A divide-and-conquer method for scalable phylogenetic network inference from multilocus data.

ABSTRACT:

Motivation

Reticulate evolutionary histories, such as those arising in the presence of hybridization, are best modeled as phylogenetic networks. Recently developed methods allow for statistical inference of phylogenetic networks while also accounting for other processes, such as incomplete lineage sorting. However, these methods can only handle a small number of loci from a handful of genomes.

Results

In this article, we introduce a novel two-step method for scalable inference of phylogenetic networks from the sequence alignments of multiple, unlinked loci. The method infers networks on subproblems and then merges them into a network on the full set of taxa. To reduce the number of trinets to infer, we formulate a Hitting Set version of the problem of finding a small number

SUBMITTER: Zhu J 

PROVIDER: S-EPMC6612858 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature