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10X Genomics visium spatial gene expression kit
Visium Spatial Gene Expression Kit, 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/visium+spatial+gene+expression+assay/pm42285969-332-29-34
Average 86 stars, based on 1 article reviews
visium spatial gene expression kit - by Bioz Stars, 2026-09
86/100 stars

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Article Title: Novel Spatial Approaches to Dissect the Lung Cancer Immune Microenvironment
Article Snippet: NGS-based methods allow us to map the sequencing data obtained by NGS in tissue; different approaches have been developed, including GeoMx DSP, oligonucleotide-based spatial barcoding on slides (Visium Spatial Gene Expression assay, 10x Genomics), and spatial barcoding on a bed array (Slide-seq, SeqScope, and Stereo-seq).

Imaging:

Article Title: Miniature spatial transcriptomics for studying parasite-endosymbiont relationships at the micro scale
Article Snippet: .. After imaging, the 10X Genomics Visium Spatial Gene Expression User Guide protocol was resumed from step 2.1.a using a Visium Spatial Gene Expression assay (10X Genomics) kit, with the modifications specified here. ..

Gene Expression:

Article Title: Miniature spatial transcriptomics for studying parasite-endosymbiont relationships at the micro scale
Article Snippet: .. After imaging, the 10X Genomics Visium Spatial Gene Expression User Guide protocol was resumed from step 2.1.a using a Visium Spatial Gene Expression assay (10X Genomics) kit, with the modifications specified here. ..

Article Title: Granzyme K + CD8 + T cells interact with fibroblasts to promote neutrophilic inflammation in nasal polyps.
Article Snippet: .. Spatial transcriptomics (ST) using Visium platform We employed the Visium Spatial Gene Expression assay (Visium, 10x Genomics) to obtain spatially-resolved gene expression data of CIT and NP samples according to Visium Spatial Gene Expression User Guide (CG000239 Rev F, 10x Genomics). ..

Article Title: Granzyme K + CD8 + T cells interact with fibroblasts to promote neutrophilic inflammation in nasal polyps
Article Snippet: .. We employed the Visium Spatial Gene Expression assay (Visium, 10x Genomics) to obtain spatially-resolved gene expression data of CIT and NP samples according to Visium Spatial Gene Expression User Guide (CG000239 Rev F, 10x Genomics). ..

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

Article Title: Effects of SSRIs on the spatial transcriptome of dorsal raphe serotonin neurons.
Article Snippet: .. Visium spatial gene expression assay (10x Genomics) was performed following manufacturer’s protocols. ..

Article Title: Spatial transcriptomics implicates the thalamus and cortex in autism and schizophrenia
Article Snippet: We mounted 4 such sections from 1 brain on a Visium Spatial Gene Expression Slide (10x Genomics, 1000187) and stored at -80°C until further processing. .. Spatial transcriptomics analysis was performed using the 10x Genomics Visium Spatial Gene Expression Assay. ..

Spatial Transcriptomics:

Article Title: Granzyme K + CD8 + T cells interact with fibroblasts to promote neutrophilic inflammation in nasal polyps.
Article Snippet: .. Spatial transcriptomics (ST) using Visium platform We employed the Visium Spatial Gene Expression assay (Visium, 10x Genomics) to obtain spatially-resolved gene expression data of CIT and NP samples according to Visium Spatial Gene Expression User Guide (CG000239 Rev F, 10x Genomics). ..

Article Title: Spatial transcriptomics implicates the thalamus and cortex in autism and schizophrenia
Article Snippet: We mounted 4 such sections from 1 brain on a Visium Spatial Gene Expression Slide (10x Genomics, 1000187) and stored at -80°C until further processing. .. Spatial transcriptomics analysis was performed using the 10x Genomics Visium Spatial Gene Expression Assay. ..

Selection:

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

Formalin-fixed Paraffin-Embedded:

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

Immunohistochemistry:

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

Immunofluorescence:

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

Expressing:

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

RNA sequencing:

Article Title: Tertiary lymphoid structures and B cells determine clinically relevant T cell phenotypes in ovarian cancer
Article Snippet: .. For the analysis of human tumor TLSs by the Visium spatial gene expression assay (10x Genomics), 4 selection steps were used on samples with available FFPE material: (1) TLS were identified by IHC for CD20 and DC-LAMP on whole FFPE sections, (2) IHC data were confirmed by multispectral immunofluorescence panel 1 and 2 (see section immunofluorescence) on whole FFPE sections, (3) TLS positivity was validated by the expression of the so-called “12-chemokines signature” ( CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11 , and CXCL13) , from bulk RNAseq data, and (4) finally, to estimate the relative abundance of immune cell populations, we used “metagene” markers , . ..

cDNA Synthesis:

Article Title: Miniature spatial transcriptomics for studying parasite-endosymbiont relationships at the micro scale.
Article Snippet: .. All brightfield images were taken with a Camera Gain of 1.0 and an Integration Time/Exposure time of 0.00004-0.00008 seconds. cDNA synthesis & library construction After imaging, the 10X Genomics Visium Spatial Gene Expression User Guide39 protocol was resumed from step 2.1.a using a Visium Spatial Gene Expression assay (10X Genomics) kit, with the modifications specified here. ..



