Adaptation of the Coloc Method for PheWAS

[Up] [Top]

Documentation for package ‘cophescan’ version 1.4.1

Help Pages

cophescan-package The 'cophescan' package.
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)
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
cophescan The 'cophescan' package.
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
get_beta Extract beta and p-values of queried variant
get_posterior_prob Calculation of the posterior prob of Hn, Ha and Hc
Hc.cutoff.fdr Estimate the Hc.cutoff for the required FDR
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