paramlink (version 0.2-1)

genoDistr: Genotype probability distribution

Description

Computes genotype probabilities of a single individual, conditional on existing markers and pedigree information. Only for diallelic markers at the moment.

Usage

genoDistr(x, id, partialmarker=NULL, t=0.5)

Arguments

x

a linkdat object.

id

an integer indicating the individual in question.

partialmarker

either NULL (indicating no given marker data), a single integer indicating the number of an existing marker, or a matrix with two columns giving alleles for each individual (0 = unkwown)

t

a numeric, the recombination fraction between marker and disease locus

Value

• If id is male and the model is X-linked: A probability vector of length 3 (if the model is autosomal or id is female) or 2 (if the model is X-linked and id is male), giving the probabilities for the different genotypes.

See Also

likelihood

Examples

data(toyped)
x = linkdat(toyped, model=1)
genoDistr(x, id = 1)

m1 = rbind(c(1,1),c(1,0),c(0,0),c(0,0))
genoDistr(x, id = 3, partialmarker = m1)

m2 = rbind(c(0,0),c(0,0),c("A","B"),c("A","B"))
genoDistr(x, id = 1, partialmarker = m2)

# gives Mendelian error (correctly):
m3 = rbind(c(1,1),c(1,1),c(2,2),c(0,0))
genoDistr(x, id = 4, partialmarker = m3)

# X-linked example
data(Xped)
y = linkdat(Xped, model=4) #X-linked recessive model
# create empty marker, and then give individuals 5 and 15 genotype AA:
y = setMarkers(y, matrix(0, ncol=2, nrow=15))
y = modifyMarker(y, id=c(5, 15), alleles=c('A', 'A'))	
genoDistr(y, id=13, partialmarker=1)	#results: A - 0.8; B - 0.2
genoDistr(y, id=13, partialmarker=1, t=0)	#results: A - 0.667; B - 0.333