Hc.cutoff.fdr           Estimate the Hc.cutoff for the required FDR
adjust_priors           adjust_priors
average_piks            Average of priors: pnk, pak and pck
average_piks_list       Average of priors: pnk, pak and pck from list
                        (memory intensive)
average_posterior_prob
                        Average of posterior probabilities: Hn, Ha and
                        Hc
average_posterior_prob_list
                        Average of posterior probabilities: Hn, Ha and
                        Hc from list (memory intensive)
combine.bf              combine.bf
cophe.hyp.predict       Predict cophescan hypothesis for tested
                        associations
cophe.multitrait        Run cophescan on multiple traits at once
cophe.single            Bayesian cophescan analysis using Approximate
                        Bayes Factors
cophe.single.lbf        cophe.single.lbf
cophe.susie             run 'cophe.susie' using susie to detect
                        separate signals
cophe.susie.lbf         cophe.susie.lbf
cophe_heatmap           Heatmap of multi-trait cophescan results
cophe_multi_trait_data
                        Simulated multi-trait data
cophe_plot              cophe_plots showing the Ha and Hc of all traits
                        and labelled above the specified threshold
cophescan-package       The 'cophescan' package.
get_beta                Extract beta and p-values of queried variant
get_posterior_prob      Calculation of the posterior prob of Hn, Ha and
                        Hc
hypothesis.priors       hypothesis.priors
logd_alpha              dnorm for alpha
logd_beta               dgamma for beta
logd_gamma              dgamma for gamma
loglik                  Log likelihood calculation
logpost                 Log posterior calculation
logpriors               Calculate log priors
logsum                  logsum
logsumexp               Log sum
metrop_run              Run the hierarchical mcmc model to infer priors
multitrait.simplify     Simplifying the output obtained from
                        'cophe.multitrait', 'cophe.single' or
                        'cophe.susie'
pars2pik                Conversion of parameters alpha, beta and gamma
                        to pnk, pak and pck
pars_init               Initiate parameters alpha, beta and gamma
per.snp.priors          per.snp.priors
piks                    List of priors: pn, pa and pc over all
                        iterations
plot_trait_manhat       Plot region Manhattan for a trait highlighting
                        the queried variant
posterior_prob          List of posterior probabilities: Hn, Ha and Hc
                        over all iterations
prepare_plot_data       Prepare data for plotting
propose                 Proposal distribution
run_metrop_priors       Run the hierarchical Metropolis Hastings model
                        to infer priors
sample_alpha            sample alpha
sample_beta             sample beta
sample_gamma            sample gamma
summary.cophe           print the summary of results from cophescan
                        single or susie
target                  Target distribution
