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partek flow pathway analysis  (Partek)

 
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    Partek partek flow pathway analysis
    ( A ) t-SNE plot of cells from all injury conditions overlay for expression of Cd68 (red) and Fabp7 (green). ( B ) Plotting cells in the macrophage (orange) and SGC (green) clusters for expression of Cd68 (y-axis) and Fabp7 (x-axis). ( C ) Dot plot of macrophage, glial and progenitor marker genes expression in the macrophage, SGC and Imoonglia clusters. The percentage of cell expressing the gene is calculated as the number of cells in each cluster express the gene ( > 0 counts) divided by the total number of cells in the respective cluster. Expression in each cluster is calculated as mean expression of the gene relative to the highest mean expression of that gene across all clusters. ( D ) Trajectory <t>analysis</t> of macrophage, SGC and Imoonglia cell clusters. ( E ) <t>Flow</t> cytometry analysis of DRG cells from Fabp7 creER : Sun1 GFP mice, stained with the macrophage marker genes CD45, CD11b and F4/80 n = 2 (F4/80) n = 1 (CD45,CD11b,F4/80) biologically independent animals. ( F ) Representative confocal images of immunofluorescence staining of DRG sections labeled with CD68 (green) and FABP7 (magenta). Fluorescence intensity for CD68 and FABP7 was measured along the arrow line. Scale bar: 50 µm ( G ) Fraction of cells in the Imoonglia cluster by injury condition. n = 2 biologically independent experiments. ( H ) Venn diagram of differentially expressed genes in the Imoonglia cluster (1,097 genes) was compared to top differentially expressed genes in the macrophage cluster (2,469 genes) and the SGC (2,331 genes) (FDR ≤ 0.05, fold-change ≥ 2). ( I ) <t>Pathway</t> analysis (KEGG 2019) of differentially expressed genes in Macrophages, Imoonglia and SGC. Figure 4—source data 1. Source files for scRNAseq analysis, flow cytometry additional experiments.
    Partek Flow Pathway Analysis, supplied by Partek, 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/partek+flow+pathway+analysis/pmc08480984-353-15-15?v=Partek
    Average 86 stars, based on 1 article reviews
    partek flow pathway analysis - by Bioz Stars, 2026-07
    86/100 stars

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    1) Product Images from "Profiling sensory neuron microenvironment after peripheral and central axon injury reveals key pathways for neural repair"

    Article Title: Profiling sensory neuron microenvironment after peripheral and central axon injury reveals key pathways for neural repair

