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stereo-seq transcriptomics set for chip-on-a-slide  (Complete Genomics Inc)


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    Structured Review

    Complete Genomics Inc stereo-seq transcriptomics set for chip-on-a-slide
    Stereo Seq Transcriptomics Set For Chip On A Slide, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 119 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/transcriptome/Stereo-seq+Transcriptomics+Set+for+Chip-on-a-slide/custom%40211st114%4042413505
    Average 99 stars, based on 119 article reviews
    stereo-seq transcriptomics set for chip-on-a-slide - by Bioz Stars, 2026-09
    99/100 stars

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    Related Articles

    Sequencing:

    Article Title: Serum metabolic profiling analysis of Gitelman syndrome using untargeted metabolomics
    Article Snippet: Additionally, the study complied with the regulations issued by the Ministry of Science and Technology of the People′s Republic of China regarding the review and approval of human genetic resources. .. Whole-exome sequencing (WES) was performed on all patients using the MGISEQ-2000 platform (MGI Tech) and validated by Sanger sequencing. .. Variants were filtered and annotated using the following databases: 1000 Genomes Project ( http://www.1000genomes.org ), Genome Aggregation Database (gnomAD) ( http://gnomad-old.broadinstitute.org ), ClinVar ( https://www.ncbi.nlm.nih.gov/clinvar/ ), Online Mendelian Inheritance in Man (OMIM) ( http://omim.org/ ), and the Human Gene Mutation Database (HGMD) ( http://www.biobase-international.com/product/hgmd ).

    Article Title: Natural Variations of ZmRLR1 Mediate the Root Lodging Resistance of Maize by Regulating Root Ascorbate and Auxin Homeostasis
    Article Snippet: .. Transcriptome sequencing was performed using the BGI DNBSEQ‐T7 high‐throughput sequencing platform by the Hainan Huada Gene Technology Co., Ltd. (Sanya, China). ..

    Single Cell:

    Article Title: Stereo-cell deciphers the spatial and functional heterogeneity of polyploid hepatocytes.
    Article Snippet: .. 349 350 Stereo chip preprocessing for hepatocyte loading and microimaging 351 The manufacturer's kits were used (Stereo-seq Spatiotemporal Single Cell Transcriptome 352 Reagent Kit, STOmics, STC1000R; Stereo-seq Spatiotemporal Single Cell Barcode 353 Amplification Reagent Kit, STOmics, STC1000P), and the experimental procedures were 354 performed according to the previously reported protocol[33]. ..

    Amplification:

    Article Title: Stereo-cell deciphers the spatial and functional heterogeneity of polyploid hepatocytes.
    Article Snippet: .. 349 350 Stereo chip preprocessing for hepatocyte loading and microimaging 351 The manufacturer's kits were used (Stereo-seq Spatiotemporal Single Cell Transcriptome 352 Reagent Kit, STOmics, STC1000R; Stereo-seq Spatiotemporal Single Cell Barcode 353 Amplification Reagent Kit, STOmics, STC1000P), and the experimental procedures were 354 performed according to the previously reported protocol[33]. ..

    Next-Generation Sequencing:

    Article Title: Natural Variations of ZmRLR1 Mediate the Root Lodging Resistance of Maize by Regulating Root Ascorbate and Auxin Homeostasis
    Article Snippet: .. Transcriptome sequencing was performed using the BGI DNBSEQ‐T7 high‐throughput sequencing platform by the Hainan Huada Gene Technology Co., Ltd. (Sanya, China). ..

    Magnetic Beads:

    Article Title: Sanyin decoction alleviates psoriasis by reshaping gut microbiota and modulating the gut–spleen–skin axis
    Article Snippet: .. High-quality RNA was subsequently used for transcriptome library construction using the MGIEasy Fast RNA Reagent (MGI, 940-002921-00), mRNA was enriched using oligo (dT) magnetic beads, followed by fragmentation with fragmentation buffer at a controlled temperature. ..



