Bayesian Evaluation of Variant Involvement in Mendelian Disease

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Documentation for package ‘BeviMed’ version 5.10

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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BeviMed-package	Bayesian Evaluation of Variant Involvement in Mendelian Disease
BeviMed	Bayesian Evaluation of Variant Involvement in Mendelian Disease
bevimed	Bayesian Evaluation of Variant Involvement in Mendelian Disease
bevimed_m	Perform inference under model gamma = 1 conditional on mode of inheritance
bevimed_polytomous	Model selection for multiple association models
call_cpp	R interface to BeviMed c++ MCMC procedure
CI_gamma1_evidence	Estimate confidence interval for estimated marginal likelihood
conditional_prob_pathogenic	Calculate probability of pathogencity for variants conditional on mode of inheritance.
expected_explained	Calculate expected number of explained cases
explaining_variants	Calculate expected number of pathogenic variants in cases
extract_conditional_prob_pathogenic	Extract probability of pathogenicity for variant conditional on a given association model
extract_expected_explained	Extract expected number of explained cases
extract_explaining_variants	Extract expected number of pathogenic variants in cases
extract_gamma1_evidence	Extract evidence for model gamma = 1
extract_prob_association	Extract the posterior probability of association
extract_prob_pathogenic	Extract variant marginal probabilities of pathogenicity
gamma0_evidence	Calculate marginal probability of observed case-control status y under model gamma = 0
gamma1_evidence	Calculate evidence under model gamma = 1
log_BF	Calculate log Bayes factor between an association model with a given mode of inheritance and model gamma = 0
print.BeviMed	Print readable summary of 'BeviMed' object
print.BeviMed_m	Print 'BeviMed_m' object
print.BeviMed_summary	Print readable summary of 'BeviMed_summary' object.
prob_association	Calculate probability of association
prob_association_m	Calculate probability of association for one mode of inheritance
prob_pathogenic	Calculate variant marginal probabilities of pathogencity
stack_BeviMeds	Concatenate objects of class 'BeviMed_raw'
stop_chain	Apply the MCMC algorithm in blocks until conditions are met
subset_variants	Remove variants with no data for pathogenicity
summary.BeviMed	Summarise a 'BeviMed' object
summary.BeviMed_m	Summarise a 'BeviMed_m' object
sum_ML_over_PP	Calculate marginal likelihood from power posteriors output
tune_proposal_sds	Tune proposal standard deviation for MH sampled parameters
tune_temperatures	Tune temperatures