circos_fruits: Add multiple layers to a 'ggtree' plot for visualizing gene...

In TransProR: Analysis and Visualization of Multi-Omics Data

Add multiple layers to a 'ggtree' plot for visualizing gene expression and enrichment data

Description

This function sequentially adds multiple layers to a 'ggtree' plot, including gene expression data, boxplots for statistical summaries, and additional tile layers for pathway enrichment scores from SSGSEA and GSVA analyses. It utilizes separate functions for adding each type of layer and allows for the specification of gene colors as well as adjustments in aesthetics for each layer. The function is designed to work with specific data structures and assumes all functions for adding layers are defined and available.

Usage

circos_fruits(
  p,
  long_format_HeatdataDeseq,
  ssgsea_kegg_HeatdataDeseq,
  gsva_kegg_HeatdataDeseq,
  gene_colors
)

Arguments

p	A 'ggtree' plot object to which the data and layers will be added.
long_format_HeatdataDeseq	A data frame containing gene expression data with columns for 'Samples', 'Genes', and 'Values'.
ssgsea_kegg_HeatdataDeseq	A data frame containing SSGSEA analysis results with columns for 'Samples', 'Genes', and 'Values'.
gsva_kegg_HeatdataDeseq	A data frame containing GSVA analysis results with columns for 'Samples', 'Genes', and 'Values'.
gene_colors	A named vector of colors for genes, used for coloring tiles in different layers.

Value

A 'ggtree' plot object with multiple layers added for comprehensive visualization.

Examples

# Check and load required packages
if (requireNamespace("ggtreeExtra", quietly = TRUE) &&
 requireNamespace("ggplot2", quietly = TRUE)) {
  library(ggtreeExtra)
  library(ggplot2)

  # Example data for gene expression, SSGSEA, and GSVA
  file_path <- system.file("extdata", "p_tree_test.rds", package = "TransProR")
  p <- readRDS(file_path)

  # Create gene expression data frame (long_format_HeatdataDeseq)
  long_format_HeatdataDeseq <- data.frame(
    Sample = rep(c("Species_A", "Species_B", "Species_C", "Species_D"), each = 5),
    Genes = rep(paste0("Gene", 1:5), times = 4),
    Value = runif(20, min = 0, max = 1)  # Randomly generate expression values between 0 and 1
  )

  # Create SSGSEA analysis results data frame (ssgsea_kegg_HeatdataDeseq)
  ssgsea_kegg_HeatdataDeseq <- data.frame(
    Sample = rep(c("Species_A", "Species_B", "Species_C", "Species_D"), each = 3),
    Genes = rep(c("Pathway1", "Pathway2", "Pathway3"), times = 4),
    Value = runif(12, min = 0, max = 1)  # Randomly generate enrichment scores between 0 and 1
  )

  # Create GSVA analysis results data frame (gsva_kegg_HeatdataDeseq)
  gsva_kegg_HeatdataDeseq <- data.frame(
    Sample = rep(c("Species_A", "Species_B", "Species_C", "Species_D"), each = 4),
    Genes = rep(c("PathwayA", "PathwayB", "PathwayC", "PathwayD"), times = 4),
    Value = runif(16, min = 0, max = 1)  # Randomly generate enrichment scores between 0 and 1
  )

  # Define gene and pathway colors (named vector), including all genes and pathways
  gene_colors <- c(
    # Genes for gene expression
    Gene1 = "#491588",
    Gene2 = "#301b8d",
    Gene3 = "#1a237a",
    Gene4 = "#11479c",
    Gene5 = "#0a5797",
    # Pathways for SSGSEA
    Pathway1 = "#0b5f63",
    Pathway2 = "#074d41",
    Pathway3 = "#1f5e27",
    # Pathways for GSVA
    PathwayA = "#366928",
    PathwayB = "#827729",
    PathwayC = "#a1d99b",
    PathwayD = "#c7e9c0"
  )

  # Call circos_fruits function to add multiple layers
  final_plot <- circos_fruits(
    p,
    long_format_HeatdataDeseq,
    ssgsea_kegg_HeatdataDeseq,
    gsva_kegg_HeatdataDeseq,
    gene_colors
  )
} else {
  message("Required packages 'ggtreeExtra' and 'ggplot2' are not installed.")
}

TransProR documentation built on April 4, 2025, 3:16 a.m.