Plot Delta Enrichment or Interaction Effects for Each Marker

This function takes a complex object containing gating tree data and performs statistical tests to evaluate the significance of delta enrichment or interaction effects across markers. It plots the results as boxplots and returns the modified object with additional annotations based on the analysis.

Usage

PlotDeltaEnrichment(x, significance = TRUE)

Arguments

x

FlowObject.

significance

A logical flag indicating whether to highlight significant markers based on the results of statistical tests.

value

A character string specifying which type of values to analyze and plot. Expected values are 'DeltaE' for delta enrichment or 'IE' for interaction effects.

Value

Returns the original object `x` for safety.

Details

The function conducts Kruskal-Wallis tests to determine the significance of differences across markers, followed by Dunn's test for post-hoc analysis with Bonferroni correction if significant. It prepares and displays a boxplot of the specified metrics (Delta Enrichment or Interaction Effects). The markers are ordered and displayed based on their significance and mean values.

See also

Other GatingTree: GatingTreeToDF(), PruneGatingTree(), addChildNode(), add_prune(), apply_gating_conditions(), baseline_entropy(), calculate_enrichment(), calculate_entropy(), collect_all_enrichment(), collect_all_entropy(), collect_history(), collect_leaf_enrichment(), collect_markers(), convertToDataTree(), convert_to_diagrammer(), count_nodes(), createChildNode(), createGatingTreeObject(), findNodeByPath(), find_and_update_nodes(), gating_entropy(), general_node_rule(), generate_marker_names(), getNode(), prune_tree(), recursiveAddChildNode()

Examples

if (FALSE) { # \dontrun{
  x <- PlotDeltaEnrichment(x, value = "DeltaE", significance = TRUE)
} # }