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    <t>Transcriptomic</t> and TME characteristics associated with ECMSig in TCGA-GBM cohort (A) Volcano plot showing DEGs between ECMSig-high and ECMSig-low groups. Red dots: upregulated in high-risk; blue dots: upregulated in low-risk. Benjamini-Hochberg adjusted. (B) Gene set enrichment analysis (GSEA) plots showing enrichment of hallmark pathways. Pathways enriched in ECMSig-high and ECMSig-low groups are shown with their running enrichment scores (ESs) and ranked gene lists. Benjamini-Hochberg adjusted. (C) Heatmap showing the activity scores of selected oncogenic and tumor-related signaling pathways (rows) across TCGA-GBM samples (columns), annotated by ECMSig group and ECMSig score. Red indicates high activity, blue indicates low activity. ∗ p < 0.05. Wilcoxon signed-rank test. (D) Heatmap depicting the estimated infiltration levels of various immune and stromal cell types (rows) in TCGA-GBM samples (columns), stratified by ECMSig group and score. Red indicates high infiltration, blue indicates low infiltration. Cells significantly highly infiltrated in ECMSig-high are labeled in red, and those high in ECMSig-low group are in blue. ∗q < 0.05, ∗∗q < 0.01, ∗∗∗q < 0.001. Wilcoxon signed-rank test. Benjamini-Hochberg adjusted. (E and F) Scatterplots showing the spearman correlation between ECMSig score and (E) Macrophage_XCELL infiltration score and (F) immune_score_XCELL. The blue line represents the linear regression fit with 95% confidence interval bands. Spearman correlation test.
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    Image Search Results


    Transcriptomic and TME characteristics associated with ECMSig in TCGA-GBM cohort (A) Volcano plot showing DEGs between ECMSig-high and ECMSig-low groups. Red dots: upregulated in high-risk; blue dots: upregulated in low-risk. Benjamini-Hochberg adjusted. (B) Gene set enrichment analysis (GSEA) plots showing enrichment of hallmark pathways. Pathways enriched in ECMSig-high and ECMSig-low groups are shown with their running enrichment scores (ESs) and ranked gene lists. Benjamini-Hochberg adjusted. (C) Heatmap showing the activity scores of selected oncogenic and tumor-related signaling pathways (rows) across TCGA-GBM samples (columns), annotated by ECMSig group and ECMSig score. Red indicates high activity, blue indicates low activity. ∗ p < 0.05. Wilcoxon signed-rank test. (D) Heatmap depicting the estimated infiltration levels of various immune and stromal cell types (rows) in TCGA-GBM samples (columns), stratified by ECMSig group and score. Red indicates high infiltration, blue indicates low infiltration. Cells significantly highly infiltrated in ECMSig-high are labeled in red, and those high in ECMSig-low group are in blue. ∗q < 0.05, ∗∗q < 0.01, ∗∗∗q < 0.001. Wilcoxon signed-rank test. Benjamini-Hochberg adjusted. (E and F) Scatterplots showing the spearman correlation between ECMSig score and (E) Macrophage_XCELL infiltration score and (F) immune_score_XCELL. The blue line represents the linear regression fit with 95% confidence interval bands. Spearman correlation test.

    Journal: iScience

    Article Title: Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis

    doi: 10.1016/j.isci.2026.115982

    Figure Lengend Snippet: Transcriptomic and TME characteristics associated with ECMSig in TCGA-GBM cohort (A) Volcano plot showing DEGs between ECMSig-high and ECMSig-low groups. Red dots: upregulated in high-risk; blue dots: upregulated in low-risk. Benjamini-Hochberg adjusted. (B) Gene set enrichment analysis (GSEA) plots showing enrichment of hallmark pathways. Pathways enriched in ECMSig-high and ECMSig-low groups are shown with their running enrichment scores (ESs) and ranked gene lists. Benjamini-Hochberg adjusted. (C) Heatmap showing the activity scores of selected oncogenic and tumor-related signaling pathways (rows) across TCGA-GBM samples (columns), annotated by ECMSig group and ECMSig score. Red indicates high activity, blue indicates low activity. ∗ p < 0.05. Wilcoxon signed-rank test. (D) Heatmap depicting the estimated infiltration levels of various immune and stromal cell types (rows) in TCGA-GBM samples (columns), stratified by ECMSig group and score. Red indicates high infiltration, blue indicates low infiltration. Cells significantly highly infiltrated in ECMSig-high are labeled in red, and those high in ECMSig-low group are in blue. ∗q < 0.05, ∗∗q < 0.01, ∗∗∗q < 0.001. Wilcoxon signed-rank test. Benjamini-Hochberg adjusted. (E and F) Scatterplots showing the spearman correlation between ECMSig score and (E) Macrophage_XCELL infiltration score and (F) immune_score_XCELL. The blue line represents the linear regression fit with 95% confidence interval bands. Spearman correlation test.

    Article Snippet: The single-cell transcriptomic sequencing dataset utilizing technology from the 10X Genomics platform was available under the accession number GEO: GSE182109 at the Gene Expression Omnibus (GEO) repository.

