Hi, I want to build a phylogenetic tree of ITS2 & 28S r DNA gene partial sequence of trematode parasite by distance and character based method (such as Neighbor-joining (NJ), Maximum likelihood, Maximum parsimony or, UPGMA methods).Out of four methods which would be the best to represent each group (means distance and character ).
ML for all! possibly with a bayesian PP addition.
previous "how to" here:
https://www.researchgate.net/post/How_do_you_align_DNA_sequences_for_phylogenetic_work_What_is_the_order_of_events_and_what_software_do_you_use?_tpcectx=profile_answers
regards
I am using Mega 5.2 for both MSA & Phylogenetic analysis. Please clarify .
Off course ML; and also do bayesian posterior probability analysis. These two methods are being used widely these days. All others are kind of out dated now.
Regarding MEGA, it can be used for preliminary analysis of your data, just to check what patterns you see. But the trees are not at all publishable, most journals will never accept it.
There are advanced softwares for better analysis of your sequence data. Many of them are freely available, almost all of them, except for PAUP, thats the only one I know which is a paid one. There is PAUP and WINCLADA which are parsimony based, WINCLADA is faster than PAUP. Then there is RAxML and GARLI, both likelihood based and both of which give good results and are being used currently.
Mr. Bayes, BEAST, *BEAST they all run on Bayesian framework. BEAST and *BEAST are used for dating the bayesian tree using a suitable calibration point relevant to your study.
You should definitely use a model-based approach, i.e. Maximum Likelihood or preferentially Bayesian. As mentioned by others, distance methods (NJ, UPGMA) and parsimony are outdated because they fail to take into account all the available prior knowledge about the data. Note that before analysis you will need to decide on the most appropriate nucleotide substitution model to use (many softwares can do this).
Get in touch with Virginia Leon-Regagnon [email protected] for some advice based on a lot of experience with digeneans.
Definitely Maximum Likelihood is a good choice. I used that for tapeworm phylogeny. You can use Modeltest to look for the best model for your dataset and use the phylip/phyml software (free) to construct your tree.
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