I have data (morphological data) that characterizes tumor in different patients and would like to run a phylogenetic analysis on it. What is the most effective and user-friendly program that I can use to analyze this? I want to make a phylogenetic tree out of it too.
I have used Mesquite but I am unsure of which model to use for building a tree. Because of lack of tutorial out there, that is why I am here.
Thanks!
Jason, that's very interesting.
I advice you to use TNT. I also advice you to carfully consider how you code your characters.
http://www.cladistics.com/aboutTNT.html
Maybe you should take a look at Simmap:
http://www.simmap.com/index.html
I recommended to you Simmap, but there is also MEGA which has a simple graphical interface.
http://www.megasoftware.net
Maybe mesquite could do the job too:
https://mesquiteproject.wikispaces.com/home
Yes; please check the TNT download page: http://www.lillo.org.ar/phylogeny/tnt/
I think Mega can handle morphological data (note sure).
http://www.megasoftware.net/tutorial.php
But I know mesquite can.
Dear Jason,
To be honest, I do not see why you would want to use a phylogenetic program for this. Phenetic clustering would seem more appropriate for the type of data, and possibly the type of questions you have. SPSS will provide all you need.
I agree with Marc. I am not sure whether the processes of tumorigenesis are similar to cladogenesis. So it may be not appropriate to apply a phylogenetic analysis in your case. However, you may try UPGMA and PCoA both of which are based on similarity distance of characters.
Dear Jason,
It is not a case of phylogenetic analysis. You should use a cluster analisis like UPGMA or WPGMA. A good program could be PAST, NTSYS, SPSS, R... with Bray-Curtis or Euclidian Distance Index. To work with a siminality matrix, you might use MANOVA or PERMANOVA analysis. I Suggest you PERMANOVA.
You might want to check these refereces out:
http://www.ncbi.nlm.nih.gov/pubmed/?term=tumor+phylogenetics
yes I agree with the multivariate analysis , clustering and principal component analysis
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