Dear babblers, in the past I followed the “total evidence” approach quite doubtlessly, especially when only DNA regions of one genome type (cp, n, mt) were involed. I merely checked if the (good supported) backbone nodes in all trees from individual markers agreed. They mostly did, so I didn’t bother any further and created the supermatrix with respective partitioning.
My question is: Is there any standard procedure or common practice I missed, to decide on a quantitative basis if one is allowed to combine the data sets?
I found hints to a couple of tools that should provide such tests [e.g. concaterpillar - couldn’t make it run with recent RAxML and is only for amino acid data(?); arn - a package from Farris (yes, THE Farris), which I couldn’t locate], but none of them seemed to be working for me.
I then calculated Robinson Foulds distances between the individual trees and the tree from the supermatrix, but I am unsure what distance value should be considered as a threshold (if this is at all a good way to go for my aim).
Please let me know if you have hints in this respect, especially some automizable thing (in R?) would be nice.