Mailund on the Internet

Just saw this paper in Bioinformatics today:

PopABC: A program to infer historical demographics parameters

Lopes, Balding and Beaumont

Abstract

Summary: PopABC is a computer package for inferring the pattern of demographic divergence of closely related populations and species. The software performs coalescent simulation in the framework of approximate Bayesian computation (ABC). PopABC can also be used to perform Bayesian model choice to discriminate between different demographic scenarios. The program can be used either for research or for education and teaching purposes.

Availability and Implementation: Source code and binaries are freely available at http://www.reading.ac.uk/~sar05sal/software.htm. The program was implemented in C and can run on UNIX, MacOSX and Windows operating systems.

The paper is just an application note, so it doesn’t tell you much about the method, but the documentation on the software page is pretty good, so you can learn more from it there.

The problem addressed is the same as we address with our coalHMM approach: figuring out population genetic parameters in ancestral species and dating the speciation events.

While our approach is based on hidden Markov models and analysing entire genome alignments, theirs is based on ABC and analyses a set of loci assumed to be independent (free recombination between them so no LD).  In that way it is similar to the MCMC methods in IM and MIMAR.

Using sampling methods is probably necessary to analyse many sequences (many, in this case, means something like 5 and above), but I am not sure exactly how well the method scales to long sequences and many loci.  I did play around with the tool a bit, but I haven’t figured out the input file format well enough to simulate my own data for it, so I have only used the toy examples distributed with the software.

One other thing I haven’t figured out yet is if this model allows recombination within loci.  MIMAR does, IM does not, but I couldn’t find anything in the documentation for popABC about it.

If it doesn’t, that is possibly a bit of a weakness.  Assuming free recombination between loci and no inter-locus recombination just doesn’t feel right.  Also, with the simulations and calculations I did for our own model, I was really surprised by how short segments that share a MRCA really are in ancestral species if Ne is reasonably large and the coalescent/recombination process is close to equilibrium at the time of the speciation event, so I guess (but don’t really know for sure) that this could put some constraints on the species you could model while ignoring inter-locus recombination.

For something like Drosophila, with pretty large Ne (compared to, say, apes, but small compared to bacteria) I estimated expected fragment lenghts of shared MRCA between erecta and yakuba in the 20-50 range.  With something like that, you cannot pick loci of any reasonable length and assume no recombination with them.

Anyway, I will definitely look more at this approach.

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Lopes, J., Balding, D., & Beaumont, M. (2009). PopABC: a program to infer historical demographic parameters Bioinformatics DOI: 10.1093/bioinformatics/btp487
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There’s a nice piece in the current issue of American Scientist on the problems of real numbers in computer arithmetic: The Higher Arithmetic.

If you have ever declared a float, but not taken any classes on nummerical analysis and such, you probably should go read it.

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Hattip Revolution.

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I wanted to post this yesterday, but after returning from BiRC’s retreat to Mols Bjerge I was really too tired to blog…

Anyway, yesterday was H.C. Ørsted’s birthday, as was also celebrated by Google’s doodle.  H.C. Ørsted (1777-1851) is one of the greatest Danish scientists, and the discoverer of elctromagnetism (back in 1820) and the term “gedankenexperiment“.

He is celebrated in Denmark by having several roads named after him.

As Danish scientists goes, Niels Bohr is probably better known, and he is celebrated by being on our 500DKK notes, but these days it is Ørsted you should be celebrating.

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