bevimed: Bayesian Evaluation of Variant Involvement in Mendelian...

Description Usage Arguments Value References See Also

View source: R/convenience.R

Description

Infer probabilities of association between disease label and locus and posterior parameter values under BeviMed model.

Usage

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bevimed(
  y,
  G,
  ploidy = rep(2L, length(y)),
  prior_prob_association = 0.01,
  prior_prob_dominant = 0.5,
  dominant_args = NULL,
  recessive_args = NULL,
  ...
)

Arguments

y

Logical vector of case (TRUE) control (FALSE) status.

G

Integer matrix of variant counts per individual, one row per individual and one column per variant.

ploidy

Integer vector giving ploidy of samples.

prior_prob_association

The prior probability of association.

prior_prob_dominant

The prior probability of dominant inheritance given that there is an association.

dominant_args

Arguments to pass to bevimed_m conditioning on dominant inheritance.

recessive_args

Arguments to pass to bevimed_m conditioning on recessive inheritance.

...

Arguments to be passed to bevimed_m for both modes of inheritance.

Value

BeviMed object containing results of inference.

References

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.

See Also

prob_association, bevimed_m, summary.BeviMed, bevimed_polytomous


BeviMed documentation built on Feb. 1, 2021, 1:06 a.m.