get_ucos_summary {colocboost}R Documentation

Get trait-specific summary table from a ColocBoost output.

Description

get_ucos_summary produces a trait-specific summary table for uncolocalized (single-trait) associations from ColocBoost results. This is particularly useful for examining trait-specific signals or for summarizing results from single-trait FineBoost analyses.

Usage

get_ucos_summary(
  cb_output,
  outcome_names = NULL,
  region_name = NULL,
  ambiguous_cos = FALSE,
  min_abs_corr_between_ucos = 0.5,
  median_abs_corr_between_ucos = 0.8
)

Arguments

cb_output

Output object from colocboost analysis

outcome_names

Optional vector of names of outcomes, which has the same order as Y in the original analysis.

region_name

Optional character string. When provided, adds a column with this gene name to the output table for easier filtering in downstream analyses.

ambiguous_cos

Logical indicating whether to include ambiguous colocalization events. The default is FALSE.

min_abs_corr_between_ucos

Minimum absolute correlation for variants across two trait-specific (uncolocalized) effects to be considered colocalized. The default is 0.5.

median_abs_corr_between_ucos

Median absolute correlation for variants across two trait-specific (uncolocalized) effects to be considered colocalized. The default is 0.8.

Value

A list containing:

Source

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

See Also

Other colocboost_utilities: get_cormat(), get_cos(), get_cos_purity(), get_cos_summary(), get_hierarchical_clusters()

Examples

# colocboost example with single trait analysis
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 <- 1  # Only one trait for single-trait analysis
true_beta <- matrix(0, P, L)
true_beta[10, 1] <- 0.5 # SNP10 affects the trait
true_beta[80, 1] <- 0.2 # SNP11 also affects the trait but with lower effect
Y <- X %*% true_beta + rnorm(N, 0, 1)
res <- colocboost(X = X, Y = Y, output_level = 2)
# Get the trait-specifc effect summary
get_ucos_summary(res)


[Package colocboost version 1.0.4 Index]