ) Applications in microbiology: protocols for bacterial single-cell <t>transcriptomics</t> . ( h ). Single-cell transcriptome reveals drug resistance in cancer cells. ( i ) Integration and utilization of single-cell datasets: “anchor” different datasets together, which not only integrates single-cell sequencing data with different scRNA-seq technologies, but also integrates single-cell sequencing data with different modalities .
St Seq Data Sets, supplied by 10X Genomics, 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/result/st-seq data sets/product/10X Genomics
Average 90 stars, based on 1 article reviews
st-seq data sets - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

Image Search Results


The patient characteristics ( a ) of the six ccRCC patients ( n = 3 LG and n = 3 HG) include: patient LG_2 with a vena cava thrombus (VCT) for which we collected primary tumour microenvironment (TME) and thrombi separately but processed in the one capture array for ST-seq; patient HG_1 that we collected and processed tissues from para-TME (pTME) and TME; and patient HG_3 that we collected tissues from pTME and TME. For this experimental workflow ( b ), ten tissue regions were sampled from pTME, TME and VCT that excluded fibrotic and necrotic regions. ST-seq was completed using 10x Genomics Visium Gene Expression microarrayed glass slides with unique spatially barcoded ST-spots that captured the mRNA released from the overlaying thin ccRCC tissue sections. Annotation of immune ST-spots was completed with data integration of six published single-cell RNA-sequencing (scRNA-seq) datasets. Further immune cell sub-typing was completed with a scRNA and T-cell receptor (TCR) sequencing dataset. Integrated analysis was completed on CD8 + T cells, TAM and monocytes.

Journal: NPJ Precision Oncology

Article Title: High risk clear cell renal cell carcinoma microenvironments contain protumour immunophenotypes lacking specific immune checkpoints

doi: 10.1038/s41698-023-00441-5

Figure Lengend Snippet: The patient characteristics ( a ) of the six ccRCC patients ( n = 3 LG and n = 3 HG) include: patient LG_2 with a vena cava thrombus (VCT) for which we collected primary tumour microenvironment (TME) and thrombi separately but processed in the one capture array for ST-seq; patient HG_1 that we collected and processed tissues from para-TME (pTME) and TME; and patient HG_3 that we collected tissues from pTME and TME. For this experimental workflow ( b ), ten tissue regions were sampled from pTME, TME and VCT that excluded fibrotic and necrotic regions. ST-seq was completed using 10x Genomics Visium Gene Expression microarrayed glass slides with unique spatially barcoded ST-spots that captured the mRNA released from the overlaying thin ccRCC tissue sections. Annotation of immune ST-spots was completed with data integration of six published single-cell RNA-sequencing (scRNA-seq) datasets. Further immune cell sub-typing was completed with a scRNA and T-cell receptor (TCR) sequencing dataset. Integrated analysis was completed on CD8 + T cells, TAM and monocytes.

Article Snippet: This study profiled the immunophenotypes within the ccRCC TME from six consenting patients, using Visium ST-seq (10x Genomics) (Fig. and Table ).

Techniques: Gene Expression, RNA Sequencing, Sequencing

Applications of single-cell transcriptome sequencing in different fields. ( a ) Large-scale cell mapping construction, the first whole-body organellar transcriptome mapping in a non-human primate, the rhesus macaque . ( b ) Oncology research: pan-cancer analyses on bone marrow cells from 210 patients with 15 different human cancer types using single-cell transcriptome sequencing . ( c ) Neuroscience research: hippocampus of humans, rhesus monkeys, and pigs . ( d ) Developmental biology: human prefrontal cortex gene expression from gestation to adulthood , embryo and Arabidopsis leaves . ( e ) Cell subpopulation refinement and rare cell type identification: liver and kidney . ( f ) Stem cells research: resurrection stem cells in the mouse intestine, which can be activated through injury . ( g ) Applications in microbiology: protocols for bacterial single-cell transcriptomics . ( h ). Single-cell transcriptome reveals drug resistance in cancer cells. ( i ) Integration and utilization of single-cell datasets: “anchor” different datasets together, which not only integrates single-cell sequencing data with different scRNA-seq technologies, but also integrates single-cell sequencing data with different modalities .

Journal: Biology

Article Title: The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research

doi: 10.3390/biology13060451

Figure Lengend Snippet: Applications of single-cell transcriptome sequencing in different fields. ( a ) Large-scale cell mapping construction, the first whole-body organellar transcriptome mapping in a non-human primate, the rhesus macaque . ( b ) Oncology research: pan-cancer analyses on bone marrow cells from 210 patients with 15 different human cancer types using single-cell transcriptome sequencing . ( c ) Neuroscience research: hippocampus of humans, rhesus monkeys, and pigs . ( d ) Developmental biology: human prefrontal cortex gene expression from gestation to adulthood , embryo and Arabidopsis leaves . ( e ) Cell subpopulation refinement and rare cell type identification: liver and kidney . ( f ) Stem cells research: resurrection stem cells in the mouse intestine, which can be activated through injury . ( g ) Applications in microbiology: protocols for bacterial single-cell transcriptomics . ( h ). Single-cell transcriptome reveals drug resistance in cancer cells. ( i ) Integration and utilization of single-cell datasets: “anchor” different datasets together, which not only integrates single-cell sequencing data with different scRNA-seq technologies, but also integrates single-cell sequencing data with different modalities .

Article Snippet: Although Spatial Transcriptomics (ST-seq) can obtain both spatial location information and the gene expression data of cells, it currently falls short of single-cell precision.

Techniques: Sequencing, Gene Expression, Single-cell Transcriptomics