FLB: Full-likelihood Bayes factor

Description Usage Arguments Value References Examples

View source: R/FLB.R

Description

Computes the Bayes factor for co-segregation, as described by Thompson et al. (2003).

Usage

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FLB(
  x,
  carriers,
  noncarriers = NULL,
  freq,
  affected,
  unknown = NULL,
  proband,
  penetrances,
  liability = NULL,
  details = FALSE,
  plot = FALSE,
  ...
)

Arguments

x

A pedtools::ped() object.

carriers

A character vector (or coercible to such), containing the ID labels of pedigree members known to carry the variant in question.

noncarriers

A character vector (or coercible to such), containing the ID labels of pedigree members known not to carry the variant in question.

freq

A single number strictly between 0 and 1: the population frequency of the observed allele.

affected

The affected pedigree members.

unknown

Pedigree members with unknown affection status.

proband

The ID label of the proband. This person must also be in both carriers and affected.

penetrances

Either a numeric vector of length 3, corresponding to (f0, f1, f2) or a matrix or data frame with 3 columns. Each row contains the penetrance values of a liability class.

liability

A vector of length pedsize(x), containing for each pedigree member the row number of penetrances which should be used for that individual. (If penetrances is just a vector, it will be used for all classes.) If liability is NULL (the default), it is set to 1 for all individuals.

details

A logical, indicating if detailed output should be returned (for debugging purposes).

plot

A logical.

...

Optional plot parameters passed on to pedtools::plot.ped().

Value

A positive number. If details = TRUE, a list of intermediate results is returned.

References

Thompson D, Easton DF, Goldgar DE. A full-likelihood method for the evaluation of causality of sequence variants from family data. Am J Hum Genet, 2003. doi: 10.1086/378100.

Examples

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x = nuclearPed(2)

FLB(x, carriers = 3:4, aff = 3:4, unknown = 1:2,
    freq = 0.0001, penetrances = c(0, 1, 1), proband = 3)

segregatr documentation built on April 15, 2021, 9:11 a.m.