visualize_gsea: Visualize GSEA results

In ggpicrust2: Make 'PICRUSt2' Output Analysis and Visualization Easier

Visualize GSEA results

Description

This function creates various visualizations for Gene Set Enrichment Analysis (GSEA) results. It automatically detects whether pathway names are available (from gsea_pathway_annotation()) and uses them for better readability, falling back to pathway IDs if names are not available.

Usage

visualize_gsea(
  gsea_results,
  plot_type = "enrichment_plot",
  n_pathways = 20,
  sort_by = "p.adjust",
  colors = NULL,
  abundance = NULL,
  metadata = NULL,
  group = NULL,
  network_params = list(),
  heatmap_params = list(),
  pathway_label_column = NULL
)

Arguments

gsea_results	A data frame containing GSEA results from the pathway_gsea function
plot_type	A character string specifying the visualization type: "enrichment_plot", "dotplot", "barplot", "network", or "heatmap"
n_pathways	An integer specifying the number of pathways to display
sort_by	A character string specifying the sorting criterion: "NES", "pvalue", or "p.adjust"
colors	A vector of colors for the visualization
abundance	A data frame containing the original abundance data (required for heatmap visualization)
metadata	A data frame containing sample metadata (required for heatmap visualization)
group	A character string specifying the column name in metadata that contains the grouping variable (required for heatmap visualization)
network_params	A list of parameters for network visualization
heatmap_params	A list of parameters for heatmap visualization
pathway_label_column	A character string specifying which column to use for pathway labels. If NULL (default), the function will automatically use 'pathway_name' if available, otherwise 'pathway_id'. This allows for custom labeling when using annotated GSEA results.

Value

A ggplot2 object or ComplexHeatmap object

Examples

## Not run: 
# Load example data
data(ko_abundance)
data(metadata)

# Prepare abundance data
abundance_data <- as.data.frame(ko_abundance)
rownames(abundance_data) <- abundance_data[, "#NAME"]
abundance_data <- abundance_data[, -1]

# Run GSEA analysis
gsea_results <- pathway_gsea(
  abundance = abundance_data,
  metadata = metadata,
  group = "Environment",
  pathway_type = "KEGG",
  method = "fgsea"
)

# Create enrichment plot with pathway IDs (default)
visualize_gsea(gsea_results, plot_type = "enrichment_plot", n_pathways = 10)

# Annotate results for better pathway names
annotated_results <- gsea_pathway_annotation(
  gsea_results = gsea_results,
  pathway_type = "KEGG"
)

# Create plots with readable pathway names
visualize_gsea(annotated_results, plot_type = "dotplot", n_pathways = 20)
visualize_gsea(annotated_results, plot_type = "barplot", n_pathways = 15)

# Create network plot with custom labels
visualize_gsea(annotated_results, plot_type = "network", n_pathways = 15)

# Use custom column for labels (if available)
visualize_gsea(annotated_results, plot_type = "barplot",
               pathway_label_column = "pathway_name", n_pathways = 10)

# Create heatmap
visualize_gsea(
  annotated_results,
  plot_type = "heatmap",
  n_pathways = 15,
  abundance = abundance_data,
  metadata = metadata,
  group = "Environment"
)

## End(Not run)

ggpicrust2 documentation built on Aug. 26, 2025, 1:07 a.m.