colocboost_plot: Plot visualization plot from a ColocBoost output.

In colocboost: Multi-Context Colocalization Analysis for QTL and GWAS Studies

Plot visualization plot from a ColocBoost output.

Description

colocboost_plot generates visualization plots for colocalization events from a ColocBoost analysis.

Usage

colocboost_plot(
  cb_output,
  y = "log10p",
  grange = NULL,
  plot_cos_idx = NULL,
  outcome_idx = NULL,
  plot_all_outcome = FALSE,
  plot_focal_only = FALSE,
  plot_focal_cos_outcome_only = FALSE,
  points_color = "grey80",
  cos_color = NULL,
  add_vertical = FALSE,
  add_vertical_idx = NULL,
  outcome_names = NULL,
  plot_cols = 2,
  variant_coord = FALSE,
  show_top_variables = FALSE,
  show_cos_to_uncoloc = FALSE,
  show_cos_to_uncoloc_idx = NULL,
  show_cos_to_uncoloc_outcome = NULL,
  plot_ucos = FALSE,
  plot_ucos_idx = NULL,
  title_specific = NULL,
  ylim_each = TRUE,
  outcome_legend_pos = "top",
  outcome_legend_size = 1.8,
  cos_legend_pos = c(0.05, 0.4),
  show_variable = FALSE,
  lab_style = c(2, 1),
  axis_style = c(2, 1),
  title_style = c(2.5, 2),
  ...
)

Arguments

cb_output	Output object from colocboost analysis
y	Specifies the y-axis values, default is "log10p" for -log10 transformed marginal association p-values.
grange	Optional plotting range of x-axis to zoom in to a specific region.
plot_cos_idx	Optional indices of CoS to plot
outcome_idx	Optional indices of outcomes to include in the plot. outcome_idx=NULL to plot only the outcomes having colocalization.
plot_all_outcome	Optional to plot all outcome in the same figure.
plot_focal_only	Logical, if TRUE only plots colocalization with focal outcome, default is FALSE.
plot_focal_cos_outcome_only	Logical, if TRUE only plots colocalization including at least on colocalized outcome with focal outcome, default is FALSE.
points_color	Background color for non-colocalized variables, default is "grey80".
cos_color	Optional custom colors for CoS.
add_vertical	Logical, if TRUE adds vertical lines at specified positions, default is FALSE
add_vertical_idx	Optional indices for vertical lines.
outcome_names	Optional vector of outcomes names for the subtitle of each figure. outcome_names=NULL for the outcome name shown in data_info.
plot_cols	Number of columns in the plot grid, default is 2. If you have many colocalization. please consider increasing this.
variant_coord	Logical, if TRUE uses variant coordinates on x-axis, default is FALSE. This is required the variable names including position information.
show_top_variables	Logical, if TRUE shows top variables for each CoS, default is FALSE
show_cos_to_uncoloc	Logical, if TRUE shows colocalization to uncolocalized outcomes to diagnose, default is FALSE
show_cos_to_uncoloc_idx	Optional indices for showing CoS to all uncolocalized outcomes
show_cos_to_uncoloc_outcome	Optional outcomes for showing CoS to uncolocalized outcomes
plot_ucos	Logical, if TRUE plots also trait-specific (uncolocalized) sets , default is FALSE
plot_ucos_idx	Optional indices of trait-specific (uncolocalized) sets to plot when included
title_specific	Optional specific title to display in plot title
ylim_each	Logical, if TRUE uses separate y-axis limits for each plot, default is TRUE
outcome_legend_pos	Position for outcome legend, default is "top"
outcome_legend_size	Size for outcome legend text, default is 1.2
cos_legend_pos	Proportion of the legend from (left edge, bottom edge), default as (0.05, 0.4) at the left - median position
show_variable	Logical, if TRUE displays variant IDs, default is FALSE
lab_style	Vector of two numbers for label style (size, boldness), default is c(2, 1)
axis_style	Vector of two numbers for axis style (size, boldness), default is c(2, 1)
title_style	Vector of two numbers for title style (size, boldness), default is c(2.5, 2)
...	Additional parameters passed to plot functions

Value

Visualization plot for each colocalization event.

Source

See detailed instructions in our tutorial portal: https://statfungen.github.io/colocboost/articles/Visualization_ColocBoost_Output.html

Examples

# colocboost example
set.seed(1)
N <- 1000
P <- 100
# Generate X with LD structure
sigma <- 0.9^abs(outer(1:P, 1:P, "-"))
X <- MASS::mvrnorm(N, rep(0, P), sigma)
colnames(X) <- paste0("SNP", 1:P)
L <- 3
true_beta <- matrix(0, P, L)
true_beta[10, 1] <- 0.5 # SNP10 affects trait 1
true_beta[10, 2] <- 0.4 # SNP10 also affects trait 2 (colocalized)
true_beta[50, 2] <- 0.3 # SNP50 only affects trait 2
true_beta[80, 3] <- 0.6 # SNP80 only affects trait 3
Y <- matrix(0, N, L)
for (l in 1:L) {
  Y[, l] <- X %*% true_beta[, l] + rnorm(N, 0, 1)
}
res <- colocboost(X = X, Y = Y)
colocboost_plot(res, plot_cols = 1)
colocboost_plot(res, plot_cols = 1, outcome_idx = 1:3)

colocboost documentation built on June 8, 2025, 11:07 a.m.