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Create a Lollipop Plot for GSEA Results

Source: R/plotNESlollipop.R
plotNESlollipop.Rd

This function generates a lollipop plot to visualize Gene Set Enrichment Analysis (GSEA) results. Pathways are shown on the y-axis, while the Normalized Enrichment Score (NES) is shown on the x-axis. The color of the lollipops represents the adjusted p-values (padj), with a custom color gradient. It supports multiple contrasts and can combine individual plots into a grid layout.

Usage

plotNESlollipop(
  GSEA_results,
  signif_color = "red",
  nonsignif_color = "white",
  sig_threshold = 0.05,
  saturation_value = NULL,
  pointSize = 5,
  grid = FALSE,
  nrow = NULL,
  ncol = NULL,
  widthlabels = 18,
  title = NULL,
  titlesize = 12
)

Arguments

GSEA_results

A named list of data frames, each containing the GSEA results for a specific contrast. Output from runGSEA. Each data frame must include the following columns:

pathway

A character vector of pathway names.

NES

A numeric vector of Normalized Enrichment Scores for the pathways.

padj

A numeric vector of adjusted p-values for the pathways.

signif_color

A string specifying the color for the low end of the adjusted p-value gradient until the value chosen for significance (sig_threshold). Default is "red".

nonsignif_color

A string specifying the color for the middle of the adjusted p-value gradient. Default is "white". Lower limit correspond to the value of sig_threshold.

sig_threshold

A numeric value that sets the midpoint for the color scale. Typically used for the significance threshold. Default is 0.05.

saturation_value

A numeric value specifying the lower limit of the adjusted p-value gradient, below which the color will correspond to signif_color. Default is the results' minimum, unless that value is above the sig_threshold; in that case, it is 0.001.

pointSize

Numeric. The size of points in the lollipop plot (default is 5).

grid

A logical value indicating whether to arrange individual plots into a grid layout. If TRUE, the function combines all plots into a grid. Default is FALSE.

nrow

A numeric value specifying the number of rows to arrange the plots into if grid = TRUE. If NULL, the function calculates this automatically. Default is NULL.

ncol

A numeric value specifying the number of columns to arrange the plots into if grid = TRUE. If NULL, the function calculates this automatically. Default is NULL.

widthlabels

A numeric value specifying the maximum width for pathway names. If a pathway name exceeds this width, it will be wrapped to fit. Default is 18.

title

A character string for the title of the combined plot (used only when grid = TRUE). Default is NULL.

titlesize

A numeric value specifying the font size for the title (used only when grid = TRUE). Default is 12.

Value

If grid = FALSE, a list of ggplot objects is returned, each corresponding to a contrast. If grid = TRUE, a single ggplot object is returned, representing the combined grid of plots.

Details

The function creates a lollipop plot for each contrast in the GSEA_results list. Each plot includes:

  • A vertical segment for each pathway, where the x-coordinate represents the NES and the y-coordinate represents the pathway.

  • A colored point at the end of each segment, where the color represents the adjusted p-value (padj), mapped using a custom color gradient.

If a pathway's padj value exceeds the maximum value in padj_limit, the corresponding pathway is colored using the high_color. Additionally, missing values (NA) for padj are assigned the high_color by setting na.value = high_color. Pathway names are wrapped using the wrap_title function to fit within the specified width (widthlabels).

Examples

# Example GSEA results (mock data, missing columns if running by runGSEA)

GSEA_results <- list(
"Contrast1" = data.frame(
NES = rnorm(3),
  padj = runif(3),
  pathway = paste("Pathway", 1:3),
  stat_used = c("t", "B", "B")
),
"Contrast2" = data.frame(
  NES = rnorm(3),
  padj = runif(3),
  pathway = paste("Pathway", 4:6),
  stat_used = c("t", "B", "B")
)
)


# Generate individual plots without grid
plot_list <- plotNESlollipop(GSEA_results)

# Generate combined grid of plots with custom title
combined_plot <- plotNESlollipop(GSEA_results, grid = TRUE,
title = "GSEA Results Overview", titlesize = 14)