Hi Justin,

The only way to establish these values for a particular size/divergence data set is to perform simulations under these conditions.

With short alignments there will be two issues:

1). Lack of statistical power to detect selection: for example if 5% of 50 codons are under selection, then the method is very unlikely to find it based on the evolution of ~2.5 codons, where as 5% of
1000 codons is a lot more manageable.

2). Numerical issues: the standard BSR model with 3 rates per branch is going to be overparameterized for short alignments. This is generally not a problem, statistically, because you simply won't have the information to estimate those parameters accurately, but the likelihood ratio tests will not be significant. However, the optimization algorithms can fail to converge if an overly complex model is fitted to a small dataset. This could manifest as false positives, for example (if the alternative model is mis-estimated). BSR has some built-in checks for that type of behavior, however.

What types of strange results are you seeing?

Sergei

Here's a BSR tree from the neighboring non-recombinant fragment of about 500bp for comparison...

Thanks for your time and help!

J

Here's the alignment...

I used the NJ trees produced in DataMonkey when running BSR.

I appreciate you taking the time to look into this...

Justin