Thanks Brian,
I think I might have to look into that idea.
Whilst picante::Kcalc() is speedy for 12 taxon trees, it's a little slow
for the tree & data I actually want to test which has 11,449 tips (a pruned
version of Hinchliffe & Smith, 2014 [1]). It takes nearly 3 hours to
calculate a single K
One thing you could do is take all nonoverlapping pairs of taxa
(Felsenstein's other technique in the contrasts paper): that is, for a tree
(A,(B,(C,(D,E, you can look at D-E and B-C, *or* D-E and A-B, *or* D-E
and A-C, *or* A-B and C-D, etc. (so, still leaving out one taxon each time,
but only
So I tried a 12-taxon fully pectinate tree with Blomberg's K as calculated
by picante::Kcalc()
library(picante)
library(ape)
aa<-"(A,(B,(C,(D,(E,(F,(G,(H,(I,(J,(K,L)));"
t1<-read.tree(text=aa)
t4 <- compute.brlen(t1,method="Grafen",1)
tipvals <- c(0,1,0,1,0,1,0,1,0,1,0,1)
Kcalc(tipvals,t4)
Thanks Dave,
I'll try Blomberg's K with small simulated fully-bifurcating trees of
simple shape (e.g. fully pectinate), where I can easily paint the tips
myself in what I believe to be a "maximally stratified manner" e.g.
010101010 to see if Blomberg's K does actually reach minimum (i.e. 0.0
?
Ross,
An interesting question. I understand it as that you want to test if
the trait is overdispersed relative to phylogeny, which still makes me
think that measures of 'phylogenetic signal' might be still be useful,
even though the typical interpretation is 'signal' as 'heritability'.
I would try
Hi all,
I'm interested in the distribution of a non-heritable binary
trait/observation across a large tree 1000+ tip tree. The tree is
non-distinct in shape and balance, it is neither fully pectinate nor fully
balanced. It has many soft polytomies too.
I believe the distribution of this trait to
