kinship2 (version 1.3.1)

kinship: Compute a kinship matrix

Description

Compute the kinship matrix for a set of related autosomal subjects. The function is generic, and can accept a pedigree, pedigreeList, or vector as the first argument.

Usage

kinship(id, ...)
kinship.default(id, dadid, momid, ...)

Arguments

id

either a pedigree object, pedigreeList object, or a vector of subject identifiers. Subject identifiers may be numeric or character.

dadid

for each subject, the identifier of the biological father. This is only used if id is a vector.

momid

for each subject, the identifier of the biological mother. This is only used if id is a vector.

...

Any number of optional arguments

Value

• a matrix of kinship coefficients.

References

K Lange, Mathematical and Statistical Methods for Genetic Analysis, Springer-Verlag, New York, 1997.

Details

The function will usually be called with a pedigree or pedigreeList; the third form is provided for backwards compatability with an earlier version that was less capable. The first argument is named id for the same reason.

When called with a pedigreeList, i.e., with multiple families, the routine will create a block-diagonal-symmetric bdsmatrix object. Since the [i,j] value of the result is 0 for any two unrelated individuals i and j and a bdsmatix utilizes sparse representation, the resulting object is often orders of magnitude smaller than an ordinary matrix. When called with a single pedigree and ordinary matrix is returned. Two genes G1 and G2 are identical by descent (IBD) if they are both physical copies of the same ancestral gene; two genes are identical by state if they represent the same allele. So the brown eye gene that I inherited from my mother is ibd with hers; the same gene in an unrelated individual is not.

The kinship coefficient between two subjects is the probability that a randomly selected allele from an autosomal locus will be IBD between them. It is obviously 0 between unrelated individuals, 0.5 for an individual with themselves (we could choose the same allele twice), .25 between mother and child, etc.

The computation is based on a recursive algorithm described in Lange, which assumes the marker autosomal in diploid subjects, and that the founder alleles are independent. It is unfortunately not vectorizable within family, so the code can be slow for very large families.

See Also

pedigree, makekinship,makefamid

Examples

test1 <- data.frame(id  =c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14),
                    mom =c(0, 0, 0, 0, 2, 2, 4, 4, 6,  2,  0,  0, 12, 13),
                    dad =c(0, 0, 0, 0, 1, 1, 3, 3, 3,  7,  0,  0, 11, 10),
                    sex =c(0, 1, 0, 1, 0, 1, 0, 1, 0,  0,  0,  1,  1,  1))
tped <- with(test1, pedigree(id, dad, mom, sex))
round(8*kinship(tped))