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implementation of phate  (MathWorks Inc)


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    MathWorks Inc implementation of phate
    (A) Confocal image and zoom-in image of a LN section from a C57BL/6 mouse, adoptively transferred with 10^6 naive OT-II CD4+ T cells and immunized with OVA plus alum. Overview image scale bar, 200 μm; zoom-in scale bar, 30 μm. Only select channels are shown. (B) Histo-cytometry plots of cell object MFI for different channels demonstrating the gating used for identification of the indicated immune cell populations. (C) Positional plot of cell data from (B) (area matches the zoom-in image in A). CytoMAP was used to calculate the number of cells in 30-μm-radius neighborhoods (denoted by the circles in the bottom left), which were raster scanned as denoted by the arrow. (D) Heatmap of the neighborhood composition (percentage of each cell phenotype per neighborhood) after SOM clustering. Individual clusters, or “regions,” aredenoted by the color bar at the top of the graph. Arrowheads at the bottom highlight specific neighborhoods. (E) Region color-coded positional plot of the neighborhoods from (D). (F) Pseudo-space plot with the neighborhoods sorted based on B cell composition (sorted to the left) and T cell composition (sorted to the right). (G) Dimensionality reduction plots of the neighborhoods in which the standardized numbers of cells and total MFI of all channels were used for the dimensionalityreduction. t-SNE, <t>PCA,</t> <t>UMAP,</t> and <t>PHATE</t> were all calculated for the same input neighborhoods, which are color coded based on region type from (D). For this experiment, an imaging volume of 0.03 mm 3 , 139,399 cells, and 11,328 neighborhoods were analyzed.
    Implementation Of Phate, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/implementation of phate/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    implementation of phate - by Bioz Stars, 2026-03
    90/100 stars

    Images

    1) Product Images from "CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues"

    Article Title: CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues

    Journal: Cell reports

    doi: 10.1016/j.celrep.2020.107523

    (A) Confocal image and zoom-in image of a LN section from a C57BL/6 mouse, adoptively transferred with 10^6 naive OT-II CD4+ T cells and immunized with OVA plus alum. Overview image scale bar, 200 μm; zoom-in scale bar, 30 μm. Only select channels are shown. (B) Histo-cytometry plots of cell object MFI for different channels demonstrating the gating used for identification of the indicated immune cell populations. (C) Positional plot of cell data from (B) (area matches the zoom-in image in A). CytoMAP was used to calculate the number of cells in 30-μm-radius neighborhoods (denoted by the circles in the bottom left), which were raster scanned as denoted by the arrow. (D) Heatmap of the neighborhood composition (percentage of each cell phenotype per neighborhood) after SOM clustering. Individual clusters, or “regions,” aredenoted by the color bar at the top of the graph. Arrowheads at the bottom highlight specific neighborhoods. (E) Region color-coded positional plot of the neighborhoods from (D). (F) Pseudo-space plot with the neighborhoods sorted based on B cell composition (sorted to the left) and T cell composition (sorted to the right). (G) Dimensionality reduction plots of the neighborhoods in which the standardized numbers of cells and total MFI of all channels were used for the dimensionalityreduction. t-SNE, PCA, UMAP, and PHATE were all calculated for the same input neighborhoods, which are color coded based on region type from (D). For this experiment, an imaging volume of 0.03 mm 3 , 139,399 cells, and 11,328 neighborhoods were analyzed.
    Figure Legend Snippet: (A) Confocal image and zoom-in image of a LN section from a C57BL/6 mouse, adoptively transferred with 10^6 naive OT-II CD4+ T cells and immunized with OVA plus alum. Overview image scale bar, 200 μm; zoom-in scale bar, 30 μm. Only select channels are shown. (B) Histo-cytometry plots of cell object MFI for different channels demonstrating the gating used for identification of the indicated immune cell populations. (C) Positional plot of cell data from (B) (area matches the zoom-in image in A). CytoMAP was used to calculate the number of cells in 30-μm-radius neighborhoods (denoted by the circles in the bottom left), which were raster scanned as denoted by the arrow. (D) Heatmap of the neighborhood composition (percentage of each cell phenotype per neighborhood) after SOM clustering. Individual clusters, or “regions,” aredenoted by the color bar at the top of the graph. Arrowheads at the bottom highlight specific neighborhoods. (E) Region color-coded positional plot of the neighborhoods from (D). (F) Pseudo-space plot with the neighborhoods sorted based on B cell composition (sorted to the left) and T cell composition (sorted to the right). (G) Dimensionality reduction plots of the neighborhoods in which the standardized numbers of cells and total MFI of all channels were used for the dimensionalityreduction. t-SNE, PCA, UMAP, and PHATE were all calculated for the same input neighborhoods, which are color coded based on region type from (D). For this experiment, an imaging volume of 0.03 mm 3 , 139,399 cells, and 11,328 neighborhoods were analyzed.

