[R-sig-ME] MCMCglmm: square root of the sampling variance of additive genetic variance
Simona Kralj Fiser
@imon@kf @ending from zrc-@@zu@@i
Wed Nov 7 13:05:28 CET 2018
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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