MCMCglmm: square root of the sampling variance of additive genetic variance

Hi.
I used MCMCglmm to calculate the heritability of a trait [Va/(Va+Vr)]; e.g.:

prior<-list(G=list(G1=list(V=matrix(p.var*0.5),n=1)),R=list(V=matrix(p.var*0.5),n=1)

model <- MCMCglmm(trait~ 1, random = ~animal, pedigree = pedigree,data =
data, nitt = 5000000, thin = 100, burnin = 150000, prior = prior, verbose =
FALSE)

summary(model)

Iterations = 150001:4999901

 Thinning interval  = 100

 Sample size  = 48500



 DIC: 2032.226



 G-structure:  ~animal



       post.mean l-95% CI u-95% CI eff.samp

animal     78.48    38.18    120.3    48500



 R-structure:  ~units



      post.mean l-95% CI u-95% CI eff.samp

units     84.11     59.5    109.2    48500



 Location effects: trait~ 1



            post.mean l-95% CI u-95% CI eff.samp  pMCMC

(Intercept)     6.918    4.589    9.091    48500 <2e-05 ***

HPDinterval(model$VCV)

lower    upper

animal 38.18195 120.3350

units  59.50312 109.1574

attr(,"Probability")

[1] 0.95

herit <- model$VCV[, "animal"]/(model$VCV[, "animal"] + model$VCV[,

"units"])

mean(herit)

[1] 0.4772017

HPDinterval(herit, 0.95)

lower     upper

var1 0.2940021 0.6576105

attr(,"Probability")

[1] 0.95


I have two questions:

1. I am trying to call the standard errors for additive and residual
variance


se(model$VCV[, "animal"]) does not work


I used

sd(model$VCV[, "animal"])

[1] 21.36365

sd(model$VCV[, "units"])

[1] 12.8011



I wonder whether the SD (of Va) provides the square root of the sampling
variance of Va. Could you please confirm this? I am interested in
calculating the SE of Va to calculate the SEs of other statistics (e.g.,
CVa).

2. Also, is there a way to plot the posterior distribution of the
heritability (or Va) estimates?

Thank you!

Simona

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