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Updated: Sep 7, 2025

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

NetRAX: accurate and fast maximum likelihood phylogenetic network inference.

Sarah Lutteropp¹, Céline Scornavacca², Alexey M Kozlov¹

¹Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies, Heidelberg 69118, Germany.

Bioinformatics (Oxford, England)

|June 17, 2022

Summary

NetRAX efficiently infers phylogenetic networks using maximum likelihood, overcoming computational limits of current methods. This tool enables rapid analysis of complex evolutionary histories, even for large datasets without incomplete lineage sorting (ILS).

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Area of Science:

Computational Biology
Evolutionary Biology
Bioinformatics

Background:

Phylogenetic networks model complex evolutionary histories beyond simple tree structures.
Current phylogenetic network inference methods struggle with computational complexity, limiting their application to small datasets.
Incomplete lineage sorting (ILS) is a major factor in evolutionary divergence, but its inclusion in network inference significantly increases computational demands.

Purpose of the Study:

To develop a computationally efficient tool for inferring phylogenetic networks.
To enable maximum likelihood (ML) inference of phylogenetic networks, specifically in scenarios excluding incomplete lineage sorting (ILS).
To provide a user-friendly tool for analyzing complex evolutionary relationships in biological data.

Main Methods:

Leveraging state-of-the-art methods for efficient phylogenetic likelihood computation on trees.
Extending tree-based likelihood methods to phylogenetic networks using the concept of 'displayed trees'.
Implementing the NetRAX tool for inferring ML phylogenetic networks from partitioned multiple sequence alignments.

Main Results:

NetRAX demonstrates high accuracy on simulated data, with low Bayesian Information Criterion (BIC) score differences and minimal unrooted softwired cluster distance to true networks.
The tool achieves rapid inference times, completing analysis on large datasets (e.g., 8000 sites, 30 taxa, 3 reticulations) in minutes on standard hardware.
Inferred networks are output in the widely compatible Extended Newick format.

Conclusions:

NetRAX offers a significant advancement in phylogenetic network inference, providing a fast and accurate solution for datasets without ILS.
The tool's efficiency and accuracy make it suitable for analyzing complex evolutionary scenarios previously intractable due to computational constraints.
NetRAX facilitates a deeper understanding of evolutionary processes by enabling the analysis of non-treelike evolutionary histories.