Difference between revisions of "Tips For Codon Matrices"
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Latest revision as of 23:43, 1 January 2017
Codon matrices in xrate
(See also known issues with DART)
When using XRATE to estimate large rate matrices (e.g. 61*61 codon matrices), the following tips are recommended:
 Decrease the mininc parameter. This commandline parameter determines the minimum fractional increase in loglikelihood that is required for EM to continue. For models with lots of parameters, small changes in the loglikelihood can represent substantial changes in the lesserused parameters. You may therefore want to set mininc to a lower value than its default. For example
xrate mininc .00001 [...other arguments...]
 Increase the forgive parameter. This commandline parameter sets the number of "bad" iterations of EM that will be forgiven (these are iterations where the likelihood decreases, instead of increasing; this should never happen in practice  the likelihood should keep asymptotically increasing  but due to precision error, it can occasionally happen in practice, especially with these big rate matrices. I usually set "forgive 2" for codon matrices, which means that at worst xrate will do 2 unnecessary iterations of EM)
 Start from a uniform (flat) seed. In other words, all the initial rates and probabilities for the model should be the same. Additionally they should be underestimates (i.e. start with rates a bit lower than the eventual values you anticipate). These both help convergence and reduce the chances of the EM algorithm getting stuck in a local maximum.
 Ian Holmes  30 Apr 2010