RAxML-NG

RAxML-NG infers phylogenetic trees from molecular sequence alignments under the maximum likelihood (ML) optimality criterion for evolutionary analyses.

Key Features:

• Maximum likelihood (ML): Infers phylogenetic trees under the ML optimality criterion.
• Greedy tree search algorithm: Re-implements the greedy tree search algorithm originally developed in RAxML/ExaML for heuristic tree optimization.
• NP-hard problem handling: Addresses the NP-hard tree-search problem using heuristic strategies derived from RAxML/ExaML.
• Terrace detection: Detects terraces in tree space to reveal regions of equivalent likelihood and inform robustness of inferred trees.
• Transfer bootstrap support: Computes the transfer bootstrap support metric to assess node support.
• Accuracy on taxon-rich datasets: Typically identifies higher-scoring trees than IQ-TREE on taxon-rich datasets.
• Performance and scalability: Improves speed and scalability for large empirical datasets.
• Flexibility: Supports diverse models and analysis configurations for varied biological datasets.

Scientific Applications:

• Large-scale phylogenetics: Infers trees for large empirical and taxon-rich molecular sequence datasets.
• Evolutionary research: Supports hypothesis testing and reconstruction of evolutionary relationships in fundamental biological research.
• Biotechnology: Applies phylogenetic inference to biotechnology research questions.
• Agriculture: Enables phylogenetic analyses relevant to agricultural studies.
• Medicine: Facilitates phylogenetic investigations applicable to medical research.

Methodology:

Maximum likelihood inference using a re-implementation of the greedy tree search algorithm from RAxML/ExaML, with detection of terraces in tree space and computation of transfer bootstrap support.