Genetic correlation matrix

Heatmap of genetic correlations (rg) between traits, typically from LD Score Regression (LDSC). Includes significance indicators and hierarchical clustering of traits.

Usage

genetic_correlation(
  rg_matrix,
  p_matrix = NULL,
  sig_threshold = 0.05,
  sig_marker = "*",
  palette = "RdBu",
  cluster = TRUE,
  rg_range = c(-1, 1),
  cell_size = 2.8,
  show_values = TRUE,
  show_diagonal = FALSE,
  title = NULL
)

Arguments

rg_matrix

A symmetric matrix of genetic correlations, or a data.frame with columns: trait1, trait2, rg, se, p.

p_matrix

Optional matrix of p-values (same dimensions as rg_matrix). If rg_matrix is a data.frame with a p column, this is extracted automatically.

sig_threshold

P-value threshold for significance markers.

sig_marker

Character to mark significant correlations.

palette

Color palette: "RdBu" (default), "PRGn", "PiYG", or a vector of colors.

cluster

If TRUE, reorder traits by hierarchical clustering.

rg_range

Range for the color scale (default c(-1, 1)).

cell_size

Size of the text inside cells.

show_values

Show rg values inside cells.

show_diagonal

Show the diagonal (always 1.0).

title

Plot title.

Value

A ggplot object.

Examples

# Simulated genetic correlation matrix
traits <- c("BMI", "Height", "WHR", "T2D", "CAD")
rg <- matrix(c(
  1.0,  -0.1,  0.6,  0.4,  0.2,
 -0.1,   1.0, -0.3, -0.1,  0.0,
  0.6,  -0.3,  1.0,  0.3,  0.15,
  0.4,  -0.1,  0.3,  1.0,  0.5,
  0.2,   0.0,  0.15, 0.5,  1.0
), nrow = 5, dimnames = list(traits, traits))
genetic_correlation(rg)


# With clustering
genetic_correlation(rg, cluster = TRUE)


# PRGn palette, no clustering
genetic_correlation(rg, palette = "PRGn", cluster = FALSE)


# PiYG palette
genetic_correlation(rg, palette = "PiYG")