Imaginings of a Livestock Geneticist

Recursive Method to Generate Partial Kinship and
Inbreeding Coefficients Across Founders

This section describes how to calculate a partial kinship matrix and partial inbreeding coefficient with respect to a given founder individual and was initially described in the Lacy et al. (1996) paper. A supplemental manuscript that provides an example is Gulisija & Crow (2007). A partial kinship matrix traces only alleles descending from a specific founder individual. A founder individual is an individual with both parents unknown and is therefore considered unrelated to all other individuals in a pedigree other than their descendants. Similarly, a partial inbreeding coefficient measures the probability that an individual is homozygous (identical by descent) for an allele descended from a given founder. To compute partial inbreeding coefficients, a distinct partial kinship matrix is built for each founder. The sum of partial kinship matrices corresponding to all founder individuals yields a matrix of kinship coefficients between individuals. As mentioned in the previous section, Recursive Method to Create A, the numerator relationship matrix is twice the co-ancestry or kinship coefficient and is a great way to confirm the calculation is correct.

The following pedigree file from Gulisija & Crow (2007) can be utilized with the R code above. The columns are animal, sire and dam and the pedigree is already ordered so that parents come before progeny. Lastly the animals go from 1 to the total number of animals. Outlined below is what the partial kinship matrix for founder 1 looks like at the end of each iteration of the for loop. The last iteration will provide the partial inbreeding values across all non-founder individuals.

Prior to For Loop
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loop Iteration 1 (i.e. i = 4)
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.25 0.0 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.25 0.0 0.0 0.25 0.0 0.0 0.0 0.0 0.0
5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loop Iteration 2 (i.e. i = 5)
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.25 0.375 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.25 0.0 0.0 0.25 0.25 0.0 0.0 0.0 0.0
5 0.375 0.0 0.0 0.25 0.50 0.0 0.0 0.0 0.0
6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loop Iteration 3 (i.e. i = 6)
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.25 0.375 0.125 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.25 0.0 0.0 0.25 0.25 0.125 0.0 0.0 0.0
5 0.375 0.0 0.0 0.25 0.50 0.125 0.0 0.0 0.0
6 0.125 0.0 0.0 0.125 0.125 0.125 0.0 0.0 0.0
7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loop Iteration 4 (i.e. i = 7)
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.25 0.375 0.125 0.25 0.0 0.0
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.25 0.0 0.0 0.25 0.25 0.125 0.188 0.0 0.0
5 0.375 0.0 0.0 0.25 0.50 0.125 0.313 0.0 0.0
6 0.125 0.0 0.0 0.125 0.125 0.125 0.125 0.0 0.0
7 0.25 0.0 0.0 0.188 0.313 0.125 0.312 0.0 0.0
8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Loop Iteration 5 (i.e. i = 8)
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.25 0.375 0.125 0.25 0.25 0.0
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.25 0.0 0.0 0.25 0.25 0.125 0.188 0.188 0.0
5 0.375 0.0 0.0 0.25 0.50 0.125 0.313 0.313 0.0
6 0.125 0.0 0.0 0.125 0.125 0.125 0.125 0.125 0.0
7 0.25 0.0 0.0 0.188 0.313 0.125 0.312 0.219 0.0
8 0.25 0.0 0.0 0.188 0.313 0.125 0.219 0.313 0.0
9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Partial Inbreeding Coefficient
4 5 6 7 8 9
0.00000 0.25000 0.00000 0.12500 0.12500 0.21875
A: Loop Iteration 6 (i.e. i = 9)
1 2 3 4 5 6 7 8 9
1 0.5 0.0 0.0 0.25 0.375 0.125 0.25 0.25 0.25
2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
4 0.25 0.0 0.0 0.25 0.25 0.125 0.188 0.188 0.188
5 0.375 0.0 0.0 0.25 0.50 0.125 0.313 0.313 0.313
6 0.125 0.0 0.0 0.125 0.125 0.125 0.125 0.125 0.125
7 0.25 0.0 0.0 0.188 0.313 0.125 0.312 0.219 0.266
8 0.25 0.0 0.0 0.188 0.313 0.125 0.219 0.313 0.266
9 0.25 0.0 0.0 0.188 0.313 0.125 0.266 0.266 0.359

References