Apologies if this is a stupid question, I’m just trying to sanity check my understanding of how character state transformation weights are used.
When carrying out sequence alignments, the more common character state transformations (e.g., transitions) would be given more weight because, being more common, they are the changes you would expect to happen during evolution.
When carrying out a phylogenetic inference, the more common character state transformations (e.g., transitions) would be given a lower weighting because, being common, they are more likely to contain noise and are less likely to represent significant evolutionary adaptations.
Have I got the logic correct or wrong? I can’t say I’ve ever seen explicit documentation about how inference programs actually use their weight matrices.
Thanks in advance.