    Journal: eLife

    doi: 10.7554/eLife.68457

    ( A ) t-SNE plot of cells from all injury conditions overlay for expression of Cd68 (red) and Fabp7 (green). ( B ) Plotting cells in the macrophage (orange) and SGC (green) clusters for expression of Cd68 (y-axis) and Fabp7 (x-axis). ( C ) Dot plot of macrophage, glial and progenitor marker genes expression in the macrophage, SGC and Imoonglia clusters. The percentage of cell expressing the gene is calculated as the number of cells in each cluster express the gene ( > 0 counts) divided by the total number of cells in the respective cluster. Expression in each cluster is calculated as mean expression of the gene relative to the highest mean expression of that gene across all clusters. ( D ) Trajectory analysis of macrophage, SGC and Imoonglia cell clusters. ( E ) Flow cytometry analysis of DRG cells from Fabp7 creER : Sun1 GFP mice, stained with the macrophage marker genes CD45, CD11b and F4/80 n = 2 (F4/80) n = 1 (CD45,CD11b,F4/80) biologically independent animals. ( F ) Representative confocal images of immunofluorescence staining of DRG sections labeled with CD68 (green) and FABP7 (magenta). Fluorescence intensity for CD68 and FABP7 was measured along the arrow line. Scale bar: 50 µm ( G ) Fraction of cells in the Imoonglia cluster by injury condition. n = 2 biologically independent experiments. ( H ) Venn diagram of differentially expressed genes in the Imoonglia cluster (1,097 genes) was compared to top differentially expressed genes in the macrophage cluster (2,469 genes) and the SGC (2,331 genes) (FDR ≤ 0.05, fold-change ≥ 2). ( I ) Pathway analysis (KEGG 2019) of differentially expressed genes in Macrophages, Imoonglia and SGC. Figure 4—source data 1. Source files for scRNAseq analysis, flow cytometry additional experiments.
    Figure Legend Snippet: ( A ) t-SNE plot of cells from all injury conditions overlay for expression of Cd68 (red) and Fabp7 (green). ( B ) Plotting cells in the macrophage (orange) and SGC (green) clusters for expression of Cd68 (y-axis) and Fabp7 (x-axis). ( C ) Dot plot of macrophage, glial and progenitor marker genes expression in the macrophage, SGC and Imoonglia clusters. The percentage of cell expressing the gene is calculated as the number of cells in each cluster express the gene ( > 0 counts) divided by the total number of cells in the respective cluster. Expression in each cluster is calculated as mean expression of the gene relative to the highest mean expression of that gene across all clusters. ( D ) Trajectory analysis of macrophage, SGC and Imoonglia cell clusters. ( E ) Flow cytometry analysis of DRG cells from Fabp7 creER : Sun1 GFP mice, stained with the macrophage marker genes CD45, CD11b and F4/80 n = 2 (F4/80) n = 1 (CD45,CD11b,F4/80) biologically independent animals. ( F ) Representative confocal images of immunofluorescence staining of DRG sections labeled with CD68 (green) and FABP7 (magenta). Fluorescence intensity for CD68 and FABP7 was measured along the arrow line. Scale bar: 50 µm ( G ) Fraction of cells in the Imoonglia cluster by injury condition. n = 2 biologically independent experiments. ( H ) Venn diagram of differentially expressed genes in the Imoonglia cluster (1,097 genes) was compared to top differentially expressed genes in the macrophage cluster (2,469 genes) and the SGC (2,331 genes) (FDR ≤ 0.05, fold-change ≥ 2). ( I ) Pathway analysis (KEGG 2019) of differentially expressed genes in Macrophages, Imoonglia and SGC. Figure 4—source data 1. Source files for scRNAseq analysis, flow cytometry additional experiments.

    Techniques Used: Expressing, Marker, Flow Cytometry, Staining, Immunofluorescence, Labeling, Fluorescence


    Figure Legend Snippet:

    Techniques Used: Binding Assay, Recombinant, Sequencing, Reverse Transcription, Plasmid Preparation, SYBR Green Assay, Software



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    ( A ) t-SNE plot of cells from all injury conditions overlay for expression of Cd68 (red) and Fabp7 (green). ( B ) Plotting cells in the macrophage (orange) and SGC (green) clusters for expression of Cd68 (y-axis) and Fabp7 (x-axis). ( C ) Dot plot of macrophage, glial and progenitor marker genes expression in the macrophage, SGC and Imoonglia clusters. The percentage of cell expressing the gene is calculated as the number of cells in each cluster express the gene ( > 0 counts) divided by the total number of cells in the respective cluster. Expression in each cluster is calculated as mean expression of the gene relative to the highest mean expression of that gene across all clusters. ( D ) Trajectory <t>analysis</t> of macrophage, SGC and Imoonglia cell clusters. ( E ) <t>Flow</t> cytometry analysis of DRG cells from Fabp7 creER : Sun1 GFP mice, stained with the macrophage marker genes CD45, CD11b and F4/80 n = 2 (F4/80) n = 1 (CD45,CD11b,F4/80) biologically independent animals. ( F ) Representative confocal images of immunofluorescence staining of DRG sections labeled with CD68 (green) and FABP7 (magenta). Fluorescence intensity for CD68 and FABP7 was measured along the arrow line. Scale bar: 50 µm ( G ) Fraction of cells in the Imoonglia cluster by injury condition. n = 2 biologically independent experiments. ( H ) Venn diagram of differentially expressed genes in the Imoonglia cluster (1,097 genes) was compared to top differentially expressed genes in the macrophage cluster (2,469 genes) and the SGC (2,331 genes) (FDR ≤ 0.05, fold-change ≥ 2). ( I ) <t>Pathway</t> analysis (KEGG 2019) of differentially expressed genes in Macrophages, Imoonglia and SGC. Figure 4—source data 1. Source files for scRNAseq analysis, flow cytometry additional experiments.
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    Image Search Results


