Compute average support score for ML tree after bayesiananalysis

[xflouris]

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

[stamatak]

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.

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.

Compute the average

—
Reply to this email directly or view it on GitHub
#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

[xflouris]

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.