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GARD results and identical sequences (Read 2990 times)
tlefebure
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GARD results and identical sequences
Apr 30th, 2007 at 8:41am
 
Hello!

I usually run GARD on a local cluster to detect genome wide intragenic recombination. In the process I don't collapse identical sequences.

The other day someone in my lab did run a GARD analysis on datamonkey on a single gene that I had already analysed. Some sequences were identical, and so, probably to save computation time, datamonkey collapse the data to unique haplotypes (21 to 8 taxa). The "surprise" is that the results are not the same:
- with some duplicates, no recombination detected (c-AIC : 1284.35)
- with unique haplotypes, 1 breakpoint (c-AIC : 1219.91)


Well, I just don't know ho to interprate this, and which one we should believe. Any idea?


Thanks,

-Tristan
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Sergei
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Datamonkeys are forever...

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Re: GARD results and identical sequences
Reply #1 - Apr 30th, 2007 at 11:16am
 
Dear Tristan,

Not collapsing the sequences will have an effect on the substitution model (via base freqs and rate estimates). My guess is that c-AIC improvement for 1bp is small compared to no bp - hence the result is marginal. Am I correct?

Cheers,
Sergei
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Division of Infectious Diseases
Division of Biomedical Informatics
School of Medicine
University of California San Diego
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tlefebure
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Re: GARD results and identical sequences
Reply #2 - Apr 30th, 2007 at 12:38pm
 
The delta c-AIC is 1.18956
The model parameters vary, but only slightly.

I'm not used to play with AIC improvement values, would you in that (and other cases) look at it before taking any decision? Do you use some sort of rule of thumb as with the Bayes factors?

-Tristan
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Sergei
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Re: GARD results and identical sequences
Reply #3 - Apr 30th, 2007 at 5:09pm
 
Dear Tristan,

You can use evidence ratios (exp(delta aic / 2)) as a form of a Bayes Factor; something on the order of 100 (or delta of about 10) would make me comfortable.

Cheers,
Sergei
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Associate Professor
Division of Infectious Diseases
Division of Biomedical Informatics
School of Medicine
University of California San Diego
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