A Shiny App for Visual Exploration of Hierarchical Clustering


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Documentation for package ‘visxhclust’ version 1.1.0

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annotate_clusters Annotate data frame with clusters
bin_df Simulated binary data
cluster_boxplots Plot boxplots with clusters
cluster_colors List of colors used in the Shiny app for clusters
cluster_heatmaps Plot heatmap with cluster results and dendrogram
compute_clusters Compute clusters hierarchically from distance matrix
compute_dmat Compute a distance matrix from scaled data
compute_gapstat Compute Gap statistic for clustered data
compute_metric Compute an internal evaluation metric for clustered data
correlation_heatmap Plot a correlation heatmap
create_annotations Create heatmap annotations from selected variables
cut_clusters Cut a hierarchical tree targeting k clusters
dmat_projection Plot a 2D MDS projection of a distance matrix
facet_boxplot Faceted boxplots with points or violin plots
line_plot A custom line plot with optional vertical line
logscaled_df Simulated logscaled data
normal_annotated Simulated normal data with annotations
normal_df Simulated normal data
normal_missing Simulated normal data with missing values
optimal_score Find minimum or maximum score in a vector
plot_annotation_dist Plot distribution of annotation data across clusters
run_app Runs the Shiny app