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HYPHY Package >> HyPhy feedback >> Switching from PAML
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Message started by Andrew_Roth on May 29th, 2007 at 7:38pm

Title: Switching from PAML
Post by Andrew_Roth on May 29th, 2007 at 7:38pm
I've been doing some positive selection analysis with PAML and I am finding it is not scaling well as I add more species. I have been using the branch models in PAML but it seems to slow down to a crawl with larger data sets (50+ species, 600+ codons).

I am wondering how well HYPHY does with larger data sets, I am using a Intel core duo which PAML can't really take full advantage of. Are there any articles comparing the two programs running similar models? I am curious to find out if HYPHY and PAML return the same results when running the same models. I would also like to know how well HYPHY does when using computers with more cores and when using clusters.

Thanks in advance.

Title: Re: Switching from PAML
Post by Sergei on May 29th, 2007 at 7:53pm
Dear Andrew,

Firstly, I would encourage you to look over the book chapter on selection using HyPhy that we recently wrote (Multimedia File Viewing and Clickable Links are available for Registered Members only!!  You need to Login Login) to see what HyPhy does and how it is similar/different from PAML. HyPhy includes a couple of analyses which could run exactly the same models as PAML, but also a much larger set of tools which is methodologically different from PAML (this is also discussed in the chapter). We also have an online server for some of the selection analyses at Multimedia File Viewing and Clickable Links are available for Registered Members only!!  You need to Login Login. A long time ago I verified that when the same models are used (e.g. M8), HyPhy and PAML do return the same results (within a few decimal places anyway).

Some of the analyses are designed to be very fast (e.g. SLAC), and some are rather intensive (e.g. those which use genetic algorithms).

HyPhy is multithreaded and will try to take advantage of all available cores in an SMP system. On sufficiently large codon datasets I am able to load all 8 cores in my dual-quad Mac system. HyPhy can also take advantage of an MPI cluster for a large number of analyses - especially those which do the same task repeatedly (simulations or site-by-site fitting would be good examples).

HTH,
Sergei

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