TOPD/FMTS: a new software to compare phylogenetic trees. A new software to compare phylogenetic trees. The FMTS program can be used to compare. Phylogenetic comparative methods. All organisms are linked together by the tree of life. We can use this tree along with trait data, to understand many aspects of.

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Like, probably don't use MEGA for ML trees. I was at a conference and a professor there didn't like that I was using MEGA to reconstruct ancestral sequences. He was also weird about the fastML program that identifies functionally divergent sites, thinking that an algorithm that performs a faster analysis is somehow suspect. PHYML and raxml are heavily cited programs.

The author of phyml is famous in his field, and, I may be wrong, developed the first program for ML analysis. This is completely untrue. You hope that they give you the same tree so there is no ambiguity, but they often can give you different trees. This establishes doubt on certain nodes. The prior for BI makes all the difference, and I've gotten different trees using both methods. In the case of my research, ML is all but useless, establishing several polytomies, while BI is able to resolve them.

So for my specific research question, if I were to make phylogenetic trees, I'd strictly use BI, which has been the standard in previous publications--although never addressed why in the publications. Cara Install Driver Sound Card. Okay, I'm very curious about this. When you say you've gotten different trees, how comparable were the analyses? Zhypermu Season 4 more. Is it *BEAST versus everything concatenated in RAxML?

Or MrBayes concatenated GTR+I+G versus RAxML concatenated GTR+I+G? The second one is much more troubling than the first, where the models are completely different. Another question, how are the trees being compared?

Is it MAP tree to ML tree? Or is it summary tree to summary tree? If it's summary to summary, how are the computed? Hmm, I see what you mean, like tree optimization where MrBayes uses MCMC. Phylogenetic is just a small adjunct if what I do, so at this point, I should be cautious what I argue.

I simply compared gene families of TreeFinder and MrBayes, then used RAxML when the developer of TreeFinder lost his mind using, and I used the same substitution model. This is where I'm grossly ignorant.

TreeFinder and RAxML produced the same tree, I compared by eye, except when I used LR-ELW, in TreeFinder, where polytomies were resolved. At this point, no longer knowing what I was doing, I admitted defeat and moved on with my actual project. The gene family I'm working on is a mess and resolving it is out of my league with regards to knowing the strengths and weaknesses of the algorithms. Honestly, even just understanding them, such is the case of MCMC. So I admit ignorance at this point.

So maybe you can explain to me why posterior probabilities wouldn't matter in tree topology, besides estimation of node support, which bootstrapping seems to be more conservative? Is there also some reading material that would breakdown this issue for me in a way that's less technical than the publications?

And the issue I'm having is that these paralogs rapidly exploded independently across an infraclass, hence the issue resolving polytomies. I gave up when I had to use LR-ELW for resolution in ML, thinking they might not be real, but artifacts of the algorithms, despite high node support. Given this wasn't fundamental to my project, it was an idea for a third chapter, but I bit off more than I could chew with this and my basal level of knowledge regarding phylogenetic reconstruction.