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ddseq single cell isolator  (Bio-Rad)


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    Bio-Rad ddseq single cell isolator
    Ddseq Single Cell Isolator, supplied by Bio-Rad, used in various techniques. Bioz Stars score: 94/100, based on 74 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/ddseq single cell isolator/product/Bio-Rad
    Average 94 stars, based on 74 article reviews
    ddseq single cell isolator - by Bioz Stars, 2026-04
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    Patient-derived organoids (PDOs) recapitulate transcriptional heterogeneity of primary pancreatic ductal adenocarcinoma (PDAC) and reveal recurrent programs (RPs). A and B Uniform manifold approximation and projections (UMAPs) <t>of</t> <t>single-cell</t> transcriptomes from 17 PDOs, analyzed sample by sample. The cells were clustered within each PDO, and UMAPs are shown separately for primary ( A ) and metastasis PDOs ( B ). C Pairwise similarity analysis of gene expression programs (GEPs) identified by consensus nonnegative matrix factorization (cNMF) across the 17 PDOs. The heatmap shows the pairwise similarity matrix of 108 GEPs, which was quantified using the Jaccard index, with hierarchical clustering revealing eight major clusters defined as RPs shared across multiple PDOs. The eight RP assignments and representative genes for each RP are shown on the right. D Heatmap showing the degree of gene-level overlap between the eight RPs that were identified in this study and the 14 GEPs that were previously reported from single-cell transcriptomic analysis of PDAC patient specimens. E Differential analysis of RP activity between primary and metastasis PDOs
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    Patient-derived organoids (PDOs) recapitulate transcriptional heterogeneity of primary pancreatic ductal adenocarcinoma (PDAC) and reveal recurrent programs (RPs). A and B Uniform manifold approximation and projections (UMAPs) <t>of</t> <t>single-cell</t> transcriptomes from 17 PDOs, analyzed sample by sample. The cells were clustered within each PDO, and UMAPs are shown separately for primary ( A ) and metastasis PDOs ( B ). C Pairwise similarity analysis of gene expression programs (GEPs) identified by consensus nonnegative matrix factorization (cNMF) across the 17 PDOs. The heatmap shows the pairwise similarity matrix of 108 GEPs, which was quantified using the Jaccard index, with hierarchical clustering revealing eight major clusters defined as RPs shared across multiple PDOs. The eight RP assignments and representative genes for each RP are shown on the right. D Heatmap showing the degree of gene-level overlap between the eight RPs that were identified in this study and the 14 GEPs that were previously reported from single-cell transcriptomic analysis of PDAC patient specimens. E Differential analysis of RP activity between primary and metastasis PDOs
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    Patient-derived organoids (PDOs) recapitulate transcriptional heterogeneity of primary pancreatic ductal adenocarcinoma (PDAC) and reveal recurrent programs (RPs). A and B Uniform manifold approximation and projections (UMAPs) <t>of</t> <t>single-cell</t> transcriptomes from 17 PDOs, analyzed sample by sample. The cells were clustered within each PDO, and UMAPs are shown separately for primary ( A ) and metastasis PDOs ( B ). C Pairwise similarity analysis of gene expression programs (GEPs) identified by consensus nonnegative matrix factorization (cNMF) across the 17 PDOs. The heatmap shows the pairwise similarity matrix of 108 GEPs, which was quantified using the Jaccard index, with hierarchical clustering revealing eight major clusters defined as RPs shared across multiple PDOs. The eight RP assignments and representative genes for each RP are shown on the right. D Heatmap showing the degree of gene-level overlap between the eight RPs that were identified in this study and the 14 GEPs that were previously reported from single-cell transcriptomic analysis of PDAC patient specimens. E Differential analysis of RP activity between primary and metastasis PDOs
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    Patient-derived organoids (PDOs) recapitulate transcriptional heterogeneity of primary pancreatic ductal adenocarcinoma (PDAC) and reveal recurrent programs (RPs). A and B Uniform manifold approximation and projections (UMAPs) of single-cell transcriptomes from 17 PDOs, analyzed sample by sample. The cells were clustered within each PDO, and UMAPs are shown separately for primary ( A ) and metastasis PDOs ( B ). C Pairwise similarity analysis of gene expression programs (GEPs) identified by consensus nonnegative matrix factorization (cNMF) across the 17 PDOs. The heatmap shows the pairwise similarity matrix of 108 GEPs, which was quantified using the Jaccard index, with hierarchical clustering revealing eight major clusters defined as RPs shared across multiple PDOs. The eight RP assignments and representative genes for each RP are shown on the right. D Heatmap showing the degree of gene-level overlap between the eight RPs that were identified in this study and the 14 GEPs that were previously reported from single-cell transcriptomic analysis of PDAC patient specimens. E Differential analysis of RP activity between primary and metastasis PDOs