    ( A ) t-SNE plot of cells from all injury conditions overlay for expression of Cd68 (red) and Fabp7 (green). ( B ) Plotting cells in the macrophage (orange) and SGC (green) clusters for expression of Cd68 (y-axis) and Fabp7 (x-axis). ( C ) Dot plot of macrophage, glial and progenitor marker genes expression in the macrophage, SGC and Imoonglia clusters. The percentage of cell expressing the gene is calculated as the number of cells in each cluster express the gene ( > 0 counts) divided by the total number of cells in the respective cluster. Expression in each cluster is calculated as mean expression of the gene relative to the highest mean expression of that gene across all clusters. ( D ) Trajectory analysis of macrophage, SGC and Imoonglia cell clusters. ( E ) Flow cytometry analysis of DRG cells from Fabp7 creER : Sun1 GFP mice, stained with the macrophage marker genes CD45, CD11b and F4/80 n = 2 (F4/80) n = 1 (CD45,CD11b,F4/80) biologically independent animals. ( F ) Representative confocal images of immunofluorescence staining of DRG sections labeled with CD68 (green) and FABP7 (magenta). Fluorescence intensity for CD68 and FABP7 was measured along the arrow line. Scale bar: 50 µm ( G ) Fraction of cells in the Imoonglia cluster by injury condition. n = 2 biologically independent experiments. ( H ) Venn diagram of differentially expressed genes in the Imoonglia cluster (1,097 genes) was compared to top differentially expressed genes in the macrophage cluster (2,469 genes) and the SGC (2,331 genes) (FDR ≤ 0.05, fold-change ≥ 2). ( I ) Pathway analysis (KEGG 2019) of differentially expressed genes in Macrophages, Imoonglia and SGC. Figure 4—source data 1. Source files for scRNAseq analysis, flow cytometry additional experiments.

    Journal: eLife

    Article Title: Profiling sensory neuron microenvironment after peripheral and central axon injury reveals key pathways for neural repair

    doi: 10.7554/eLife.68457

    Figure Lengend Snippet: ( A ) t-SNE plot of cells from all injury conditions overlay for expression of Cd68 (red) and Fabp7 (green). ( B ) Plotting cells in the macrophage (orange) and SGC (green) clusters for expression of Cd68 (y-axis) and Fabp7 (x-axis). ( C ) Dot plot of macrophage, glial and progenitor marker genes expression in the macrophage, SGC and Imoonglia clusters. The percentage of cell expressing the gene is calculated as the number of cells in each cluster express the gene ( > 0 counts) divided by the total number of cells in the respective cluster. Expression in each cluster is calculated as mean expression of the gene relative to the highest mean expression of that gene across all clusters. ( D ) Trajectory analysis of macrophage, SGC and Imoonglia cell clusters. ( E ) Flow cytometry analysis of DRG cells from Fabp7 creER : Sun1 GFP mice, stained with the macrophage marker genes CD45, CD11b and F4/80 n = 2 (F4/80) n = 1 (CD45,CD11b,F4/80) biologically independent animals. ( F ) Representative confocal images of immunofluorescence staining of DRG sections labeled with CD68 (green) and FABP7 (magenta). Fluorescence intensity for CD68 and FABP7 was measured along the arrow line. Scale bar: 50 µm ( G ) Fraction of cells in the Imoonglia cluster by injury condition. n = 2 biologically independent experiments. ( H ) Venn diagram of differentially expressed genes in the Imoonglia cluster (1,097 genes) was compared to top differentially expressed genes in the macrophage cluster (2,469 genes) and the SGC (2,331 genes) (FDR ≤ 0.05, fold-change ≥ 2). ( I ) Pathway analysis (KEGG 2019) of differentially expressed genes in Macrophages, Imoonglia and SGC. Figure 4—source data 1. Source files for scRNAseq analysis, flow cytometry additional experiments.

    Article Snippet: The data was subsequently analyzed for enrichment of GO terms and the KEGG pathways using Partek flow pathway analysis.

    Techniques: Expressing, Marker, Flow Cytometry, Staining, Immunofluorescence, Labeling, Fluorescence

    Journal: eLife

    Article Title: Profiling sensory neuron microenvironment after peripheral and central axon injury reveals key pathways for neural repair

    doi: 10.7554/eLife.68457

    Figure Lengend Snippet:

    Article Snippet: The data was subsequently analyzed for enrichment of GO terms and the KEGG pathways using Partek flow pathway analysis.

    Techniques: Binding Assay, Recombinant, Sequencing, Reverse Transcription, Plasmid Preparation, SYBR Green Assay, Software