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BeviMed (version 3.0)

Bayesian Evaluation of Variant Involvement in Mendelian Disorders

Description

A fast integrative genetic association test for rare diseases.

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Version

Install

install.packages('BeviMed')

Monthly Downloads

658

Version

3.0

License

GPL (>= 2)

Maintainer

Daniel Greene

Last Published

February 16th, 2017

Functions in BeviMed (3.0)

CI_gamma1_evidence

Estimate confidence interval for estimated marginal likelihood by simulation

exact_evidence

Calculate exact evidence for model gamma=1

ccvt-package

extract_expected_explained

Extract expected number of cases explained by pathogenic conigurations of alleles from

explaining_variants

Get expected number of variants involved in cases explained by pathogenic conigurations of alleles

call_cpp

R interface to BeviMed c++ MCMC procedure

conditional_prob_pathogenic

Calculate probability of pathogencity for variants in region given an association between case label and the region

bevimed

Perform inference under model gamma = 1

extract_explaining_variants

Extract expected number of variants involved in cases explained by pathogenic conigurations of alleles from

expected_explained

Get expected number of cases explained by pathogenic configurations of alleles

lower_bound_gamma1_evidence

Calculate log lower bound for marginal probability of observations under model gamma = 1 by summing likelihood over pathogenic variant (z) configurations, or probabilities that individual variants are pathogenic.

gamma1_prob

Calculate probability of an association

prob_association

Calculate probability of an association between presence/absence of local genotype configuration and case-control label

gamma1_evidence

Calculate marginal probability of observed case-control status under model gamma = 1

log_BF

Calculate log Bayes factor between models gamma=1 and gamma=0 given the data

gamma0_evidence

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

print.BeviMed

Print readable summary of

print.BeviMed_summary

Print readable summary of

prob_pathogenic

Calculate probability of pathogencity for variants in region given a prior probability of association between case label and the region

extract_gamma1_evidence

Extract evidence for gamma = 1 model from

region_association_evidence

Calculate marginal probability of observed genotypes under 'pathogenic region' model

stack_BeviMeds

Concatenate objects of class

sum_ML_over_PP

Calculate the Marginal Likelihood by summation over power posterior likelihood exptectances

tune_proposal_sds

Tune the proposal standard deviations for the Metropolis-Hastings updates of either phi or omega

summary.BeviMed

Create summary of

tune_temperatures

Tune temperatures using interval bisection to minimimise Kullback-Liebler divergence between adjacent power posteriors

stop_chain

Apply the MCMC algorithm in blocks until conditions are met