Phylogenetic Tools Of Large Data Sets That Use Multicore Processors?

Question

[2184687-1231-83-]

Does anybody know of examples of phylogenetic tools of large data sets that use multicore processors?

I know of RAxML (http://hpseewiki.ipb.ac.rs/index.php/RAxML) but I would like to know of other examples, specially if they haven't been published yet but are released and ready to be tested.

Answer 1

[Botond Sipos]

For Maximum Likelihood inference:

• GARLI supports multiple cores through OpenMP. It also uses a genetic algorithm approach for parameter optimization.
• HYPHY supports multicore and can perform ML tree inference.
• There also seems to be a PhyML fork with OpenMP suport.

For Bayesian MCMC inference:

• MrBayes supports multicore through MPI (Altekar et al.).
• One can use BEAST on many cores by performing independent runs in parallel and combining the output.

[lh3]

+1 Great! Thanks.

[Frédéric Mahé]

With PhyML (compiled with the MPI option), it's the bootstrapping step that be parallelized. I didn't know about that PhyML+m3l fork.

Answer 2

[Jan Kosinski]

I have just stumbled upon a paper comparing RAxML with FastTree.

FastTree is another fast ML method, they say much faster than RAxML and not so much less accurate... And is available as Multi-threaded FastTree with OpenMP

[DG]

I use FastTree and RAxML for pretty much all of my phylogenetic analyses. They are pretty comparable, and the major topology differences between the two tend to occur only at poorly supported nodes anyway. I had to construct a pipeline to do trees on tens of thousands of alignments and FastTreeMP was virtually the only good option.

[ALchEmiXt]

+1 for FastTree as well http://www.microbesonline.org/fasttree/

Answer 3

[Farhat]

There's also POY from AMNH that can be run on clusters.

Answer 4

[Gjain]

I heard R`s phylogenetic package combined with its multicore package works fine. But I never tried it.

Answer 5

[Ahdf-Lell-Kocks]

• Fastcodeml http://wiki.isb-sib.ch/selectome/Selectome_requirements