Hi,
Have a look at the function makeNodeLabel with the option method = "md5sum": it
will create a label to each node depending on the tips descending from it. You
can then use them to match nodes and edges of different trees.
Best,
Emmanuel
-Original Message-
From: Jingchun Li
Sender:
Hi Matthew,
You could try phylolm() in my R package phylolm which uses a linear time
algorithm:
http://cran.r-project.org/web/packages/phylolm/index.html
Another option is the function fitContinuous() in geiger package:
http://cran.r-project.org/web/packages/geiger/index.html
Lam.
On Mon, Nov
If the trees are indeed identical, you can just go through the matrix
matching nodes in the two trees (matrix M, here) and find out the order
of the edges in B with respect to A.
Try this:
library(phytools) # uses phytools
n<-length(A$tip.label)
## matrix matching tip & internal nodes
M<-rbind
Thanks Liam. Unfortunately for now, the second tree is read in separately
because it is generated from a different software. So the nodes numbers do
not match. But I get the general idea. I'll have to think more about it.
Cheers,
Jingchun
On Mon, Nov 11, 2013 at 6:02 PM, Liam J. Revell wrote:
Hi Jingchun.
The function ladderize in ape does not change the node numbers of the
tree in phy$edge, only the order of the edges in the matrix. To verify
this, you can use the phytools function matchNodes which matches nodes
between two trees. Note that if a tree that is ladderized using
ladd
Dear all,
I am trying to make a tree figure and I can not figure out the right way to
do it.
I have two trees, A and B. They have the same set of taxa but are in
different orders. A is in the default order when read by read.tree(). B is
ladderized. For my purpose, I want to plot A and label edges
Hi Matthew-
Rob Freckleton had a short paper last year demonstrating the calculations for
PGLS (using Felsenstein's 1973 algorithm) without the need for numerically
challenging (perhaps impossible in this case) matrix inversion for a dataset of
this size.
http://onlinelibrary.wiley.com/doi/1
Dear all,
I am attempting to run a PGLS in R (please see code below) where I am
accounting for phylogenetic affinity (via taxonomy) to the class level and then
testing for the potential relationship between 3 basic ecological axes (habitat
tiering, motility level, and feeding mode) on body size
This definitely looks like something. Thanks, Matt!
Cheers,
Luiz
2013/11/11 Matt Pennell
> Hi Luiz,
>
>
> Yes, non-random sampling of traits, if not taken into account will
> certainly bias the estimation of the transition parameters. Methods for
> addressing this have been developed by Rich
Hi Luiz,
Yes, non-random sampling of traits, if not taken into account will
certainly bias the estimation of the transition parameters. Methods for
addressing this have been developed by Rich FitzJohn and colleagues
http://sysbio.oxfordjournals.org/content/58/6/595.short (this was discussed
in th
Dear all,
Suppose you have observed K discrete traits for a phylogeny with N tips.
For some reason, you think your trait sampling is not random, i.e., it may
be biased towards some particular K's, for example because they're easier
to sample.
I imagine this will introduce some bias in the estima
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