cojam: Merge two 'JAM' models
In simisc/cojam: Multi-variant colocalisation with summary genetic association data

Combines samples from the posterior model space of two JAM models, allowing posterior inference about colocalisation, i.e. about the existence of one or more shared variants that are associated with both outcome traits.

1	cojam(jam_res_1, jam_res_2)

`jam_res_1`	A `R2BGLiMS_Results-class` object, from running `JAM` for trait 1.
`jam_res_2`	A `R2BGLiMS_Results-class` object, from running `JAM` for trait 2.

A list containing the following elements:

bayes_factor

Bayes Factor for H4 versus H3.

posterior_overlap

Posterior probability of H4 U H3.

model_info

Extra info for other functions / post-processing:

models_grid: All sampled configurations (joint JAM models) and their posterior counts.
implied_prior_odds_43: Prior odds of H4 versus H3 that would have been implied under an assumption of independence between traits. Provided as a sanity check for user-supplied priors, which should usually promote H4 vs H3 (i.e. user supplied prior_odds_43 should usually be greater than implied_prior_odds_43).