If you are concerned with a lack of stationarity in the data, you could try
analysing the data under the LogDet substitution model with an appropriate
proportion of invariable sites removed. The LogDet model is not constrained by
the assumption of reversibility, so should be resistant to any shifts in the
substitution process over the tree. Although it will still be susceptable to
changes in the distribution of sites free to vary.
Hope this helps,
Jean-François Martin wrote:
> In butterfly mtDNA, the composition bias is extreme toward A-T (80 to 90%
> depending on gene and codon position).
> It seems also unlikely that every kind of substitution has equal probability
> to occur.
> Furthermore a selection against substitutions providing G and C, which has
> been demonstrated in Dloop of mammalians (A-T rich), is not correctly
> represented by ML models. At least for what I know about Maximum Likelihood
> and PAUP* options, it is impossible to use a non reversible model. Even if
> it was possible, what kind of weighting sheme could fit to the actual (not
> the observed) substitution pattern?
>> Jean-Francois Martin