Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses

Horizontal integration of summary statistics from different GWAS traits can be used to evaluate evidence for their shared genetic causality. One popular method to do this is a Bayesian method, coloc, which is attractive in requiring only GWAS summary statistics and no linkage disequilibrium estimates and is now being used routinely to perform thousands of comparisons between traits. Here we show that while most users do not adjust default software values, misspecification of prior parameters can substantially alter posterior inference. We suggest data driven methods to derive sensible prior values, and demonstrate how sensitivity analysis can be used to assess robustness of posterior inference. The flexibility…

• W
  Wellcome

  Award: WT107881
• WT
  Wellcome Trust

  Award: WT107881
• EB
  European Bioinformatics Institute
• NI
  National Institutes of Health

  Award: 00002
• MR
  Medical Research Council

  Awards: MC UU 00002/4, MC_UU_00002/4
• NH
  National Heart, Lung, and Blood Institute
• NI
  National Institute of Mental Health
• NI
  National Institute on Drug Abuse
• NH
  National Human Genome Research Institute
• NO
  NIH Office of the Director
• NC
  National Cancer Institute
• NI
  National Institute of Neurological Disorders and Stroke
• CF
  Common Fund