    Techniques Used: Cytometry, Imaging



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    implementation of phate  (MathWorks Inc)
    90
    MathWorks Inc implementation of phate
    (A) Confocal image and zoom-in image of a LN section from a C57BL/6 mouse, adoptively transferred with 10^6 naive OT-II CD4+ T cells and immunized with OVA plus alum. Overview image scale bar, 200 μm; zoom-in scale bar, 30 μm. Only select channels are shown. (B) Histo-cytometry plots of cell object MFI for different channels demonstrating the gating used for identification of the indicated immune cell populations. (C) Positional plot of cell data from (B) (area matches the zoom-in image in A). CytoMAP was used to calculate the number of cells in 30-μm-radius neighborhoods (denoted by the circles in the bottom left), which were raster scanned as denoted by the arrow. (D) Heatmap of the neighborhood composition (percentage of each cell phenotype per neighborhood) after SOM clustering. Individual clusters, or “regions,” aredenoted by the color bar at the top of the graph. Arrowheads at the bottom highlight specific neighborhoods. (E) Region color-coded positional plot of the neighborhoods from (D). (F) Pseudo-space plot with the neighborhoods sorted based on B cell composition (sorted to the left) and T cell composition (sorted to the right). (G) Dimensionality reduction plots of the neighborhoods in which the standardized numbers of cells and total MFI of all channels were used for the dimensionalityreduction. t-SNE, <t>PCA,</t> <t>UMAP,</t> and <t>PHATE</t> were all calculated for the same input neighborhoods, which are color coded based on region type from (D). For this experiment, an imaging volume of 0.03 mm 3 , 139,399 cells, and 11,328 neighborhoods were analyzed.
    Implementation Of Phate, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/implementation of phate/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    implementation of phate - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    (A) Confocal image and zoom-in image of a LN section from a C57BL/6 mouse, adoptively transferred with 10^6 naive OT-II CD4+ T cells and immunized with OVA plus alum. Overview image scale bar, 200 μm; zoom-in scale bar, 30 μm. Only select channels are shown. (B) Histo-cytometry plots of cell object MFI for different channels demonstrating the gating used for identification of the indicated immune cell populations. (C) Positional plot of cell data from (B) (area matches the zoom-in image in A). CytoMAP was used to calculate the number of cells in 30-μm-radius neighborhoods (denoted by the circles in the bottom left), which were raster scanned as denoted by the arrow. (D) Heatmap of the neighborhood composition (percentage of each cell phenotype per neighborhood) after SOM clustering. Individual clusters, or “regions,” aredenoted by the color bar at the top of the graph. Arrowheads at the bottom highlight specific neighborhoods. (E) Region color-coded positional plot of the neighborhoods from (D). (F) Pseudo-space plot with the neighborhoods sorted based on B cell composition (sorted to the left) and T cell composition (sorted to the right). (G) Dimensionality reduction plots of the neighborhoods in which the standardized numbers of cells and total MFI of all channels were used for the dimensionalityreduction. t-SNE, PCA, UMAP, and PHATE were all calculated for the same input neighborhoods, which are color coded based on region type from (D). For this experiment, an imaging volume of 0.03 mm 3 , 139,399 cells, and 11,328 neighborhoods were analyzed.

    Journal: Cell reports

    Article Title: CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues

    doi: 10.1016/j.celrep.2020.107523

    Figure Lengend Snippet: (A) Confocal image and zoom-in image of a LN section from a C57BL/6 mouse, adoptively transferred with 10^6 naive OT-II CD4+ T cells and immunized with OVA plus alum. Overview image scale bar, 200 μm; zoom-in scale bar, 30 μm. Only select channels are shown. (B) Histo-cytometry plots of cell object MFI for different channels demonstrating the gating used for identification of the indicated immune cell populations. (C) Positional plot of cell data from (B) (area matches the zoom-in image in A). CytoMAP was used to calculate the number of cells in 30-μm-radius neighborhoods (denoted by the circles in the bottom left), which were raster scanned as denoted by the arrow. (D) Heatmap of the neighborhood composition (percentage of each cell phenotype per neighborhood) after SOM clustering. Individual clusters, or “regions,” aredenoted by the color bar at the top of the graph. Arrowheads at the bottom highlight specific neighborhoods. (E) Region color-coded positional plot of the neighborhoods from (D). (F) Pseudo-space plot with the neighborhoods sorted based on B cell composition (sorted to the left) and T cell composition (sorted to the right). (G) Dimensionality reduction plots of the neighborhoods in which the standardized numbers of cells and total MFI of all channels were used for the dimensionalityreduction. t-SNE, PCA, UMAP, and PHATE were all calculated for the same input neighborhoods, which are color coded based on region type from (D). For this experiment, an imaging volume of 0.03 mm 3 , 139,399 cells, and 11,328 neighborhoods were analyzed.

    Article Snippet: We used the e4 MATLAB implementation of UMAP, with default parameters, provided by the Herzenberg Lab at Stanford University available for download at: https://www.mathworks.com/matlabcentral/fileexchange/71902-uniform-manifold-approximation-and-projection-umap .> We used the MATLAB implementation of PHATE, with default parameters, provided by Krishnaswamy Lab available for download at: https://github.com/KrishnaswamyLab/PHATE .

    Techniques: Cytometry, Imaging