PhyML 3.0 Benchmarks

Medium-size data sets

Comparison of PhyML 3.0 tree search options and RAxML, using 100 DNA and protein alignments extracted from Treebase.

See DNA benchmark - See protein benchmark - Download DNA medium-size data sets - Download protein medium-size data sets

Medium-size data sets

Distribution of relative computing times: for each of the 2 sets of alignments (50 DNA and 50 protein medium-size alignments) 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; e.g. with DNA alignments PhyML 2.4.5 NNI is basically twice faster than PhyML 3.0 NNI, but both are pretty much the same with protein alignments.

DNAAv. LogLk rankDelta>5P-value<0.05Av. RF distance
PhyML 3.0 NNI5.183350.28
PhyML 3.0 SPR2.78200.15
PhyML 3.0 BEST2.7200.15
PhyML 3.0 RAND1.64000.03

PROTEINAv. LogLk rankDelta>5P-value<0.05Av. RF distance
PhyML 3.0 NNI4.332010.24
PhyML 3.0 SPR3.24500.14
PhyML 3.0 BEST3.16400.14
PhyML 3.0 RAND2.35000.03

Comparison of log-likelihoods on 50 DNA and 50 protein medium-size data sets. 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 drops 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). The ‘Av. RF distance’ values are the average Robinson and Foulds topological distances between the trees estimated by the method of interest and the corresponding most likely trees (0 corresponds to identical trees, while 1 means that the two trees do not have any clade in common).

Data sets

The benchmark contains 50 protein alignments and 50 DNA alignments.


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 have only considered effective computing times for the CPU.


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).


Resulting trees are compared regarding topology, log-likelihood and computing time.