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: Patient-derived orthotopic xenograft models recapitulate the peritoneal dissemination of pancreatic cancer and delineate its transcriptional and regulatory programs

    doi: 10.1186/s13046-026-03668-9

    Figure Lengend Snippet: Patient-derived organoids (PDOs) recapitulate transcriptional heterogeneity of primary pancreatic ductal adenocarcinoma (PDAC) and reveal recurrent programs (RPs). A and B Uniform manifold approximation and projections (UMAPs) of single-cell transcriptomes from 17 PDOs, analyzed sample by sample. The cells were clustered within each PDO, and UMAPs are shown separately for primary ( A ) and metastasis PDOs ( B ). C Pairwise similarity analysis of gene expression programs (GEPs) identified by consensus nonnegative matrix factorization (cNMF) across the 17 PDOs. The heatmap shows the pairwise similarity matrix of 108 GEPs, which was quantified using the Jaccard index, with hierarchical clustering revealing eight major clusters defined as RPs shared across multiple PDOs. The eight RP assignments and representative genes for each RP are shown on the right. D Heatmap showing the degree of gene-level overlap between the eight RPs that were identified in this study and the 14 GEPs that were previously reported from single-cell transcriptomic analysis of PDAC patient specimens. E Differential analysis of RP activity between primary and metastasis PDOs

    Article Snippet: scATAC-seq was performed as previously described [ ] using the ddSEQ Single-Cell Isolator (Bio-Rad) together with the ddSEQ Single-Cell ATAC-Seq Library Prep Kit (Bio-Rad) according to the manufacturer’s protocol.

    Techniques: Derivative Assay, Single Cell, Gene Expression, Activity Assay

    Single-cell multiomic analysis of the PDOX12 lineage revealing dissemination-associated transcriptional programs. A Schematic overview of the PDOX12 lineage used for single-nucleus RNA sequencing. The colors indicate the tissue origin: green circle, primary pancreatic lesion from PDOX12 (PDOX12-P); yellow circle, primary pancreatic lesion from PDOX12P (PDOX12P-P); gray circle, primary pancreatic lesion from PDOX12A (PDOX12A-P); violet circle, peritoneal metastatic lesion from PDOX12A (PDOX12A-A). B and C Uniform manifold approximation and projection (UMAP) visualization of 21,523 single-nucleus transcriptomes from the four tumors. Cells colored by cluster identity ( B ) and sample of origin ( C ). D Proportion of each cluster across the four tumors. E Number of cluster-specific differentially expressed genes (DEGs). F Representative examples of cluster-4 and cluster-1-specific DEGs expression on UMAPs. G UMAP visualization of single-cell ATAC sequencing (scATAC-seq) of PDOX12A-P and PDOX12A-A. Cells colored by sample of origin. H UMAPs colored by gene-activity scores for cluster-4-specific DEGs. I – K Integrative analysis of chromatin accessibility and transcriptional activity using scATAC-seq data. Correlations were calculated between the module scores (derived from gene activity scores of cluster-specific DEGs) and the motif activity scores across all single nuclei. I Example scatter plot showing the correlation between cluster-4-specific DEG module score and SOX2 motif activity score at the single-cell level. J Heatmap showing the correlation coefficients between each DEG module score and all transcription factor motif activity scores, identifying regulatory modules with shared motif-association patterns. K UMAP illustrating the representative motif activities correlated with the cluster-4-specific DEG modules

    Journal: Journal of Experimental & Clinical Cancer Research : CR

    Article Title: Patient-derived orthotopic xenograft models recapitulate the peritoneal dissemination of pancreatic cancer and delineate its transcriptional and regulatory programs

    doi: 10.1186/s13046-026-03668-9

    Figure Lengend Snippet: Single-cell multiomic analysis of the PDOX12 lineage revealing dissemination-associated transcriptional programs. A Schematic overview of the PDOX12 lineage used for single-nucleus RNA sequencing. The colors indicate the tissue origin: green circle, primary pancreatic lesion from PDOX12 (PDOX12-P); yellow circle, primary pancreatic lesion from PDOX12P (PDOX12P-P); gray circle, primary pancreatic lesion from PDOX12A (PDOX12A-P); violet circle, peritoneal metastatic lesion from PDOX12A (PDOX12A-A). B and C Uniform manifold approximation and projection (UMAP) visualization of 21,523 single-nucleus transcriptomes from the four tumors. Cells colored by cluster identity ( B ) and sample of origin ( C ). D Proportion of each cluster across the four tumors. E Number of cluster-specific differentially expressed genes (DEGs). F Representative examples of cluster-4 and cluster-1-specific DEGs expression on UMAPs. G UMAP visualization of single-cell ATAC sequencing (scATAC-seq) of PDOX12A-P and PDOX12A-A. Cells colored by sample of origin. H UMAPs colored by gene-activity scores for cluster-4-specific DEGs. I – K Integrative analysis of chromatin accessibility and transcriptional activity using scATAC-seq data. Correlations were calculated between the module scores (derived from gene activity scores of cluster-specific DEGs) and the motif activity scores across all single nuclei. I Example scatter plot showing the correlation between cluster-4-specific DEG module score and SOX2 motif activity score at the single-cell level. J Heatmap showing the correlation coefficients between each DEG module score and all transcription factor motif activity scores, identifying regulatory modules with shared motif-association patterns. K UMAP illustrating the representative motif activities correlated with the cluster-4-specific DEG modules

    Article Snippet: scATAC-seq was performed as previously described [ ] using the ddSEQ Single-Cell Isolator (Bio-Rad) together with the ddSEQ Single-Cell ATAC-Seq Library Prep Kit (Bio-Rad) according to the manufacturer’s protocol.

    Techniques: Single Cell, RNA Sequencing, Expressing, Sequencing, Activity Assay, Derivative Assay