In the following example, an inbreeding analysis is performed for a complicated pedigree. This analysis includes computing selective matings of some individuals and inbreeding coefficients of all individuals. Also, inbreeding coefficients are averaged within sex categories. The following statements produce Output 10.2.1:
data Swine; input Swine_Number $ Sire $ Dam $ Sex $; datalines; 3504 2200 2501 M 3514 2521 3112 F 3519 2521 2501 F 2501 2200 3112 M 2789 3504 3514 F 3501 2521 3514 M 3712 3504 3514 F 3121 2200 3501 F ;
title 'Least Related Matings'; proc inbreed data=Swine ind average; var Swine_Number Sire Dam; matings 2501 / 3501 3504 , 3712 / 3121; gender Sex; run;
Note the following from Output 10.2.1:
Observation 4, which defines Swine_Number=2501, should precede the first and third observations where the progeny for 2501 are given. PROC INBREED ignores observation 4 since it is given out of order. As a result, the parents of 2501 are missing or unknown.
The first column in the "Inbreeding Averages" table corresponds to the averages taken over the on-diagonal elements of the inbreeding coefficients matrix, and the second column gives averages over the off-diagonal elements.
Least Related Matings |
Inbreeding Coefficients of Individuals | |||
---|---|---|---|
Swine_Number | Sire | Dam | Coefficient |
2200 | . | ||
2501 | . | ||
3504 | 2200 | 2501 | . |
2521 | . | ||
3112 | . | ||
3514 | 2521 | 3112 | . |
3519 | 2521 | 2501 | . |
2789 | 3504 | 3514 | . |
3501 | 2521 | 3514 | 0.2500 |
3712 | 3504 | 3514 | . |
3121 | 2200 | 3501 | . |
Inbreeding Coefficients of Matings | ||
---|---|---|
Sire | Dam | Coefficient |
2501 | 3501 | . |
2501 | 3504 | 0.2500 |
3712 | 3121 | 0.1563 |
Averages of Inbreeding Coefficient Matrix | ||
---|---|---|
Inbreeding | Coancestry | |
Male X Male | 0.0625 | 0.1042 |
Male X Female | . | 0.1362 |
Female X Female | 0.0000 | 0.1324 |
Over Sex | 0.0227 | 0.1313 |
Number of Males | 4 |
---|---|
Number of Females | 7 |
Number of Individuals | 11 |