ibdBootstrap: Bootstrap estimation of IBD coefficients

In forrel: Forensic Pedigree Analysis and Relatedness Inference

Bootstrap estimation of IBD coefficients

Description

This function produces (parametric or nonparametric) bootstrap estimates of the IBD coefficients between two individuals; either the three \kappa -coefficients or the nine condensed identity coefficients \Delta (see ibdEstimate()).

Usage

ibdBootstrap(
  x = NULL,
  ids = NULL,
  param = NULL,
  kappa = NULL,
  delta = NULL,
  N,
  method = "parametric",
  freqList = NULL,
  plot = TRUE,
  seed = NULL
)

Arguments

x	A ped object, or a list of such. If method = "parametric", this is only used to extract the allele frequencies, and can be skipped if freqList is provided.
ids	A pair of ID labels.
param	Either NULL (default), "kappa" or "delta". (See below.)
kappa, delta	Probability vectors of length 3 (kappa) or 9 (delta). Exactly one of param, kappa and delta must be non-NULL. If kappa and delta are both NULL, the appropriate set of coefficients is computed as ibdEstimate(x, ids, param).
N	The number of simulations.
method	Either "parametric" (default) or "nonparametric". Abbreviations are allowed. see Details for more information about each method.
freqList	A list of probability vectors: The allele frequencies for each marker.
plot	A logical, only relevant for bootstraps of kappa. If TRUE, the bootstrap estimates are plotted in the IBD triangle.
seed	An integer seed for the random number generator (optional).

Details

The parameter method controls how bootstrap estimates are obtained in each replication:

• "parametric": new profiles for two individuals are simulated from the input coefficients, followed by a re-estimation of the coefficients.

• "nonparametric": the original markers are sampled with replacement, before the coefficients are re-estimated.

Note that the pedigree itself does not affect the output of this function; the role of x is simply to carry the marker data.

Value

A data frame with N rows containing the bootstrap estimates. The last column, dist, gives the Euclidean distance to the original coefficients (either specified by the user or estimated from the data), viewed as a point in R^3 (kappa) or R^9 (delta).

See Also

ibdEstimate()

Examples

# Frequency list of 15 standard STR markers
freqList = NorwegianFrequencies[1:15]

# Number of bootstrap simulations (increase!)
N = 5

# Bootstrap estimates for kappa of full siblings
boot1 = ibdBootstrap(kappa = c(0.25, .5, .25), N = N, freqList = freqList)
boot1

# Mean deviation
mean(boot1$dist)

# Same, but with the 9 identity coefficients.
delta = c(0, 0, 0, 0, 0, 0, .25, .5, .25)
boot2 = ibdBootstrap(delta = delta, N = N, freqList = freqList)

# Mean deviation
mean(boot2$dist)

#### Non-parametric bootstrap.
# Requires `x` and `ids` to be provided

x = nuclearPed(2)
x = markerSim(x, ids = 3:4, N = 50, alleles = 1:10, seed = 123)

bootNP = ibdBootstrap(x, ids = 3:4, param = "kappa", method = "non", N = N)

# Parametric bootstrap can also be done with this syntax
bootP = ibdBootstrap(x, ids = 3:4, param = "kappa", method = "par", N = N)

forrel documentation built on April 12, 2025, 2:12 a.m.