Re: variance modelling
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Re: variance modelling

This sounds like you are fitting a crossbreeding model since ua from breed
A and ub from breed B and the second generation will be the F1. ASREML
only fits additive genetic models and you really need to examine
if dominance is present and the covariance between the additive effects
from both parental generations.  It is unlikely that second generation
will be an exact 50:50 mixture of the two parent variances.

The paper by Lo et al. (1995? Journal of Animal Science) and other more
recent papers with Fito Cantet and Rohan Fernando (
appear to do what you want to do.  Although, you can't fit a very complex
model with 'two' generations.


On Mon, 27 Aug 2001, Joe Daley wrote:

> G'day Asreml
> I am trying to model some g2 data using a mixed model
> y = XB + Zu + e
> where u is (2*numg1 + numg2) vector, numg1 is the number of generation
> 1 animals and numg2 is the number of generation 2 animals.  Generation 1
> animals are comprised of sires and dams, numg1 = numsg1 + numdg1.
> u can be partitioned into u = [ ua | ub | a ]T, a is a random animal effect
> derived from the numerator relationship matrix.
> ua can be partitioned into ua = [ uas | uad ] and ub can be partitioned
> ub = [ ubs | ubd ], here a or b distinguish between two types of effects
> and s or d distinguish between sire or dam origin of the effect.
> where
> ua ~ (0, 2aGa) and ub ~ (0, 2bGb)
> this means that sire and dam a effects are coming from the same variance
> 2a with a known correlation structure Ga as sires and dams from g1
> are
> correlated with each other. Sire and dam b effects are similar.
> I am fitting the asreml model
> Traitname ~ mu  !r  sire.sirea  dam.dama  sire.sireb  dam.damb animal
> Here sire and dam are factors with a level for each sire and dam while
> Sirea, dama sireb and damb are the respective a or b coefficients for
> each g2 animal.
> Initially I want to set 2a = 2b so that all ua and ub
> effects are coming
> >From one variance, all the u's are now grouped.
> How do I get asreml to model traitname this way knowing that sirea, dama,
> sireb and damb are all from the one variance and relationships exist between
> sirea and dama and sireb and damb. I want to get a blup estimate
> for each level of sire and dam for both a and b effects and overlay the
> predetermined correlation matrices Ga and Gb.
> Secondly I want to repeat this without the constraint  2a =
> 2b , unequal
> Variances.
> Any help is appreciated.
> Cheers
> Joe Daley
> PhD researcher
> Central Queensland University
> --
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