Man pages for visxhclust
A Shiny App for Visual Exploration of Hierarchical Clustering

annotate_clustersAnnotate data frame with clusters
bin_dfSimulated binary data
cluster_boxplotsPlot boxplots with clusters
cluster_colorsList of colors used in the Shiny app for clusters
cluster_heatmapsPlot heatmap with cluster results and dendrogram
compute_clustersCompute clusters hierarchically from distance matrix
compute_dmatCompute a distance matrix from scaled data
compute_gapstatCompute Gap statistic for clustered data
compute_metricCompute an internal evaluation metric for clustered data
correlation_heatmapPlot a correlation heatmap
create_annotationsCreate heatmap annotations from selected variables
cut_clustersCut a hierarchical tree targeting k clusters
dmat_projectionPlot a 2D MDS projection of a distance matrix
facet_boxplotFaceted boxplots with points or violin plots
line_plotA custom line plot with optional vertical line
logscaled_dfSimulated logscaled data
normal_annotatedSimulated normal data with annotations
normal_dfSimulated normal data
normal_missingSimulated normal data with missing values
optimal_scoreFind minimum or maximum score in a vector
plot_annotation_distPlot distribution of annotation data across clusters
plot_cluster_heatmapsDraw two heatmaps
run_appRuns the Shiny app
visxhclust documentation built on March 31, 2023, 7:30 p.m.