The INBREED Procedure

OUTCOV= Data Set

The OUTCOV= data set has the following variables:

  • a list of BY variables, if there is a BY statement

  • the generation variable, if there is a CLASS statement

  • the gender variable, if there is a GENDER statement

  • _Type_, a variable indicating the type of observation. The valid values of the _Type_ variable are ‘COV’ for covariance estimates and ‘INBREED’ for inbreeding coefficients.

  • _Panel_, a variable indicating the panel number used when populations delimited by BY groups contain different numbers of individuals. If there are n individuals in the first BY group and if any subsequent BY group contains a larger population, then its covariance/inbreeding matrix is divided into panels, with each panel containing n columns of data. If you put these panels side by side in increasing _Panel_ number order, then you can reconstruct the covariance or inbreeding matrix.

  • _Col_, a variable used to name columns of the inbreeding or covariance matrix. The values of this variable start with ‘COL’, followed by a number indicating the column number. The names of the individuals corresponding to any given column i can be found by reading the individual’s name across the row that has a _Col_ value of ‘COLi’. When the inbreeding or covariance matrix is divided into panels, all the rows repeat for the first n columns, all the rows repeat for the next n columns, and so on.

  • the variable containing the names of the individuals, that is, the first variable listed in the VAR statement

  • the variable containing the names of the first parents, that is, the second variable listed in the VAR statement

  • the variable containing the names of the second parents, that is, the third variable listed in the VAR statement

  • a list of covariance variables Col1Coln, where n is the maximum number of individuals in the first population

The functions of the variables _Panel_ and _Col_ can best be demonstrated by an example. Assume that there are three individuals in the first BY group and that, in the current BY group (Byvar=2), there are five individuals with the following covariance matrix.

COV

1

2

3

4

5

1

Cov(1,1)

Cov(1,2)

Cov(1,3)

Cov(1,4)

Cov(1,5)

2

Cov(2,1)

Cov(2,2)

Cov(2,3)

Cov(2,4)

Cov(2,5)

3

Cov(3,1)

Cov(3,2)

Cov(3,3)

Cov(3,4)

Cov(3,5)

4

Cov(4,1)

Cov(4,2)

Cov(4,3)

Cov(4,4)

Cov(4,5)

5

Cov(5,1)

Cov(5,2)

Cov(5,3)

Cov(5,4)

Cov(5,5)

 

 Panel 1 

 Panel 2 

Then the OUTCOV= data set appears as follows.

Byvar

_Panel_

_Col_

Individual

Parent

Parent2

Col1

Col2

Col3

2

1

COL1

1

   

Cov(1,1)

Cov(1,2)

Cov(1,3)

2

1

COL2

2

   

Cov(2,1)

Cov(2,2)

Cov(2,3)

2

1

COL3

3

   

Cov(3,1)

Cov(3,2)

Cov(3,3)

2

1

 

4

   

Cov(4,1)

Cov(4,2)

Cov(4,3)

2

1

 

5

   

Cov(5,1)

Cov(5,2)

Cov(5,3)

2

2

 

1

   

Cov(1,4)

Cov(1,5)

.

2

2

 

2

   

Cov(2,4)

Cov(2,5)

.

2

2

 

3

   

Cov(3,4)

Cov(3,5)

.

2

2

COL1

4

   

Cov(4,4)

Cov(4,5)

.

2

2

COL2

5

   

Cov(5,4)

Cov(5,5)

.

Notice that the first three columns go to the first panel (_Panel_=1), and the remaining two go to the second panel (_Panel_=2). Therefore, in the first panel, ‘COL1’, ‘COL2’, and ‘COL3’ correspond to individuals 1, 2, and 3, respectively, while in the second panel, ‘COL1’ and ‘COL2’ correspond to individuals 4 and 5, respectively.