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BeviMed (version 6.0)

Bayesian Evaluation of Variant Involvement in Mendelian Disease

Description

A fast integrative genetic association test for rare diseases based on a model for disease status given allele counts at rare variant sites. Probability of association, mode of inheritance and probability of pathogenicity for individual variants are all inferred in a Bayesian framework - 'A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases', Greene et al 2017 .

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Version

Install

install.packages('BeviMed')

Monthly Downloads

658

Version

6.0

License

GPL (>= 2)

Maintainer

Daniel Greene

Last Published

April 29th, 2025

Functions in BeviMed (6.0)

print.BeviMed_summary

Print readable summary of BeviMed_summary object.
prob_association

Calculate probability of association
gamma0_evidence

Calculate marginal probability of observed case-control status y under model gamma = 0
subset_variants

Remove variants with no data for pathogenicity
sum_ML_over_PP

Calculate marginal likelihood from power posteriors output
tune_temperatures

Tune temperatures
tune_proposal_sds

Tune proposal standard deviation for MH sampled parameters
extract_prob_association

Extract the posterior probability of association
extract_gamma1_evidence

Extract evidence for model gamma = 1
prob_pathogenic

Calculate variant marginal probabilities of pathogencity
stop_chain

Apply the MCMC algorithm in blocks until conditions are met
stack_BeviMeds

Concatenate objects of class BeviMed_raw
prob_association_m

Calculate probability of association for one mode of inheritance
summary.BeviMed

Summarise a BeviMed object
print.BeviMed

Print readable summary of BeviMed object
print.BeviMed_m

Print BeviMed_m object
summary.BeviMed_m

Summarise a BeviMed_m object
CI_gamma1_evidence

Estimate confidence interval for estimated marginal likelihood
expected_explained

Calculate expected number of explained cases
conditional_prob_pathogenic

Calculate probability of pathogencity for variants conditional on mode of inheritance.
call_cpp

R interface to BeviMed c++ MCMC procedure
explaining_variants

Calculate expected number of pathogenic variants in cases
BeviMed-package

Bayesian Evaluation of Variant Involvement in Mendelian Disease
bevimed_polytomous

Model selection for multiple association models
extract_conditional_prob_pathogenic

Extract probability of pathogenicity for variant conditional on a given association model
bevimed

Bayesian Evaluation of Variant Involvement in Mendelian Disease
bevimed_m

Perform inference under model gamma = 1 conditional on mode of inheritance
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
extract_prob_pathogenic

Extract variant marginal probabilities of pathogenicity
extract_expected_explained

Extract expected number of explained cases
extract_explaining_variants

Extract expected number of pathogenic variants in cases