Currently HyPrColoc requires effect estimates and associated standard errors as inputs. My understanding from the manuscript is that ultimately approximate Bayes factors are used when evaluating for colcalization. I'm curious whether Bayes factors could be directly used as input? My particular use case would be using results from a GWAS meta-analysis performed using MR-MEGA (https://pubmed.ncbi.nlm.nih.gov/28911207/), which will directly provide Bayes factors as output (but doesn't provide effect estimates due to the underlying nature of mega-regression).
Currently HyPrColoc requires effect estimates and associated standard errors as inputs. My understanding from the manuscript is that ultimately approximate Bayes factors are used when evaluating for colcalization. I'm curious whether Bayes factors could be directly used as input? My particular use case would be using results from a GWAS meta-analysis performed using MR-MEGA (https://pubmed.ncbi.nlm.nih.gov/28911207/), which will directly provide Bayes factors as output (but doesn't provide effect estimates due to the underlying nature of mega-regression).