To calculate the genetic variance under the random regression model, you need to identify the pol()
coefficients used by ASReml (they are reported in the .res file) for the particular age of interest.
Then use these to pre and post multiply the variance matrix.

polcoeff <- c(1.000, .125, .325, .425) # values from .res file
rrmat <- matrix(c(
7.695 , 0.2049 , -0.7956 , 0.7513,
0.9376 , 2.721 , 0.3095 , -0.3744,
-3.456 , 0.7996 , 2.453 , -0.7301,
3.042 , -0.9014 , -1.669 , 2.131 ),4,4)
# values from .asr file (but Upper is correlation)
rrmat[lower.tri(rrmat)]<- 0
rrmat <- rrmat+t(rrmat)-diag(diag(rrmat))
rrmat
[1,] 7.6950 0.9376 -3.4560 3.0420
[2,] 0.9376 2.7210 0.7996 -0.9014
[3,] -3.4560 0.7996 2.4530 -1.6690
[4,] 3.0420 -0.9014 -1.6690 2.1310
>
t(polcoeff) %*% rrmat %*% polcoeff
[,1]
[1,] 8.463358

Thus you have the genetic variance for the age corresponding to the coefficients used.
Then proceed with the heritability depending on the structure of the rest of the model.
## See Also

See also Fischer, Gilmour and van der Werf (2004) Genetics Selection and Evolution 36:363-369
ARG 25 Oct 2008

More queries
**Return to start**