Description Usage Arguments Details Value Author(s) References Examples
The likelihood()
and likelihood2()
functions constitute the heart of
pedprobr. The former computes the pedigree likelihood for each indicated
marker. The latter computer the likelihood for a pair of linked markers
separated by a given recombination rate.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36  likelihood(x, ...)
## S3 method for class 'ped'
likelihood(
x,
markers = NULL,
peelOrder = NULL,
eliminate = 0,
logbase = NULL,
loop_breakers = NULL,
verbose = FALSE,
theta = 0,
...
)
## S3 method for class 'list'
likelihood(x, markers = NULL, logbase = NULL, ...)
likelihood2(x, ...)
## S3 method for class 'ped'
likelihood2(
x,
marker1,
marker2,
rho,
peelOrder = NULL,
eliminate = 0,
logbase = NULL,
loop_breakers = NULL,
verbose = FALSE,
...
)
## S3 method for class 'list'
likelihood2(x, marker1, marker2, logbase = NULL, ...)

x 
A 
... 
Further arguments. 
markers 
One or several markers compatible with

peelOrder 
For internal use. 
eliminate 
Mostly for internal use: a nonnegative integer indicating the number of iterations in the internal genotypecompatibility algorithm. Positive values can save time if the number of alleles is large. 
logbase 
Either NULL (default) or a positive number indicating the
basis for logarithmic output. Typical values are 
loop_breakers 
A vector of ID labels indicating loop breakers. If NULL
(default), automatic selection of loop breakers will be performed. See

verbose 
A logical. 
theta 
Theta correction. 
marker1, marker2 
Single markers compatible with 
rho 
The recombination rate between 
The implementation is based on the peeling algorithm of Elston and Stewart (1971). A variety of situations are covered; see the Examples section for some demonstrations.
complex inbred pedigrees
pedigrees with inbred founders
autosomal and Xlinked markers
a single marker or two linked markers
markers with mutation models
A numeric with the same length as the number of markers indicated by
markers
. If logbase
is a positive number, the output is
log(likelihood, logbase)
.
Magnus Dehli Vigeland
Elston and Stewart (1971). A General Model for the Genetic Analysis of Pedigree Data. doi: https://doi.org/10.1159/000152448
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32  ### Example 1: Likelihood of trio with inbred father
x = cousinPed(0, child = TRUE)
x = addSon(x, 5)
x = relabel(x, old = 5:7, new = c("father", "mother", "child"))
# Equifrequent SNP marker: father homozygous, child heterozygous
m = marker(x, father = 1, child = 1:2)
x = addMarkers(x, m)
# Plot with genotypes
plot(x, marker = 1)
# Compute the likelihood
lik1 = likelihood(x, markers = 1)
### Example 2: Same as above, but using founder inbreeding
# Extract the trio
y = subset(x, c("father", "mother", "child"))
# Indicate that the father has inbreeding coefficient 1/4
founderInbreeding(y, "father") = 1/4
# Plot (notice the inbreeding coefficient)
plot(y, marker = 1)
# Likelihood should be the same as above
lik2 = likelihood(y, markers = 1)
stopifnot(all.equal(lik1, lik2))

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