[R-sig-ME] covariance problems in MCMCglmm. genetic effects and multiple membership

[Alexandre Martin]

Dear Szymek, 

Thank you again for your contribution with your last answer. 

I am wondering now how to write the model to estimate the covariance between
the “mm(…)” and the “animal” random parts. 

Jarrod wrote in this thread
(https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q4/017034.html) about
maternal genetic effects : “it is not yet possible to fit the covariance
between maternal genetic and direct genetic effects“

Since my model is similar to that described in the thread, is it still
impossible to fit a model to assess the covariance between direct and
indirect genetic effects in a way similar to that in ASReml as follow?

 

For y =Xb + Z1animal + Z2maternal + e 

Analysis of some kind

anim !P                       # The variable ‘anim’ is related to a pedigree
fil

dam !P                        # The variable ‘dam’ is related to a pedigree
file

dage 10 !A

rt 6 

wwt

grp 322 !A

example.ped

example.dat

wwt ~ mu rt dage !r anim dam !f grp 

0 0 1 

anim 2 

2 0 US !GP

.2 0 .15 

anim o AINV

 

 

Best 

 

Alexandre

 

 

De : Szymek Drobniak [mailto:szymek.drobniak at uj.edu.pl] 
Envoyé : 14 mai 2015 17:39
À : r-sig-mixed-models at r-project.org
Cc : alexandre.m.martin at gmail.com
Objet : Re: genetic effects and multiple membership in MCMCglmm (Alexandre
Martin)

 

Hello Alexandre,

 

using ped assigns a given correlation structure only to the "animal" random
effect. You have to create an inverse of A matrix:

 

my_inverse <- inverseA(ped)$Ainv

 

and assign it in MCMCglmm to specific random effects:

 

MCMCglmm(Y~1,
random=~animal+mm(m1+m2+m3),

ginverse=list(animal=my_inverse, m1=my_inverse,
m2=my_inverse,m3=my_inverse), data=dat, pr=T).

 

Cheers

Szymek


	[[alternative HTML version deleted]]