geom_dense_scatter: Create a density-colored scatter plot

In tanaylab/tgutil: Simple utility functions for Tanay lab code

Create a density-colored scatter plot

Description

This geom creates a scatter plot where points are colored by their local density, using a custom color gradient.

Usage

geom_dense_scatter(
  mapping = NULL,
  data = NULL,
  stat = "DenseScatter",
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  pal = NULL,
  size = 0.8,
  alpha = 1,
  ...
)

Arguments

mapping	Set of aesthetic mappings created by aes
data	The data to be displayed in this layer
position	Position adjustment, either as a string, or the result of a call to a position adjustment function
na.rm	If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them
pal	Color palette. A vector of colors to use for the density gradient, from lowest to highest density
size	Point size
alpha	Point alpha/transparency
...	Other arguments passed on to layer

Value

A ggplot2 layer that can be added to a plot

Examples

# Create large dataset with multiple clusters
library(ggplot2)
set.seed(60427)
n <- 1e4
df <- data.frame(
    x = c(rnorm(n * 0.5), rnorm(n * 0.3, 3, 0.5), rnorm(n * 0.2, 0, 2)),
    y = c(rnorm(n * 0.5), rnorm(n * 0.3, 3, 0.5), rnorm(n * 0.2, 0, 2))
)

# Basic usage with default settings
ggplot(df, aes(x, y)) +
    geom_dense_scatter()

# Custom color palette to highlight density variations
ggplot(df, aes(x, y)) +
    geom_dense_scatter(
        pal = c("lightblue", "darkblue", "purple", "red"),
        size = 0.5
    )

# Create large dataset with non-linear relationship
x <- runif(n, -3, 3)
df2 <- data.frame(
    x = x,
    y = sin(x) * 2 + rnorm(n, 0, 0.5)
)

# Visualize non-linear relationship with density
ggplot(df2, aes(x, y)) +
    geom_dense_scatter(
        pal = c("gray90", "gray50", "orange", "red"),
        size = 0.4,
        alpha = 0.8
    ) +
    labs(title = "Non-linear Pattern with Density Coloring")

# Create large dataset with varying spread
x <- rnorm(n)
df3 <- data.frame(
    x = x,
    y = x * rnorm(n, mean = 1, sd = abs(x) / 2)
)

# Visualize heteroscedastic pattern
ggplot(df3, aes(x, y)) +
    geom_dense_scatter(
        pal = c("#F5F5F5", "#4169E1", "#FF4500"),
        size = 0.3
    ) +
    theme_minimal() +
    labs(title = "Varying Spread Pattern")

tanaylab/tgutil documentation built on April 12, 2025, 8:52 p.m.