bio-causal-genomics-colocalization-analysis

coloc.abf Analysis

Goal: Test whether two traits share a causal variant at a GWAS locus using Bayesian colocalization.

Approach: Format summary statistics for each trait as named lists, run coloc.abf to compute posterior probabilities for five hypotheses (H0-H4), and interpret PP.H4 as evidence for a shared causal variant.

library(coloc)

## type = 'quant' (continuous) or 'cc' (case-control)

gwas_data <- list(
  beta = gwas_df$BETA,
  varbeta = gwas_df$SE^2,
  snp = gwas_df$SNP,
  position = gwas_df$POS,
  type = 'cc',           # Case-control study
  s = 0.3,               # Proportion of cases (required for cc)
  N = 50000              # Total sample size
)

eqtl_data <- list(
  beta = eqtl_df$BETA,
  varbeta = eqtl_df$SE^2,
  snp = eqtl_df$SNP,
  position = eqtl_df$POS,
  type = 'quant',        # Quantitative trait (expression)
  N = 500,               # eQTL sample size
  sdY = 1                # SD of trait (1 if already normalized)
)

## --- Run colocalization ---

result <- coloc.abf(dataset1 = gwas_data, dataset2 = eqtl_data)