coloc.bf_bf: Coloc data through Bayes factors

Description Usage Arguments Details Value Author(s)

View source: R/susie.R

Description

Colocalise two datasets represented by Bayes factors

Usage

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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 BF, or matrix of BF with colnames (cols=snps, rows=signals)

bf2

named vector of 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.

Details

This is the workhorse behind many coloc functions

Value

coloc.signals style result

Author(s)

Chris Wallace


chr1swallace/coloc documentation built on June 10, 2021, 8:38 p.m.