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Lpnet: Reconstructing phylogenetic networks from distances using integer linear programming
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DOI：10.1111/2041-210X.14086.png)
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摘要
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Neighbor-net is a widely used network reconstructing method that approximates pairwise distances between taxa by a circular phylogenetic network. We present Lpnet, a variant of Neighbor-net. We first apply standard methods to construct a binary phylogenetic tree and then use integer linear programming to compute an optimal circular ordering that agrees with all tree splits. This approach achieves an improved approximation of the input distance for the clear majority of experiments that we have run for simulated and real data. We release an implementation in R that can handle up to 94 taxa and usually needs about 1 min on a standard computer for 80 taxa. For larger taxa sets, we include a top-down heuristic which also tends to perform better than Neighbor-net. Our Lpnet provides an alternative to Neighbor-net and performs better in most cases. We anticipate Lpent will be useful to generate phylogenetic hypotheses.
Keyword:
circular split systems
distance-based phylogenetics
integer linear programming
neighbor-net
phylogenetic networks
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