linkage.power: Power of a linkage study

In paramlink: Parametric Linkage and Other Pedigree Analysis in R

Power of a linkage study

Description

Power analysis of parametric linkage studies

Usage

linkage.power(
  x,
  N = 100,
  available = x$available,
  afreq = c(0.5, 0.5),
  loop_breakers = NULL,
  threshold = NULL,
  seed = NULL,
  verbose = FALSE
)

## S3 method for class 'powres'
summary(object, threshold = NULL, ...)

Arguments

x	a linkdat object with a valid model. (See setModel.)
N	an integer; the number of markers to simulate.
available	a vector containing IDs of the available individuals, i.e. those whose genotypes should be simulated.
afreq	a numerical vector with sum 1; the population frequencies for the marker alleles.
loop_breakers	a numeric containing IDs of individuals to be used as loop breakers. Relevant only if the pedigree has loops. See breakLoops.
threshold	NULL, or a single numeric. If numeric, the output includes the percentage of simulated markers having LOD larger than threshold.
seed	NULL, or a numeric seed for the random number generator.
verbose	a logical passed on to linkageSim. If TRUE, some details are shown during the marker simulation.
object	a powres object, normally produced by linkage.power.
...	not used.

Value

The function prints a summary and returns invisibly a powres object, which is a list with the following entries:

sim	A linkdat object with the simulated markers
lod	The LOD scores (computed with recombination fraction theta=0) of the simulated markers
maxlod	The highest LOD score of the simulated markers
elod	The average LOD score for the simulated markers

returns the maximum LOD score for each element of values.

References

Marker simulation is inspired by the SLINK algorithm: https://www.jurgott.org/linkage/SLINK.htm.

See Also

linkdat, linkageSim

Examples

# Note: In the examples below N is set very low in order to reduce time consumption.
# Increase N to get more interesting results.

x = nuclearPed(3)
x = swapAff(x, c(1,3,4))
x = setModel(x, 1) # Autosomal dominant
linkage.power(x, N=1)

# X-linked recessive example:
y = linkdat(Xped, model=4)
linkage.power(y, N=1)

# Power of homozygosity mapping:
z = addOffspring(cousinPed(1), father=7, mother=8, noffs=1, aff=2)
z = setModel(z, 2) # Autosomal recessive model
pow = linkage.power(z, N=1, loop_breaker=7, seed=123)
stopifnot(round(pow$maxlod, 1) == 1.2)

paramlink documentation built on April 15, 2022, 9:06 a.m.