Hi Tom.
This was the subject of discussion recently on this list. ace does not
do marginal ancestral state reconstruction (which is probably what you
want) - it computes the conditional scaled likelihoods of the subtree.
These are the same as the marginal reconstructions only at the root
node. If your transition matrix is symmetric, then you can get the
marginal reconstructions by rerooting at all the internal nodes. This is
in the phytools function rerootingMethod
(http://www.phytools.org/static.help/rerootingMethod.html). If you want
to use a more complicated model, you will have to use another package -
such as diversitree.
An alternative is to use stochastic mapping and then compute the
posterior frequencies from the sample of stochastic maps. This makes it
easy to put an explicit prior on the root and to integrate over
uncertainty in the transition matrix. This is implemented in phytools
also (http://www.phytools.org/static.help/make.simmap.html).
All the best, Liam
Liam J. Revell, Assistant Professor of Biology
University of Massachusetts Boston
web: http://faculty.umb.edu/liam.revell/
email: liam.rev...@umb.edu
blog: http://blog.phytools.org
On 7/29/2013 5:45 PM, Tom Wenseleers wrote:
Dear all,
@Arne: yes I think it has to do something with the priors for the root.
I’m not sure what prior ace uses – I think equal, which in my case would
not be so appropriate given that nearly all species have the trait.Would
anyone know by any chance whether in ape it is possible to haveace use a
prior for the root which would reflect the frequency at the tips, and if
so, how one could specify this?
Cheers,
Tom
*From:*Arne Mooers [mailto:amoo...@sfu.ca]
*Sent:* 29 July 2013 20:10
*To:* Tom Wenseleers
*Subject:* Question on ace ML reconstruction of discrete binary character
Hoi Tom,
What is the default prior on the root in ace? Different approaches use
different priors (=observed frequency at tips, equal, equal to tested
ratio of q's, etc.) That has had a big affect on reconstructions I have
done in the past.
Cheers,
Arne Mooers
Begin forwarded message:
*From: *Tom Wenseleers <tom.wensele...@bio.kuleuven.be
<mailto:tom.wensele...@bio.kuleuven.be>>
*Date: *29 July, 2013 9:00:28 AM PDT
*To: *"r-sig-phylo@r-project.org <mailto:r-sig-phylo@r-project.org>"
<r-sig-phylo@r-project.org <mailto:r-sig-phylo@r-project.org>>
*Subject: [R-sig-phylo] Question on ace ML reconstruction of discrete
binary character*
Dear all,
I just did some ancestral state reconstructions of binary characters
(screenshot attached) using ace (using an equal rate discrete character
reconstruction) . Everything seems to make sense to me, except the two
basal nodes, where I end up with quite low likelihoods for my red
character being 1 (cf. the pie charts), even though I get higher
likelihoods at practically all of the more shallow nodes in the tree.
Any ideas why one can get a result like this, and what I could
potentially do about it, since it doesn’t seem quite right to me?
Cheers,
Tom
/_______________________________________________________________________________________/
/Prof. Tom Wenseleers/
*/ Lab. of Socioecology and Social Evolution/
/ Dept. of Biology/
/ Zoological Institute/
/ K.U.Leuven/
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/(/+32 (0)16 32 39 64 / +32 (0)472 40 45 96/
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*/http://bio.kuleuven.be/ento/wenseleers/twenseleers.htm/*
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