TransProR (version 1.0.2)

merge_density_foldchange: Create high-density region plot with optional points, density rugs, and contours

Description

This function creates a high-density region plot using hdr methods to add density rug and filled contours. It also adds a regression line and Pearson correlation label. Points can be added to the plot optionally.

Usage

merge_density_foldchange(
  data,
  x_var,
  y_var,
  group_var,
  palette = c("#3949ab", "#1e88e5", "#039be5", "#00897b", "#43a047", "#7cb342"),
  show_points = FALSE,
  point_size = 2.5,
  point_alpha = 0.2,
  x_lim = c(0, 20),
  y_lim = c(0, 20),
  cor_method = "pearson",
  line_size = 1.6,
  cor_label_pos = c("left", 0.97)
)

Value

A ggplot object representing the high-density region plot.

Arguments

data

Data frame containing variables for plotting.

x_var

Name of the x-axis variable as a string.

y_var

Name of the y-axis variable as a string.

group_var

Name of the grouping variable for color mapping as a string.

palette

Color palette for the plot as a character vector.

show_points

Logical, if TRUE adds points to the plot.

point_size

Size of the points, relevant if show_points is TRUE.

point_alpha

Transparency level of the points, relevant if show_points is TRUE.

x_lim

Numeric vector of length 2, giving the x-axis limits.

y_lim

Numeric vector of length 2, giving the y-axis limits.

cor_method

Method to calculate correlation ("pearson" or "spearman").

line_size

Size of the smoothing line.

cor_label_pos

Vector of length 2 indicating the position of the correlation label (x and y).

Examples

combined_df_file <- system.file("extdata", "combined_df.rds", package = "TransProR")
combined_df <- readRDS(combined_df_file)
pal1 = c("#3949ab","#1e88e5","#039be5","#00897b","#43a047","#7cb342")

all_density_foldchange_name1 <- merge_density_foldchange(
  data = combined_df,
  x_var = "log2FoldChange_1",
  y_var = "log2FoldChange_2",
  group_var = "name",
  palette = pal1,
  show_points = FALSE,
  point_size = 2.5,
  point_alpha = 0.1,
  x_lim = c(0, 20),
  y_lim = c(0, 20),
  cor_method = "pearson",
  line_size = 1.6,
  cor_label_pos = c("left", "top")
)