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Table 2 Computational efficiencies on the OrthoMaM data set for the tested methods

From: Fast and accurate branch lengths estimation for phylogenomic trees

  Concat+Dist Concat+ML SDM*add DistRadd ERaBLEadd SDM* DistR ERaBLE
T 1 ≈0 3 h 20 m/39 h 28 m 2 m 46 s 2 m 46 s 2 m 46 s
T 2 5 m 41 s 41 h 16 m 8 h 2 m 2 h 9 m 7 s 8 h 33 m 2 h 6 m 7 s
M 889 MB 117 GB 1.2 GB 2.8 GB 222 MB 1.2 GB 3.0 GB 221 MB
  1. Note.— The first row gives (T 1) the running time to obtain the data on which subsequent computations are based: the superalignment and the distance-based gene trees for Concat+Dist, the superalignment and ML gene trees for Concat+ML, the ML gene trees and resulting additive distances for the three supertree methods, and the estimated distances for the three medium-level methods. When ML gene trees are used (Concat+ML, SDM*add, DistRadd and ERaBLEadd), two alternative approaches are possible and therefore two running times are provided: first that to infer trees with fixed topology (3 h 20 m), and then that to infer trees where the topology is also estimated (39 h 28 m). The second row gives (T 2) the remaining running time to obtain estimates for branch lengths and gene rates. The third row (M) gives the maximum amount of memory allocated. All the experiments were conducted on a PC with 4 GB RAM and a 2.7 GHz CPU, except branch length estimation (T 2 and M) for Concat+ML, which, because of the large memory requirements, was run on a cluster machine with 200 GB RAM and a 2.66 GHz CPU