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graphs and umap plots  (RStudio)

 
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    RStudio graphs and umap plots
    Correlation of IFC features with phenotypic features (A) Correlation plot showing the correlation between IFC features and clinical phenotypes. All clinical features were converted to binary parameters (Yes = Present, No=Not present) and correlation was calculated using Spearman’s correlation. The color coding and dot size correlate with Spearman’s rho coefficient. (B) All significant correlations have been plotted as a boxplot. For the boxplots, the values of each of the five features ( <xref ref-type=Table 1 ) were normalized against the mean of the healthy control taken along within the same experiment and converted to percentages. Statistics were calculated using Welsch’s t test. The black line indicates the median value, the lower and upper hinges correspond to the 25th and 75th percentiles. The upper and lower whisker extend to 1.5∗IQR. (C) Showing the UMAP plots from Figures 2 C and A. The nodes are colored according to the presence of neuropathy (Yes, No, NA). NA means that the specific feature was not assessed in patients. Statistical significance between the two clusters was calculated using Fisher’s exact test. Neuropathy was the only clinical feature that had a significant association with one of the clusters. " width="250" height="auto" />
    Graphs And Umap Plots, supplied by RStudio, 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/graphs and umap plots/product/RStudio
    Average 90 stars, based on 1 article reviews
    graphs and umap plots - by Bioz Stars, 2026-04
    90/100 stars

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    1) Product Images from "Imaging flow cytometry reveals divergent mitochondrial phenotypes in mitochondrial disease patients"

    Article Title: Imaging flow cytometry reveals divergent mitochondrial phenotypes in mitochondrial disease patients

    Journal: iScience

    doi: 10.1016/j.isci.2024.111496

    Correlation of IFC features with phenotypic features (A) Correlation plot showing the correlation between IFC features and clinical phenotypes. All clinical features were converted to binary parameters (Yes = Present, No=Not present) and correlation was calculated using Spearman’s correlation. The color coding and dot size correlate with Spearman’s rho coefficient. (B) All significant correlations have been plotted as a boxplot. For the boxplots, the values of each of the five features ( <xref ref-type=Table 1 ) were normalized against the mean of the healthy control taken along within the same experiment and converted to percentages. Statistics were calculated using Welsch’s t test. The black line indicates the median value, the lower and upper hinges correspond to the 25th and 75th percentiles. The upper and lower whisker extend to 1.5∗IQR. (C) Showing the UMAP plots from Figures 2 C and A. The nodes are colored according to the presence of neuropathy (Yes, No, NA). NA means that the specific feature was not assessed in patients. Statistical significance between the two clusters was calculated using Fisher’s exact test. Neuropathy was the only clinical feature that had a significant association with one of the clusters. " title="... lower whisker extend to 1.5∗IQR. (C) Showing the UMAP plots from Figures 2 C and ..." property="contentUrl" width="100%" height="100%"/>
    Figure Legend Snippet: Correlation of IFC features with phenotypic features (A) Correlation plot showing the correlation between IFC features and clinical phenotypes. All clinical features were converted to binary parameters (Yes = Present, No=Not present) and correlation was calculated using Spearman’s correlation. The color coding and dot size correlate with Spearman’s rho coefficient. (B) All significant correlations have been plotted as a boxplot. For the boxplots, the values of each of the five features ( Table 1 ) were normalized against the mean of the healthy control taken along within the same experiment and converted to percentages. Statistics were calculated using Welsch’s t test. The black line indicates the median value, the lower and upper hinges correspond to the 25th and 75th percentiles. The upper and lower whisker extend to 1.5∗IQR. (C) Showing the UMAP plots from Figures 2 C and A. The nodes are colored according to the presence of neuropathy (Yes, No, NA). NA means that the specific feature was not assessed in patients. Statistical significance between the two clusters was calculated using Fisher’s exact test. Neuropathy was the only clinical feature that had a significant association with one of the clusters.

    Techniques Used: Control, Whisker Assay



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    graphs and umap plots  (RStudio)
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    Correlation of IFC features with phenotypic features (A) Correlation plot showing the correlation between IFC features and clinical phenotypes. All clinical features were converted to binary parameters (Yes = Present, No=Not present) and correlation was calculated using Spearman’s correlation. The color coding and dot size correlate with Spearman’s rho coefficient. (B) All significant correlations have been plotted as a boxplot. For the boxplots, the values of each of the five features ( <xref ref-type=Table 1 ) were normalized against the mean of the healthy control taken along within the same experiment and converted to percentages. Statistics were calculated using Welsch’s t test. The black line indicates the median value, the lower and upper hinges correspond to the 25th and 75th percentiles. The upper and lower whisker extend to 1.5∗IQR. (C) Showing the UMAP plots from Figures 2 C and A. The nodes are colored according to the presence of neuropathy (Yes, No, NA). NA means that the specific feature was not assessed in patients. Statistical significance between the two clusters was calculated using Fisher’s exact test. Neuropathy was the only clinical feature that had a significant association with one of the clusters. " width="100%" height="100%">

    Journal: iScience

    Article Title: Imaging flow cytometry reveals divergent mitochondrial phenotypes in mitochondrial disease patients

    doi: 10.1016/j.isci.2024.111496

    Figure Lengend Snippet: Correlation of IFC features with phenotypic features (A) Correlation plot showing the correlation between IFC features and clinical phenotypes. All clinical features were converted to binary parameters (Yes = Present, No=Not present) and correlation was calculated using Spearman’s correlation. The color coding and dot size correlate with Spearman’s rho coefficient. (B) All significant correlations have been plotted as a boxplot. For the boxplots, the values of each of the five features ( Table 1 ) were normalized against the mean of the healthy control taken along within the same experiment and converted to percentages. Statistics were calculated using Welsch’s t test. The black line indicates the median value, the lower and upper hinges correspond to the 25th and 75th percentiles. The upper and lower whisker extend to 1.5∗IQR. (C) Showing the UMAP plots from Figures 2 C and A. The nodes are colored according to the presence of neuropathy (Yes, No, NA). NA means that the specific feature was not assessed in patients. Statistical significance between the two clusters was calculated using Fisher’s exact test. Neuropathy was the only clinical feature that had a significant association with one of the clusters.

    Article Snippet: All graphs and UMAP plots were created using R-studio, except for the line chart of A, which was created with GraphPad Prism version 6 for Windows.

    Techniques: Control, Whisker Assay