ggrecipes (version 0.1.0)

gg_splitcorr: Split-Correlation Heatmap

Description

Creates a split-correlation plot where the upper triangle shows correlations for one subgroup and the lower triangle for another, based on a binary splitting variable. This allows quick visual comparison of correlation structures between two groups. Significant correlations (after multiple testing adjustment) can be labeled directly in the plot.

Usage

gg_splitcorr(
  data,
  split,
  style = "tile",
  method = "pearson",
  padjust = "BH",
  use = "complete.obs",
  colors = c("blue", "white", "red"),
  text_colors = c("white", "black"),
  text_size = 3.5,
  border_color = "black",
  prefix = NULL,
  linetype = "dashed",
  linealpha = 0.5,
  offset = 0.75
)

Value

A ggplot2 object showing the split-correlation heatmap. The plot displays:

• Upper triangle: correlations for the first level of the split variable

• Lower triangle: correlations for the second level of the split variable

• Diagonal line separating the two triangles

• Group labels indicating which split level is shown in each triangle

• Correlation values displayed only for significant pairs (p < 0.05 after adjustment)

• Color gradient representing correlation strength (-1 to 1)

• Optional point size (if style = "point") indicating absolute correlation strength

Arguments

data

A data frame containing numeric variables to correlate and the variable to split by.

split

A character string specifying the name of the binary variable in data used to split the dataset.

style

Type of visualization; either "tile" (default) for a heatmap or "point" for a bubble-style plot.

method

Correlation method to use; either "pearson" (default) or "spearman".

padjust

Method for p-value adjustment, passed to p.adjust (default "BH").

use

Handling of missing values, passed to cor (default "complete.obs").

colors

A vector of three colors for the low, mid, and high values of the correlation scale (default c("blue", "white", "red")).

text_colors

A vector of two colors for the text labels, used for negative and positive correlations (default c("white", "black")).

text_size

Numeric value giving the size of correlation text labels (default 3.5).

border_color

Color for tile or point borders (default "black").

prefix

Character string prefix for group labels. If NULL (default), uses "split_variable = " format. Default is NULL.

linetype

Type of diagonal line separating upper and lower triangles; one of "solid", "dashed", or "dotdash" (default "dashed").

linealpha

Alpha transparency for the diagonal line (default 0.5).

offset

Numeric offset for the position of the group labels (default 0.75).

Details

The function:

1. Splits the dataset into two groups using the variable specified by split.

2. Computes pairwise correlations and p-values for each group (via a helper cor_p()).

3. Combines the upper triangle from one group and lower triangle from the other.

4. Adjusts p-values using the selected method and annotates significant cells.

The result is a heatmap (or bubble plot) showing both groups' correlation patterns in a single compact visualization.

See Also

cor for correlation computation, p.adjust for multiple testing correction, geom_tile, geom_point

Examples

# Compare correlations between V-shaped vs straight engines
data(mtcars)

gg_splitcorr(
  data = mtcars,
  split = "vs",
  prefix = "Engine Type: "
)

# Alternative style "point"
gg_splitcorr(
  data = mtcars,
  split = "vs",
  style = "point",
  method = "spearman",
  prefix = "Engine Type: "
)