Account Options

  1. Sign in
The old Google Groups will be going away soon, but your browser is incompatible with the new version.
Google Groups Home
« Groups Home
Higher posterior probabilities with an incorrect substitution model?
There are currently too many topics in this group that display first. To make this topic appear first, remove this option from another topic.
There was an error processing your request. Please try again.
flag
  2 messages - Collapse all  -  Translate all to Translated (View all originals)
The group you are posting to is a Usenet group. Messages posted to this group will make your email address visible to anyone on the Internet.
Your reply message has not been sent.
Your post was successful
 
From:
To:
Cc:
Followup To:
Add Cc | Add Followup-to | Edit Subject
Subject:
Validation:
For verification purposes please type the characters you see in the picture below or the numbers you hear by clicking the accessibility icon. Listen and type the numbers you hear
 
Rutger Wilschut  
View profile  
 More options Jun 20 2012, 4:11 am
From: Rutger Wilschut <rutgerwilsc...@gmail.com>
Date: Wed, 20 Jun 2012 01:11:52 -0700 (PDT)
Local: Wed, Jun 20 2012 4:11 am
Subject: Higher posterior probabilities with an incorrect substitution model?
Hello everybody,

When running jmodeltest on my chloroplast dataset of the genus
Mosannona the substitution model GTR+G is predicted to be the best
fitting model. Accidently, I performed BEAST analyses with a GTR model
without gamma. These analyses remarkably show a significantly higher
support value (0.91 instead of 0.74) for one of the basal nodes of
interest compared to the same analyses with a GTR+G model.

Jmodeltest gives a –lnL of 11.314,459 for GTR+G and 11.362,524 for
GTR.

My question is whether it is more likely that the analyses with the
GTR model find an incorrectly high support value or that jmodeltest
fails in finding the model best describing the data.

Has anyone had a similar experience in BEAST?  Comments are welcome!

Kind regards,

Rutger


 
You must Sign in before you can post messages.
To post a message you must first join this group.
Please update your nickname on the subscription settings page before posting.
You do not have the permission required to post.
Alexei Drummond  
View profile  
 More options Jun 20 2012, 4:42 am
From: Alexei Drummond <alexei.drumm...@gmail.com>
Date: Wed, 20 Jun 2012 01:42:30 -0700 (PDT)
Local: Wed, Jun 20 2012 4:42 am
Subject: Re: Higher posterior probabilities with an incorrect substitution model?

Dear Rutger,

This is not unexpected. Models with less parameters generally admit less
uncertainty and so if you use a simpler model within a set of nested models
(e.g. GTR instead of GTR+G) then you will be often obtain estimates that
have less uncertainty associated with them. If you had tried Jukes-Cantor
you would probably have gotten even higher posterior probabilities for the
clades in the majority consensus tree. The posterior probabilities reported
in each analysis are conditional on the model being correct. So the
tradeoff is that you may get higher support for the clades estimated by
less parameter-rich models, but the clades estimated are more likely to be
wrong if the simpler model is further from the true evolutionary process.
You will often be trading accuracy for precision.

In your case if you have the same topology then this may not be a problem,
but you should also consider that the estimate of the divergence times are
also conditional on the model chosen. The best approach would be to
actually admit that the you don't know what model to use and average over
the substitution model space as well. Without that option in BEAST 1, a
formal model selection approach like Jmodeltest is a much better idea than
choosing the model that gives you the highest posterior probabilities for
the clades.

Cheers
Alexei


 
You must Sign in before you can post messages.
To post a message you must first join this group.
Please update your nickname on the subscription settings page before posting.
You do not have the permission required to post.
End of messages
« Back to Discussions « Newer topic     Older topic »