, ML tree search #6, logLikelihood: -9974.666906 [00:00:26] ML tree search #7, ML tree search #16

, This example illustrates why it is so important to use multiple starting trees: we can see that some searches ended up in a local optimum with a substantially lower likelihood (?9980.607281 vs. ?9974.669997). Once again, let us check if the resulting trees differ topologically: REFERENCES, vol.1, p.23

-. Raxml and . Ng, That is, in our case, an estimate given by the --parse command should be multiplied by 8. Second, correct thread allocation (one thread per CPU core) is crucial for achieving the optimal performance. Hence, we recommend to check thread allocation, for instance, by running htop after your initial script submission. NOTE: RAxML-NG v. 1.0 and later provides "built-in" coarse-grained parallelization

L. References-czech, J. Huerta-cepas, and A. Stamatakis, A critical review on the use of support values in tree viewers and bioinformatics toolkits, Molecular Biology and Evolution, vol.34, issue.6, pp.1535-1542, 2017.

D. Darriba, D. Posada, A. M. Kozlov, A. Stamatakis, B. Morel et al., ModelTest-NG: A New and Scalable Tool for the Selection of DNA and Protein Evolutionary Models, Molecular Biology and Evolution, vol.37, issue.1, pp.291-294, 2020.

D. A. Duchene, K. J. Tong, C. S. Foster, S. Duchene, R. Lanfear et al., Linking branch lengths across loci provides the best fit for phylogenetic inference, 2018.

M. Hoff, S. Orf, B. Riehm, D. Darriba, and A. Stamatakis, Does the choice of nucleotide substitution models matter topologically?, BMC Bioinformatics, vol.17, issue.1, p.143, 2016.

D. H. Huson and C. Scornavacca, Dendroscope 3: An Interactive Tool for Rooted Phylogenetic Trees and Networks, Systematic Biology, issue.6, pp.1061-1067, 2012.
URL : https://hal.archives-ouvertes.fr/hal-02154987

E. D. Jarvis, S. Mirarab, A. J. Aberer, B. Li, P. Houde et al., Whole-genome analyses resolve early branches in the tree of life of modern birds, Science, vol.346, issue.6215, pp.1320-1331, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02046801

S. Kalyaanamoorthy, B. Q. Minh, T. K. Wong, A. Von-haeseler, and L. S. Jermiin, Modelfinder: fast model selection for accurate phylogenetic estimates, Nature methods, vol.14, issue.6, p.587, 2017.

A. M. Kozlov, A. J. Aberer, and A. Stamatakis, ExaML version 3: a tool for phylogenomic analyses on supercomputers, Bioinformatics, vol.31, issue.15, pp.2577-2579, 2015.

A. M. Kozlov, D. Darriba, T. Flouri, B. Morel, and A. Stamatakis, RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference, Bioinformatics, vol.35, issue.21, pp.4453-4455, 2019.

O. Kozlov, Models, Optimizations, and Tools for Large-Scale Phylogenetic Inference, Handling Sequence Uncertainty, and Taxonomic Validation, 2018.

R. Lanfear, P. B. Frandsen, A. M. Wright, T. Senfeld, and B. Calcott, Partitionfinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses, Molecular Biology and Evolution, vol.34, issue.3, pp.772-773, 2016.

F. Lemoine, J. B. Domelevo-entfellner, E. Wilkinson, D. Correia, M. Dávila-felipe et al., Renewing Felsenstein's phylogenetic bootstrap in the era of big data, Nature, vol.556, issue.7702, pp.452-456, 2018.
URL : https://hal.archives-ouvertes.fr/lirmm-02078445

B. Misof, S. Liu, K. Meusemann, R. S. Peters, A. Donath et al., Phylogenomics resolves the timing and pattern of insect evolution, Science, vol.346, issue.6210, pp.763-767, 2014.

B. Morel, A. M. Kozlov, and A. Stamatakis, ParGenes: a tool for massively parallel model selection and phylogenetic tree inference on thousands of genes, Bioinformatics, vol.35, issue.10, pp.1771-1773, 2019.

L. Nguyen, IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies, Molecular Biology and Evolution, vol.32, issue.1, pp.268-274, 2015.

N. D. Pattengale, M. Alipour, O. R. Bininda-emonds, B. M. Moret, and A. Stamatakis, How many bootstrap replicates are necessary, Journal of Computational Biology, vol.17, issue.3, pp.337-354, 2010.

D. Posada and T. R. Buckley, Model selection and model averaging in phylogenetics: Advantages of akaike information criterion and bayesian approaches over likelihood ratio tests, Systematic Biology, vol.53, issue.5, pp.793-808, 2004.

A. Rambaut, Figtree v1. 4. molecular evolution, phylogenetics and epidemiology, 2012.

D. Robinson and L. Foulds, Comparison of phylogenetic trees, Mathematical Biosciences, vol.53, issue.1, pp.131-147, 1981.

H. Shimodaira and M. Hasegawa, Consel: for assessing the confidence of phylogenetic tree selection, Bioinformatics, vol.17, issue.12, pp.1246-1247, 2001.

A. Stamatakis, Phylogenetic Models of Rate Heterogeneity: A High Performance Computing Perspective, Proc. of IPDPS2006, HICOMB Workshop, Proceedings on CD, 2006.

A. Stamatakis, RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models, Bioinformatics, vol.22, issue.21, pp.2688-2690, 2006.

A. Stamatakis, RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies, Bioinformatics, vol.30, issue.9, pp.1312-1313, 2014.

A. Stamatakis and A. Aberer, Novel parallelization schemes for large-scale likelihoodbased phylogenetic inference, Parallel Distributed Processing (IPDPS), pp.1195-1204, 2013.

A. Stamatakis and A. M. Kozlov, Efficient maximum likelihood tree building methods, Phylogenetics in the Genomic Era, 2020.
URL : https://hal.archives-ouvertes.fr/hal-02535285

Z. Yang, A space-time process model for the evolution of DNA sequences, Genetics, vol.139, issue.2, pp.993-1005, 1995.

A. B. Yoo, M. A. Jette, and M. Grondona, Slurm: Simple linux utility for resource management, Workshop on Job Scheduling Strategies for Parallel Processing, pp.44-60, 2003.