Evaluating Fast Maximum Likelihood-Based Phylogenetic Programs Using Empirical Phylogenomic Data Sets
By Xiaofan Zhou, Xing‐Xing Shen, C. T. Hittinger, Antonis Rokas. 2017
165 citations recorded by the source corpus.
Phylogenetics has witnessed dramatic increases in the sizes of data matrices assembled to resolve branches of the tree of life, motivating the development of programs for fast, yet accurate, inference. For example, several different fast programs have been developed in the very popular maximum likelihood framework, including RAxML/ExaML, PhyML, IQ-TREE, and FastTree. Although these four programs are widely used, a systematic evaluation and comparison of their performance using empirical genome-scale data matrices has so far been lacking. To address this question, we evaluated these four programs on 19 empirical phylogenomic data sets from diverse animal, plant, and fungal lineages with respect to likelihood maximization, tree topology, and computational speed. For single-gene tree inference, we found that the more exhaustive and slower strategies (ten searches per alignment) outperformed faster strategies (one tree search per alignment) using RAxML, PhyML, or IQ-TREE. Interestingly, single-gene trees inferred by the three programs yielded comparable coalescent-based species tree estimations. For concatenation–based species tree inference, IQ-TREE consistently achieved the best-observed likelihoods for all data sets, and RAxML/ExaML was a close second. In contrast, PhyML often failed to complete concatenation-based analyses, whereas FastTree was the fastest but generated lower likelihood values and more dissimilar tree topologies in both types of analyses. Finally, data matrix properties, such as the number of taxa and the strength of phylogenetic signal, sometimes substantially influenced the relative performance of the programs. Our results provide real-world gene and species tree phylogenetic inference benchmarks to inform the design and execution of large-scale phylogenomic data analyses.
Subfields: Genetics, Molecular Biology, Paleontology
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Citations in the corpus
- PhyloSuite: An integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies (2019, methodology): “…via a simple click of a button (section 5.10.1 in Appendix S2). iq ‐ tree was designed primarily for large data and phylogenomic inference (Nguyen et al., 2015), it outperforms other maximum likelihood‐based phylogenetic pro‐ grams for this type of data (Zhou, Shen, Hittinger, & Rokas, 2018).”
- Using PhyloSuite for molecular phylogeny and tree‐based analyses (2023, methodology): “In a comparative study of several popular maximum likelihood ‐ based software programs for phylogenetic reconstruction, including RAxML/ExaML, PhyML, IQ ‐ TREE, and FastTree, IQ ‐ TREE showed the highest likelihoods for concatenation ‐ based species tree inference [51].”