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This figure summarizes the machine learning-guided workflow used to define tumor, boundary, and stromal domains in hepatocellular carcinoma specimens. ( a) Study workflow. Eleven treatment-naive HCC resection specimens, including seven HBV-related and four non-B non-C cases, were profiled <t>using</t> <t>10x</t> <t>Visium</t> spatial transcriptomics. CancerFinder was used to estimate spot-level malignancy probability, SpaceFlow was used for spatially regularized clustering, and the resulting outputs were integrated with histologic review to define three spatial domains: Tumor, Boundary, and Stroma. A signed distance-to-border axis was constructed for continuous spatial gradient analyses. ( b) Hematoxylin and eosin-stained sections from representative HBV-related and NBNC specimens. ( c) CancerFinder-derived cancer/normal classification maps for the same specimens. Blue indicates normal or low-malignancy-probability regions, and orange indicates cancer or high-malignancy-probability regions. ( d) Integrated three-domain spatial annotation maps. Dark red indicates Boundary, cyan indicates Stroma, and dark blue indicates Tumor. ( e) Boxplots of estimated malignant cell proportion across ordered spatial subdomains in the representative specimens. The red line indicates mean distance from the tumor for each subdomain, supporting concordance between the inferred malignancy gradient and the spatial domain hierarchy.
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Average 86 stars, based on 1 article reviews
visium spatial gene expression slide kit - by Bioz Stars, 2026-09
86/100 stars
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Image Search Results


This figure summarizes the machine learning-guided workflow used to define tumor, boundary, and stromal domains in hepatocellular carcinoma specimens. ( a) Study workflow. Eleven treatment-naive HCC resection specimens, including seven HBV-related and four non-B non-C cases, were profiled using 10x Visium spatial transcriptomics. CancerFinder was used to estimate spot-level malignancy probability, SpaceFlow was used for spatially regularized clustering, and the resulting outputs were integrated with histologic review to define three spatial domains: Tumor, Boundary, and Stroma. A signed distance-to-border axis was constructed for continuous spatial gradient analyses. ( b) Hematoxylin and eosin-stained sections from representative HBV-related and NBNC specimens. ( c) CancerFinder-derived cancer/normal classification maps for the same specimens. Blue indicates normal or low-malignancy-probability regions, and orange indicates cancer or high-malignancy-probability regions. ( d) Integrated three-domain spatial annotation maps. Dark red indicates Boundary, cyan indicates Stroma, and dark blue indicates Tumor. ( e) Boxplots of estimated malignant cell proportion across ordered spatial subdomains in the representative specimens. The red line indicates mean distance from the tumor for each subdomain, supporting concordance between the inferred malignancy gradient and the spatial domain hierarchy.

Journal: bioRxiv

Article Title: Spatial Transcriptomics Reveals a Conserved Border Niche and Etiology-Associated Immune Rewiring in Hepatocellular Carcinoma

doi: 10.64898/2026.06.02.729569

Figure Lengend Snippet: This figure summarizes the machine learning-guided workflow used to define tumor, boundary, and stromal domains in hepatocellular carcinoma specimens. ( a) Study workflow. Eleven treatment-naive HCC resection specimens, including seven HBV-related and four non-B non-C cases, were profiled using 10x Visium spatial transcriptomics. CancerFinder was used to estimate spot-level malignancy probability, SpaceFlow was used for spatially regularized clustering, and the resulting outputs were integrated with histologic review to define three spatial domains: Tumor, Boundary, and Stroma. A signed distance-to-border axis was constructed for continuous spatial gradient analyses. ( b) Hematoxylin and eosin-stained sections from representative HBV-related and NBNC specimens. ( c) CancerFinder-derived cancer/normal classification maps for the same specimens. Blue indicates normal or low-malignancy-probability regions, and orange indicates cancer or high-malignancy-probability regions. ( d) Integrated three-domain spatial annotation maps. Dark red indicates Boundary, cyan indicates Stroma, and dark blue indicates Tumor. ( e) Boxplots of estimated malignant cell proportion across ordered spatial subdomains in the representative specimens. The red line indicates mean distance from the tumor for each subdomain, supporting concordance between the inferred malignancy gradient and the spatial domain hierarchy.

Article Snippet: Specimens were OCT-embedded, snap-frozen, and cryosectioned at 10 um onto Visium Spatial Gene Expression slides (10x Genomics).

Techniques: Spatial Transcriptomics, Construct, Staining, Derivative Assay