spatial transcriptome sequencing (st-seq) dataset Search Results


86
Spatial Transcriptomics Inc st seq
St 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+transcriptome+sequencing+(st-seq)+dataset/seq+st/pmc12528271-58-16-0
Average 86 stars, based on 1 article reviews
st seq - by Bioz Stars, 2026-10
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86
10X Genomics st seq dataset
St Seq Dataset, 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+transcriptome+sequencing+(st-seq)+dataset/dataset+seq+st/pm39450547-167-7-9
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86
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: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatial+transcriptome+sequencing+(st-seq)+dataset/st+technology+visium/pmc10495390-39-14-16
Average 86 stars, based on 1 article reviews
visium st seq - by Bioz Stars, 2026-10
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90
MCLAB Inc srveaedvgiyy
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.
Srveaedvgiyy, supplied by MCLAB 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+transcriptome+sequencing+(st-seq)+dataset/srveaedvgiyy/us11357849-1230-122-128
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86
10X Genomics visium st seq method
Fig. 1 Schematic of patient characteristics and experiment workflow. 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 Method, 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+transcriptome+sequencing+(st-seq)+dataset/expression+gene+slides+spatial+visium/pm37696903-120-3-11
Average 86 stars, based on 1 article reviews
visium st seq method - by Bioz Stars, 2026-10
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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

Fig. 1 Schematic of patient characteristics and experiment workflow. 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: Fig. 1 Schematic of patient characteristics and experiment workflow. 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: In brief, the Visium ST-seq method (CG000239 Rev D, 2020 October, 10x Genomics, USA) involved the use of microarrayed glass slides with 55 μm spots (or ST-spots) containing oligonucleotides with a sequence of deoxythymine (oligo-dT) and unique spatial barcodes printed within capture arrays.

Techniques: Gene Expression, RNA Sequencing, Sequencing