Open xflouris opened 9 years ago
could we think of some sort of adaptation of the TC/IC (see http://mbe.oxfordjournals.org/content/31/5/1261) metrics to delimitations?
I know that the bipartitions don't change, but it would be interesting to somehow compare the support for being a single species above the current node with the support below or so, I don't know if it is feasible, just a thought.
alexis
On 23.11.2015 23:38, Tomas Flouri wrote:
Compute an average support/confidence score for the ML tree after a bayesian run.
1.
Method: Sum up the support values for each node of the bayesian tree * if the corresponding node of the ML tree is within the speciation process add the support value to the sum. * if the corresponding node of the ML tree is within a coalescent process then add 1 minus the support value to the sum. * leaf nodes or roots of subtrees that contain only edges smaller than the minimum branch length are ignored from the computation.
2.
Compute the average
— Reply to this email directly or view it on GitHub https://github.com/Pas-Kapli/delimitation/issues/55.
Alexandros (Alexis) Stamatakis
Research Group Leader, Heidelberg Institute for Theoretical Studies Full Professor, Dept. of Informatics, Karlsruhe Institute of Technology Adjunct Professor, Dept. of Ecology and Evolutionary Biology, University of Arizona at Tucson
www.exelixis-lab.org
finished ticket.
@stamatak : I'll have to read the TC/IC paper as I'm not familiar with it. But we have exactly the kind of statistic you mention already implemented. The support values from a bayesian run state how many times a node was in the speciation process (in a probability format, i.e. 0 never and 1 always). To compute how many times a clade was a single species (or equivalently, how many times a node was a coalescent root) we only need to subtract the support value of the node from the support value of its parent.
Compute an average support/confidence score for the ML tree after a bayesian run.