likelihood: Pedigree likelihood

Description

Calculates various forms of pedigree likelihoods.

Usage

likelihood(x, locus1, locus2=NULL, theta=NULL, startdata=NULL, eliminate=0, 
           logbase=NULL)

likelihoodSNP(x, marker, theta=NULL, afreq=NULL, logbase=NULL, TR.MATR=NULL, 
              singleNum.geno=NULL)

Arguments

a linkdat object, with x$model different from NULL.

locus1

a marker object compatible with x.

locus2

either NULL, the character "disease", or a marker object compatible with x. See Details.

theta

the recombination rate between locus1 and locus2 (in likelihoodSNP: between the marker and the disease locus). To make biological sense theta should be between 0 and 0.5.

eliminate

mostly for internal use: a non-negative integer indicating the number of iterations in the internal genotype-compatibility algorithm. Positive values can save time if partialmarker is non-empty and the number of alleles is large.

logbase

a numeric, or NULL. If numeric the loglikelihood is returned, with logbase as basis for the logarithm.

marker

an integer between 0 and x$nMark, indicating which marker to use in the calculation.

afreq

a numeric containing the marker allele frequencies.

startdata

for internal use.

TR.MATR

for internal use: an 10*10*10 array with haplotype transmission probabilities, for speedy computation with diallelic markers.

singleNum.geno

for internal use: a numeric vector containing SNP genotypes coded as a single integer: 00 -> 0, 11 -> 1, 22 -> 2, 12/21 -> 3, 01/10 -> 4, 02/20 -> 5. If this is non-NULL the marker argument is ignored.

Value

The likeihood of the data. If the parameter logbase is numeric, the output is log(likelihood, logbase).

Details

The likelihoods are calculated using the Elston-Stewart algorithm. If locus2 = NULL, the result is the likelihood of the genotypes observed at the marker in locus1. If locus2 = "disease", the result is the likelihood of the marker genotypes in locus1, given the affection statuses of the pedigree members, the disease model and the recombination rate theta between the marker and disease loci. (This computation is central in parametric linkage analysis.) If locus2 is a marker object, the result is the likelihood of the genotypes at the two markers, given the recombination rate theta between them. The function likelihoodSNP is a fast version of the case locus2 = "disease", when the marker in locus1 is diallelic.

Examples

Run this code

data(toyped)
x = linkdat(toyped, model=1) #dominant model

lod1 = likelihoodSNP(x, marker=1, theta=0, logbase=10) - 
       likelihoodSNP(x, marker=1, theta=0.5, logbase=10)
lod2 = lod(x, markers=1, theta=0)
# should be the same:
stopifnot(identical(lod1, as.numeric(lod2)), round(lod1, 2)==0.3)