A representative Performance Assessment of Maximum Likelihood based Phylogenetic Inference Tools

Abstract:
      Abstract
      
        Summary
        The evaluation of phylogenetic inference tools is commonly conducted on simulated and empirical sequence data alignments. An open question is how representative these alignments are with respect to those, commonly analyzed by users. Based upon the RAxMLGrove database, it is now possible to simulate DNA sequences based on more than 70, 000 representative RAxML and RAxML-NG tree inferences on empirical datasets conducted on the RAxML web servers. This allows to assess the phylogenetic tree inference accuracy of various inference tools based on realistic and representative simulated DNA alignments. We simulated 20, 000 MSAs based on representative datasets (in terms of signal strength) from RAxMLGrove, and used 5, 000 datasets from the TreeBASE database, to assess the inference accuracy of FastTree2, IQ-TREE2, and RAxML-NG. We find that on quantifiably difficult-to-analyze MSAs all of the analysed tools perform poorly, such that the quicker FastTree2, can constitute a viable alternative to infer trees. We also find, that there are substantial differences between accuracy results on simulated and empirical data, despite the fact that a substantial effort was undertaken to simulate sequences under as realistic as possible settings.
      
      
        Contact
        
          Dimitri Höhler,
          dimitri.hoehler@h-its.org

Citation: biorxiv;2022.10.31.514545v1,[Preprint]

Date Published: 1st Nov 2022

Registered Mode: by DOI

Citation
Höhler, D., Haag, J., Kozlov, A. M., & Stamatakis, A. (2022). A representative Performance Assessment of Maximum Likelihood based Phylogenetic Inference Tools. In []. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2022.10.31.514545
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Created: 2nd Jan 2024 at 18:00

Last updated: 5th Mar 2024 at 21:25

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