PhyML 3.0 Benchmarks
Simulated data sets
Comparison of PhyML 3.0 tree search options and RAxML, using 100 simulated DNA data sets.
Distribution of relative computing times: for the whole set of alignments (100 simulated DNA data) we measured the base-2 logarithm of the ratio of the computing time of the given method, and that of the fastest approach with the corresponding alignment. Thus, a log-ratio equals to X corresponds to a method being 2^X times slower than the fastest approach.
| Av. LogLk rank | Delta>5 | P-value<0.05 | Av. RF distance | |
| PhyML 2.4.5 | 3.975 | 4 | 0 | 0.102 |
| PhyML 3.0 NNI | 3.59 | 3 | 0 | 0.100 |
| PhyML 3.0 SPR | 3.705 | 0 | 0 | 0.100 |
| PhyML 3.0 BEST | 3.075 | 0 | 0 | 0.097 |
| PhyML 3.0 RAND | 2.8 | 0 | 0 | 0.097 |
| RAxML | 3.855 | 0 | 0 | 0.097 |
Performance of tree searching algorithms on 100 simulated nucleotide alignments. The column ‘Av. LogLk rank’ gives the average log-likelihood ranks for the different methods. These ranks are corrected by taking into account information on tree topologies. ‘Delta>5’ gives the number of cases (among 50) for which the difference of log-likelihood between the method of interest and the highest log-likelihood for the corresponding data set is greater than 5. The column ‘p-value<0.05’ displays the number of cases for which the difference of log-likelihood when comparing the method of interest to the corresponding highest log-likelihood is statistically significant (SH test). Note that in this table the Robinson and Foulds distance measures the topological difference between true and inferred trees (instead of the difference between inferred and most likely trees, as for the other tables).
Data sets
The benchmark contains 100 simulated data sets of 40 sequences and 500 sites. Data sets have been generated by Seq-Gen along random trees, using GTR model,with parameters estimated from HIV data (Posada and Crandall, 2001): nucleotide frequencies fA = 0.40, fC = 0.20, fG = 0.22, fT = 0.18, four rate categories of gamma shape parameter 0.969, and rates of nucleotide changes r(AC) = 1.72, r(AG) = 5.03, r(AT) = 0.84, r(CG) = 0.91, r(CT) = 7.70, r(GT) = 1; (M. Anisimova and O. Gascuel, 2006).Hardware
All programs have been run on a cluster Intel(R) Xeon(R) CPU 5140 @ 2.33GHz, 24 computing nodes, with 8GB of RAM for one bi-dualcore unit. Times can be compared because we've only considered effective computing time for the CPU.Programs
6 programs and options have been compared. All programs were configured with the GTR model for DNA sequences, with WAG for proteins, and with 4 discrete gamma rate categories (alpha estimated from the data).- PhyML_2.4.5
Previous version of PhyML, optimizing the topology with simultaneous NNIs (original PhyML algorithm), and using a BioNJ starting tree. - PhyML 3.0 NNI
PhyML, optimizing the topology with both simultaneous NNIs (as in original PhyML algorithm) and refined NNIs with 5-edge-length optimization, and using a BioNJ starting tree. - PhyML 3.0 SPR
PhyML, optimizing the topology with SPR (and NNI 3.0) operations, and using a BioNJ starting tree. - PhyML 3.0 BEST
PhyML, best tree obtained by PHYML_NNI and PHYML_SPR. - PhyML 3.0 BEST RANDOM
PhyML, adding to the BEST option 5 SPR tree searches using random starting trees, output is the best of the 7 inferred trees. - RAxML
RAxML version 7.0. To obtain comparable results, the tree likelihood has been re-optimized by PhyML, keeping the topology but fitting all numerical parameters.
Results
Resulting trees are compared regarding topology, log-likelihood and computing time.- Computing time ranks
The six methods are ranked for each of the alignments, based on the computing time. First rank contains methods with computing time ranging from the best (B) computing time to 1.25 X B (i.e. nearly best computing time). Remaining methods are ranked in the same way, until all methods are ranked. Ties are accounted for; e.g. if the first and second group contains 2 methods each, the ranks will be 1.5 ( (1+2)/2 ) and 3.5 ( (3+4)/2 ). To summarize these results, we provide the median and average ranks for all alignments. - LogLK ranks
The six methods are ranked for each of the alignments using a similar principle, based on the tree likelihood. Ranks account for ties, just as with log-likelihood values. Moreover, we provide the median and average ranks for all DNA and protein alignments. - Robinson and Foulds distances
RF is the Robinson and Foulds (bipartition) distance between the best topology and the given topology. - Robinson and Foulds ranks
The six methods are ranked for each of the alignments using a similar principle, based on the RF distance with the true tree. First rank contains all methods which find the same best topology. And so on. Moreover, we provide the median and average ranks for all alignments. - Delta>5
Another variable of interest is the number of times a method fails to find a phylogeny which log-likelihood is close to the highest log-likelihood found by any of the methods being compared. We thus counted the number of data sets for which the log-likelihoods returned by a given method was smaller than the highest log-likelihood found on the corresponding alignments minus 5.0. While this boundary of 5.0 points of log-likelihood is arbitrary, we believe that it provides a simple and practical way to tell the methods apart at first sight. - SH tests
We used the Shimoidara-Hasegawa (SH) test to assess the statistical significance of the likelihood differences. Every result displays the P-value between its logLk and the logLk of the best result for the same data. As a summary, we provide the number of times each method is significatively worst than the best one.
Contact: Vincent Lefort, LIRMM.
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