Infer probabilities of association between disease label and locus and posterior parameter values under BeviMed model.
bevimed(
y,
G,
ploidy = rep(2L, length(y)),
prior_prob_association = 0.01,
prior_prob_dominant = 0.5,
dominant_args = NULL,
recessive_args = NULL,
...
)Logical vector of case (TRUE) control (FALSE) status.
Integer matrix of variant counts per individual, one row per individual and one column per variant.
Integer vector giving ploidy of samples.
The prior probability of association.
The prior probability of dominant inheritance given that there is an association.
Arguments to pass to bevimed_m conditioning on dominant inheritance.
Arguments to pass to bevimed_m conditioning on recessive inheritance.
Arguments to be passed to bevimed_m for both modes of inheritance.
BeviMed object containing results of inference.
Greene et al., A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases, The American Journal of Human Genetics (2017), http://dx.doi.org/10.1016/j.ajhg.2017.05.015.
prob_association, bevimed_m, summary.BeviMed, bevimed_polytomous