    Techniques: Activity Assay, Protein-Protein interactions, Labeling

    Single-cell RNA sequencing analysis revealing ECMSig expression across cell types and identification of prognostically relevant cell states in GBM (A) UMAP visualization of major cell types identified in GBM scRNA-seq data. (B) Dot plot showing the scaled average expression (color intensity) and percentage of cells expressing (dot size) canonical marker genes for each major cell type. (C) Dot plot showing the scaled average expression and percentage of cells expressing the seven ECMSig genes across major cell types. (D) UMAP plots showing the expression levels of individual ECMSig genes and overall ECMSig score across all cells. (E–G) UMAP plots illustrating Scissor-identified prognostically unfavorable (Scissor_Pos, red dashed circle) and favorable (Scissor_Neg, blue dashed circle; Scissor_Others, gray) cell subpopulations within (E) tumor cells, (F) myeloid cells, and (G) endothelial cells. (H–K) Violin plots comparing ECMSig scores among tumor cells grouped by Scissor status (H) and tumor type (I), and myeloid cells (J) or endothelial cells (K) grouped by Scissor status. ∗∗∗∗ p < 0.0001. Wilcoxon signed-rank test. (L) Dot plot showing differentially expressed marker genes between myeloid Scissor_Pos and other myeloid cells. Dot size indicates the fraction of cells in the group expressing the gene; color indicates average expression level.

    Journal: iScience

    Article Title: Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis

    doi: 10.1016/j.isci.2026.115982

    Figure Lengend Snippet: Single-cell RNA sequencing analysis revealing ECMSig expression across cell types and identification of prognostically relevant cell states in GBM (A) UMAP visualization of major cell types identified in GBM scRNA-seq data. (B) Dot plot showing the scaled average expression (color intensity) and percentage of cells expressing (dot size) canonical marker genes for each major cell type. (C) Dot plot showing the scaled average expression and percentage of cells expressing the seven ECMSig genes across major cell types. (D) UMAP plots showing the expression levels of individual ECMSig genes and overall ECMSig score across all cells. (E–G) UMAP plots illustrating Scissor-identified prognostically unfavorable (Scissor_Pos, red dashed circle) and favorable (Scissor_Neg, blue dashed circle; Scissor_Others, gray) cell subpopulations within (E) tumor cells, (F) myeloid cells, and (G) endothelial cells. (H–K) Violin plots comparing ECMSig scores among tumor cells grouped by Scissor status (H) and tumor type (I), and myeloid cells (J) or endothelial cells (K) grouped by Scissor status. ∗∗∗∗ p < 0.0001. Wilcoxon signed-rank test. (L) Dot plot showing differentially expressed marker genes between myeloid Scissor_Pos and other myeloid cells. Dot size indicates the fraction of cells in the group expressing the gene; color indicates average expression level.

    Article Snippet: The single-cell transcriptomic sequencing dataset utilizing technology from the 10X Genomics platform was available under the accession number GEO: GSE182109 at the Gene Expression Omnibus (GEO) repository.

    Techniques: Single Cell, RNA Sequencing, Expressing, Marker

    Spatial transcriptomic analysis revealing co-localization of ECMSig, hypoxia, Scissor-Positive cells, and pericytes in GBM (A) Spatial feature plots for four GBM samples. Each row represents a sample. Columns show spatial heatmaps of: ECMSig score, hypoxia signature score, tumor Scissor_Pos signature score, myeloid Scissor_Pos signature score, endothelial Scissor Pos signature score, and pericyte marker signature score. Color scale indicates scaled expression or score (low to high). Each dot represents a spatial barcoded spot.

    Journal: iScience

    Article Title: Multi-omics profiling-derived signature links cellular ecosystem to glioblastoma prognosis

    doi: 10.1016/j.isci.2026.115982

    Figure Lengend Snippet: Spatial transcriptomic analysis revealing co-localization of ECMSig, hypoxia, Scissor-Positive cells, and pericytes in GBM (A) Spatial feature plots for four GBM samples. Each row represents a sample. Columns show spatial heatmaps of: ECMSig score, hypoxia signature score, tumor Scissor_Pos signature score, myeloid Scissor_Pos signature score, endothelial Scissor Pos signature score, and pericyte marker signature score. Color scale indicates scaled expression or score (low to high). Each dot represents a spatial barcoded spot.

    Article Snippet: The single-cell transcriptomic sequencing dataset utilizing technology from the 10X Genomics platform was available under the accession number GEO: GSE182109 at the Gene Expression Omnibus (GEO) repository.

    Techniques: Marker, Expressing