Coloc data through Bayes factors — coloc.bf

Colocalise two datasets represented by Bayes factors

coloc.bf_bf(
  bf1,
  bf2,
  p1 = 1e-04,
  p2 = 1e-04,
  p12 = 5e-06,
  overlap.min = 0.5,
  trim_by_posterior = TRUE
)

Arguments

bf1: named vector of log BF, or matrix of BF with colnames (cols=snps, rows=signals)
bf2: named vector of log BF, or matrix of BF with colnames (cols=snps, rows=signals)
p1: prior probability a SNP is associated with trait 1, default 1e-4
p2: prior probability a SNP is associated with trait 2, default 1e-4
p12: prior probability a SNP is associated with both traits, default 1e-5
overlap.min: see trim_by_posterior
trim_by_posterior: it is important that the signals to be colocalised are covered by adequate numbers of snps in both datasets. If TRUE, signals for which snps in common do not capture least overlap.min proportion of their posteriors support are dropped and colocalisation not attempted.

coloc.signals style result

This is the workhorse behind many coloc functions

Chris Wallace