Hello, have you ever used a parallelized version of clustalw? I see that the most famous one is Clustal-MPI, but it does not seem to be updated.
Thanks for your help
Hello, have you ever used a parallelized version of clustalw? I see that the most famous one is Clustal-MPI, but it does not seem to be updated.
Thanks for your help
Hi there,
ClustalW-MPI! is the right thing to use if you're interested in using something that's based on ClustalW-1.8, which has been in use (but not under development) for ages.
ClustalW-2 is pretty much just a C++-reimplementation (mainly to make the GUI portable) with the addition of some minor features and some bug-fixes. I don't think anyone has implemented a parallel version of this, but there's not much point in this because of the similarity to version 1.8.
And just to add to this: Clustal-Omega is completely new and at least the pairwise alignment stage is fully parallellized.
Andreas
If you are going to use Clustal at all, go with Omega. It is substantially better than ClustalW. I would also caution using ClustalW if you have enough sequences that parallelization is something you need. In the group I did my PhD in we never used ClustalW for alignments as its quality was quite poor for our purposes, and there were much better and faster alternatives out there. Muscle, Mafft, etc are all much better options. But I have seen benchmarking results for Clustal-Omega and it looks like it performs much better and has comparable/better results compared to Muscle and Mafft.
Absolutely. As always, the suitability of a tool for a given application depends on the application - for example, if you were interested in phylogenetic analysis of your dataset, then PRANK or BaliPhy could also be worth looking at, for HUGE datasets, I'd indeed try out Clustal-Omega
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Clustal Omega is parallel and fastest among clustal group of program since it is using profile HMM.
Another big part of why clustal omega is so fast (and it really is astoundingly fast) are tricks it uses to build the guide tree extremely quickly