Dataset Information

NetRAX: accurate and fast maximum likelihood phylogenetic network inference.

ABSTRACT:

Motivation

Phylogenetic networks can represent non-treelike evolutionary scenarios. Current, actively developed approaches for phylogenetic network inference jointly account for non-treelike evolution and incomplete lineage sorting (ILS). Unfortunately, this induces a very high computational complexity and current tools can only analyze small datasets.

Results

We present NetRAX, a tool for maximum likelihood (ML) inference of phylogenetic networks in the absence of ILS. Our tool leverages state-of-the-art methods for efficiently computing the phylogenetic likelihood function on trees, and extends them to phylogenetic networks via the notion of 'displayed trees'. NetRAX can infer ML phylogenetic networks from partitioned multiple sequence alignments and returns the inferred networks in Extended Newick format. On simulated data, our results show a very low relative difference in Bayesian Information Criterion (BIC) score and a near-zero unrooted softwired cluster distance to the true, simulated networks. With NetRAX, a network inference on a partitioned alignment with 8000 sites, 30 taxa and 3 reticulations completes within a few minutes on a standard laptop.

Availability and implementation

Our implementation is available under the GNU General Public License v3.0 at https://github.com/lutteropp/NetRAX.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Lutteropp S

PROVIDER: S-EPMC9344847 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

NetRAX: accurate and fast maximum likelihood phylogenetic network inference.

Lutteropp Sarah S Scornavacca Céline C Kozlov Alexey M AM Morel Benoit B Stamatakis Alexandros A

Bioinformatics (Oxford, England) 20220801 15

<h4>Motivation</h4>Phylogenetic networks can represent non-treelike evolutionary scenarios. Current, actively developed approaches for phylogenetic network inference jointly account for non-treelike evolution and incomplete lineage sorting (ILS). Unfortunately, this induces a very high computational complexity and current tools can only analyze small datasets.<h4>Results</h4>We present NetRAX, a tool for maximum likelihood (ML) inference of phylogenetic networks in the absence of ILS. Our tool l ...[more]

PMID: 35713506

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Dataset Information

NetRAX: accurate and fast maximum likelihood phylogenetic network inference.

Motivation

Results

Availability and implementation

Supplementary information

Publications

NetRAX: accurate and fast maximum likelihood phylogenetic network inference.

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