computeLRF module

pylabeledrf.computeLRF.computeELRF(intree1, intree2)

Function to estimate the edge-based labeled Robinson-Foulds distance. This is a heuristic which returns an upper bound on the distance.

Trees need to have their inner nodes with a label attribute “speciation” or “duplication”. To correctly process gene trees from Ensembl, use the parseEnsemblLabels().

Parameters:
  • intree1 – a labeled tree as Dendropy object
  • intree2 – a labeled tree as Dendropy object
pylabeledrf.computeLRF.computeLRF(intree1, intree2)

Function to compute exactly the Labeled Robinson-Foulds (LRF) distance.

Trees need to have their inner nodes with a label attribute “speciation” or “duplication”. To correctly process gene trees from Ensembl, use the parseEnsemblLabels().

Parameters:
  • intree1 – a labeled tree as Dendropy object
  • intree2 – a labeled tree as Dendropy object
pylabeledrf.computeLRF.mutateLabeledTree(tree, n, p_flip=0.3, model='LRF')

Function to perform random edits to labeled tree. For each n edit, the probability of a flip is specified by p_flip, and the rest of the probability density is evenly split among all potential edges to flip and all nodes with degree >3. Returns a new tree (leaves the input tree unchanged)

Parameters:
  • tree – a labeled tree as Dendropy object
  • n – number of edits
  • p_flip – probability of flipping between “duplication” and “speciation” state (0.3 by default)
  • model – either ELRF, which requires edge additions/removals to be between same types, or LRF (default), which has no such requirement.
pylabeledrf.computeLRF.parseEnsemblLabels(intree)

Function to convert a Dendropy tree obtained from Ensembl (in NHX) format. Returns a new tree (leaves the input tree unchanged)

Parameters:intree – a tree as Dendropy object
pylabeledrf.computeLRF.randomLabels(intree, p_speciation=0.7)

Function to assign random speciation and duplication nodes to a tree. Returns a new tree (leaves the input tree unchanged)

Parameters:
  • intree – a tree as Dendropy object
  • p_speciation – probability of a speciation node.