-- Hi R users,
I'm trying to fit an animal model using lme and cannot fit the corelation matrix which describes the additive genetic correlation between individuals.
I have created a test data set (pedigree) where the first column specifies the id of each individual, and the second column contains simulated trait values. AGRM is the corresponding additive genetic relationship matrix whose elements are equal to the genetic correlation between individuals.
The test data is simulated to have a heritibility of 0.8 (i.e. 80% of the variation can be explained by genetic effects)
My initial attempt has been:
CM<-pdSymm(AGRM, ~1|animal) lme(trait~1, data=pedigree, CM)
but which ever combination I use I always get "invalid formula for groups".
Does any one know how to code this sort of model?
Thanks for your help,
Jarrod Hadfield.
copy and paste from here to get the test data (Sorry the correlation matrix is so big)
##############################################################################################
animal<-c("Newbird1","Newbird2","a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z","aa","bb","cc","dd","ee","ff","gg","hh","ii","jj","kk","ll","mm")
trait<-c(-1.10988343,-0.95061690,-1.05596407,-0.20075671,-0.98747062,1.72132706,1.33973268,0.30333354,0.34969961,0.70681745,-0.15210172,-1.05918719,-0.32665059,0.55423824,-0.81324407,-0.61359451,,0.65936390,-0.92295239,0.87285686,1.11508781,1.30904325,0.83437615,,0.72948628,,0.63043694,-0.40078431,,1.20814060,,0.69233357,-1.51568342,-0.16235203,-2.26109886,1.21242313,0.04010594,0.06988673,-0.70644384,-0.69870290,-0.02043294,-0.57957532,-0.78726879,0.20574982,0.27469486,-0.25899545)
pedigree<-data.frame(cbind(animal, trait))
AGRM<-as.matrix(cbind(c(1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0),c(0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5),c(0,0,1,0,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0),c(0,0,0,1,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0),c(0,0,0,0,1,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.25,0.25,0.25,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0,1,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.75,0.75,0.75,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,0.25,0.25,0.25),c(0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5!
, 0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25),c(0,0,0.5,0.5,0,0,0,0,0,0,1,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0),c(0,0,0.5,0.5,0,0,0,0,0,0,0.5,1,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0),c(0,0,0.5,0.5,0,0,0,0,0,0,0.5,0.5,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0),c(0,0,0.5,0.5,0,0,0,0,0,0,0.5,0.5,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,1,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.75,0.75,0.75,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0.5,1,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.5,0.5,0.5,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0.5,0.5,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.5,0.5,0.5,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0.5,0.5,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.5,0.5,0.5,0.5,0.5,0.5,0,0,0),c(0,0,0,0,0,0,0.!
5 ,0.5,0,0,0,0,0,0,0,0,0,0,1,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0.5,1,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0.5,0.5,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),c(0,0,0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,1,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0.25,0.25),c(0,0,0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.5,1,0.5,0.5,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0.25,0.25),c(0,0,0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,1,0.5,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.5,0.5,0.5),c(0,0,0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0.5,1,0,0,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0.25,0.25),c(0.5,0,0.5,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0,0,0,0,1,0.5,0.5,0.125,0.125,0.125,0,0,0,0,0,0,0,0,0),c(0.5,0,0.5,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,!
0 ,0,0,0,0,0.5,1,0.5,0.125,0.125,0.125,0,0,0,0,0,0,0,0,0),c(0.5,0,0.5,0,0,0,0,0,0,0,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,1,0.125,0.125,0.125,0,0,0,0,0,0,0,0,0),c(0,0,0.25,0.25,0.5,0,0,0,0,0,0.25,0.25,0.25,0.5,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0.125,0.125,0.125,1,0.5,0.5,0.125,0.125,0.125,0.125,0.125,0.125,0,0,0),c(0,0,0.25,0.25,0.5,0,0,0,0,0,0.25,0.25,0.25,0.5,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0.125,0.125,0.125,0.5,1,0.5,0.125,0.125,0.125,0.125,0.125,0.125,0,0,0),c(0,0,0.25,0.25,0.5,0,0,0,0,0,0.25,0.25,0.25,0.5,0.25,0.25,0.25,0.25,0,0,0,0,0,0,0,0,0.125,0.125,0.125,0.5,0.5,1,0.125,0.125,0.125,0.125,0.125,0.125,0,0,0),c(0,0,0,0,0.25,0.75,0,0,0,0,0,0,0,0,0.75,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0.125,0.125,0.125,1.25,0.75,0.75,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0.25,0.75,0,0,0,0,0,0,0,0,0.75,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0.125,0.125,0.125,0.75,1.25,0.75,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0.25,0.75,0,0,0,0,0,0,0,0,0.75,0.5,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0.125,0.125,0!
. 125,0.75,0.75,1.25,0.25,0.25,0.25,0,0,0),c(0,0,0,0,0.25,0.25,0,0,0.5,0,0,0,0,0,0.25,0.25,0.25,0.5,0,0,0,0,0.25,0.25,0.25,0.25,0,0,0,0.125,0.125,0.125,0.25,0.25,0.25,1,0.5,0.5,0.125,0.125,0.125),c(0,0,0,0,0.25,0.25,0,0,0.5,0,0,0,0,0,0.25,0.25,0.25,0.5,0,0,0,0,0.25,0.25,0.25,0.25,0,0,0,0.125,0.125,0.125,0.25,0.25,0.25,0.5,1,0.5,0.125,0.125,0.125),c(0,0,0,0,0.25,0.25,0,0,0.5,0,0,0,0,0,0.25,0.25,0.25,0.5,0,0,0,0,0.25,0.25,0.25,0.25,0,0,0,0.125,0.125,0.125,0.25,0.25,0.25,0.5,0.5,1,0.125,0.125,0.125),c(0,0.5,0,0,0,0,0,0,0.25,0.25,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.5,0.25,0,0,0,0,0,0,0,0,0,0.125,0.125,0.125,1,0.5,0.5),c(0,0.5,0,0,0,0,0,0,0.25,0.25,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.5,0.25,0,0,0,0,0,0,0,0,0,0.125,0.125,0.125,0.5,1,0.5),c(0,0.5,0,0,0,0,0,0,0.25,0.25,0,0,0,0,0,0,0,0,0,0,0,0,0.25,0.25,0.5,0.25,0,0,0,0,0,0,0,0,0,0.125,0.125,0.125,0.5,0.5,1)))
colnames(AGRM)<-animal
rownames(AGRM)<-animal
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