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Review methods for dN and dS on trees (Read 10255 times)
Sergei
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Datamonkeys are forever...

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Re: Review methods for dN and dS on trees
Reply #15 - Sep 17th, 2006 at 1:45pm
 
Dear Sarah,

One of the nodes on our cluster seems to have developed hardware problems - thus the hung jobs. I restarted the queue just now, having taken the problem node out of the pool; we'll see how that goes.

You can indeed increase the number of categories when running the analysis locally, and also tighten the convergence criterion (e.g. not 30 generations with no c-AIC improvement, but 50 or 100).

Using a consistent tree would be a good idea, because lineage specific analyses could be influenced quite a bit by the changes in the topology. I could take a look at the specific outputs which generate different results and see if anything else stands out; it's a bit difficult to speak in generalities and be helpful here:)


Cheers,
Sergei
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Sarah
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Re: Review methods for dN and dS on trees
Reply #16 - Nov 13th, 2006 at 10:07am
 
Quote:
It's probably a reasonable approximation to estimate the nucleotide biases using a nucleotide mode (NucModelCompare) rather than the codon model (CodonModelCompare), which will be much faster. I'd be interested to hear if they came up with different answers for the best fitting nucleotide model.

Just wanted to say that CodonModelCompare found three good, statistically indistinguishable models, and NucModelCompare (after two months on two processors) settled on the most likely of those three.

Sarah
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Sergei
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Re: Review methods for dN and dS on trees
Reply #17 - Nov 13th, 2006 at 10:16am
 
Dear Sarah,

Two months? Wow! Did you use the branch length approximation heuristic? It speeds things up by a factor of 50x or so, and almost always gets the same results.

Cheers,
Sergei

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Sarah
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Re: Review methods for dN and dS on trees
Reply #18 - Nov 13th, 2006 at 11:33am
 
My mistake--it was a single processor (Athlon XP2000+ I think). I used the branch length approximation.

I'd love to read that chapter.

Sarah
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