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stereo-seq transcriptomics set  (Complete Genomics Inc)


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    Structured Review

    Complete Genomics Inc stereo-seq transcriptomics set
    Stereo Seq Transcriptomics Set, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 123 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/seq/Stereo-seq+Transcriptomics+Set/custom%40111st122%4042824453
    Average 99 stars, based on 123 article reviews
    stereo-seq transcriptomics set - by Bioz Stars, 2026-10
    99/100 stars

    Images

    Related Articles

    Bulk RNA Sequencing:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K

    Spatial & Multi-Omics:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K

    Epigenomics & Chromatin Profiling:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K

    Single-Cell Sequencing:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K

    Targeted Sequencing:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K

    Whole-Exome Sequencing:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K

    Metagenomics & Microbiome:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: two serial sections were prepared for analysis. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N K



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    Image Search Results


    ( A ) Bulk RNA-seq data are used to translate between clinical samples (in vivo) with phenotypic annotations and an MPS model of disease (in vitro). ( B ) The MASLD score (MAS) and fibrosis stage are clinically relevant metrics of disease that correlate and need to be modeled jointly. ( C ) A PLSR model predicts both phenotypes from bulk transcriptomics and performs significantly better in 10-fold cross-validation than random or shuffled models. For all comparisons, a two-sided unpaired Wilcoxon test was used. In all box plots, the centerline denotes the median, the bounds of the box denote the first and third quantiles, and the whiskers denote points not being further from the median than 1.5 × interquartile range. ( D ) The PLSR model with eight LVs fits the full clinical dataset well and achieves good correlations with the measured phenotypes. ( E ) Qualitative trends in the phenotypic scores are visible when projecting the clinical data onto the first two LVs of the PLSR model.

    Journal: Science Advances

    Article Title: Systems biology framework for the rational design of operational conditions for in vitro/in vivo translation of tissue models

    doi: 10.1126/sciadv.aef7756

    Figure Lengend Snippet: ( A ) Bulk RNA-seq data are used to translate between clinical samples (in vivo) with phenotypic annotations and an MPS model of disease (in vitro). ( B ) The MASLD score (MAS) and fibrosis stage are clinically relevant metrics of disease that correlate and need to be modeled jointly. ( C ) A PLSR model predicts both phenotypes from bulk transcriptomics and performs significantly better in 10-fold cross-validation than random or shuffled models. For all comparisons, a two-sided unpaired Wilcoxon test was used. In all box plots, the centerline denotes the median, the bounds of the box denote the first and third quantiles, and the whiskers denote points not being further from the median than 1.5 × interquartile range. ( D ) The PLSR model with eight LVs fits the full clinical dataset well and achieves good correlations with the measured phenotypes. ( E ) Qualitative trends in the phenotypic scores are visible when projecting the clinical data onto the first two LVs of the PLSR model.

    Article Snippet: Purified RNA was sent to Plasmidsaurus for bulk RNA-seq using the Illumina sequencing technology.

    Techniques: RNA Sequencing, In Vivo, In Vitro, Transcriptomics, Biomarker Discovery

    ( A ) Schematic of validation liver triculture spheroid experiments. Hepatocytes, Kupffer cells, and hepatic stellate cells were seeded in a 10:1:1 ratio in alginate wells and cultured for 11 days. Treatments were initiated on day 3 (D3) and replenished with each medium change. ( B and C ) Quantification of spheroid phenotypes shows that TGFβ1 (10 ng/ml) decreased steatosis, as measured by normalized BODIPY signal (B), while increasing fibrosis, measured by α-SMA in vimentin-positive areas (C). Cotreatment with IFN-α (1000 U/ml) reduced lipid content further and restored α-SMA to baseline expression. a.u., arbitrary units. ( D ) Bulk RNA-seq performed on parallel spheroid cultures reveals strong transcriptional differences associated with the experimental treatments, as evidenced by PCA. ( E ) Pathway activity inference confirms a TGFβ signature associated with PC1 and a JAK-STAT signature associated with PC2. ( F ) Projection of the gene expression data onto TC1 and extra LV 1 preserves clustering by experimental condition. Imaging data are presented as a ratio normalized to the median of the control group. Each point represents an individual spheroid. In all panels, asterisks indicate statistical significance level defined as follows: **** P ≤ 10 –4 , *** P ≤ 10 –3 , and ns for P > 0.05.

    Journal: Science Advances

    Article Title: Systems biology framework for the rational design of operational conditions for in vitro/in vivo translation of tissue models

    doi: 10.1126/sciadv.aef7756

    Figure Lengend Snippet: ( A ) Schematic of validation liver triculture spheroid experiments. Hepatocytes, Kupffer cells, and hepatic stellate cells were seeded in a 10:1:1 ratio in alginate wells and cultured for 11 days. Treatments were initiated on day 3 (D3) and replenished with each medium change. ( B and C ) Quantification of spheroid phenotypes shows that TGFβ1 (10 ng/ml) decreased steatosis, as measured by normalized BODIPY signal (B), while increasing fibrosis, measured by α-SMA in vimentin-positive areas (C). Cotreatment with IFN-α (1000 U/ml) reduced lipid content further and restored α-SMA to baseline expression. a.u., arbitrary units. ( D ) Bulk RNA-seq performed on parallel spheroid cultures reveals strong transcriptional differences associated with the experimental treatments, as evidenced by PCA. ( E ) Pathway activity inference confirms a TGFβ signature associated with PC1 and a JAK-STAT signature associated with PC2. ( F ) Projection of the gene expression data onto TC1 and extra LV 1 preserves clustering by experimental condition. Imaging data are presented as a ratio normalized to the median of the control group. Each point represents an individual spheroid. In all panels, asterisks indicate statistical significance level defined as follows: **** P ≤ 10 –4 , *** P ≤ 10 –3 , and ns for P > 0.05.

    Article Snippet: Purified RNA was sent to Plasmidsaurus for bulk RNA-seq using the Illumina sequencing technology.

    Techniques: Biomarker Discovery, Cell Culture, Expressing, RNA Sequencing, Activity Assay, Gene Expression, Imaging, Control