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On the inference of complex phylogenetic networks by Markov Chain Monte-Carlo

Fig 6

Example of a phylogenetic network where the level ℓ is equal to 6 (the reticulation nodes are depicted in grey), while , depending on the traversal algorithm (not shown).

A traversal ensuring that remains close to the lower end of this interval (the scanwidth of the network [66]) will be several orders of magnitude faster than algorithms whose complexity depends exponentially on ℓ. Increasing the number of reticulation nodes while keeping a “ladder” topology as above can make ℓ arbitrarily large, while the scanwidth remains constant. This topology may seem odd but it is intended as the backbone of a more complex and realistic network with subtrees hanging from the different internal branches of the ladder, in which case the complexity issue remains.

doi: https://doi.org/10.1371/journal.pcbi.1008380.g006