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  ASReml  ~  how to get genetic correlation in multivariate GBLUP model

MaoHuang
Posted: Wed Dec 05, 2018 5:09 pm Reply with quote
Joined: 19 Nov 2018 Posts: 3
Hi all,
I am trying to fit multi-trait GBLUP model with the known the ginverse matrix termed as gmatrix (the inverse of additive relationship matrix calculated from marker data).
I used the below model:
modelGBLUP<-asreml(fixed=cbind(tr1,tr2,tr3)~trait,rcov=~units:us(trait),random=~corh(trait):giv(ID),ginverse=list(ID=gmatrix),na.method.Y="include",data=Y)

I then obtained:
summary(modelGBLUP)$varcomp

I got output with
gamma component std_error Z.ratio constraint
tr1 tr1 1.672322483. 1.672322483
tr2 tr1. -1.15232172. -1.15232172
tr2 tr2. 4.952745793. 4.952745793
tr3 tr1. -0.280542184. -0.280542184
tr3 tr2
tr3 tr3

is this variance values referring to the genetic correlation (variance due to additive genetic effects) among traits?
How come there's negative values and values >1

If this is not the genetic correlation. Then how should I proceed to get the genetic correlation for these traits?

Thanks
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tshalev
Posted: Wed Dec 05, 2018 10:20 pm Reply with quote
Joined: 03 Mar 2017 Posts: 5
If you use corh() you will only get one correlation, as you assume that all traits are equally correlated. If you want a genetic correlation between each pair of traits, you need to use the corgh() structure.
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MaoHuang
Posted: Mon Dec 10, 2018 4:06 pm Reply with quote
Joined: 19 Nov 2018 Posts: 3
Hi there tshalev, Thank you for your reply.
Before fitting this simpler version of model with corh(),
I did try using the cough()
But it gave me the below error message:

Nonpositive definite G matrix: 0 singularities, 1 negative pivots; order 6



Do you know what may cause this error?
Note: Our G matrix was already positive definite, so not sure why it gives this error.
something else may be wrong?

Thanks again.
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tshalev
Posted: Tue Dec 11, 2018 5:25 pm Reply with quote
Joined: 03 Mar 2017 Posts: 5
In this case, it would seem that the correlation matrix is non-positive definite. Since your model is already quite simple, you could run a univariate model for each trait and then try to use the genetic variance component as your initial starting values in the multivariate model. Note that the message you get is a warning and not an error, so the model is running. You should check whether it converged; if it did, you can still use the output.
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MaoHuang
Posted: Tue Dec 11, 2018 5:36 pm Reply with quote
Joined: 19 Nov 2018 Posts: 3
Thanks tshalev,
I did get some output using this corgh() in the model that produced warnings
summary(modelGBLUP)$varcomp

gamma component
giv(Genot):trait!trait.trt2:!trait.trt1.cor -0.01321706 -0.01321706
giv(Genot):trait!trait.trt3:!trait.trt1.cor 0.63034235 0.63034235

1) So these cor values then should be the genetic correlation among traits I'm looking at?

2) When I further tried obtaining the estimated BV for individual lines with:
predGBLUP<-predict(modelGBLUP,classify="Genot")$predictions$pvals

Same Warning message showed up:
Abnormal termination
Nonpositive definite G matrix: 0 singularities, 1 negative pivots; order 6
Results may be erroneous

Then, the predicted.values were all 0s. So somehow why it gives the varcomp but not the EBVs?

Thanks again,
Mao
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tshalev
Posted: Thu Dec 13, 2018 7:29 pm Reply with quote
Joined: 03 Mar 2017 Posts: 5
Don't use predict to get breeding values. The breeding values are found in
Code:
summary(modelGBLUP, all = T)$coef.random
, along with the standard errors and z-values. You will be looking for the coeffcients that begin with giv(ID).
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