The Molecular Ecologist: ABC, quick as A-B-C

If I said you had a nice posterior Reverend Bayes, would you take offense? Photo via WikiMedia Commons.

Over at The Molecular Ecologist, new contributor Peter Fields—a Ph.D. student studying plant-pathogen coevolution at the University of Virginia—writes about approximate Bayesian computation and a new approach to this still-developing method of statistical inference that can make it quite a bit faster.

ABC functions upon the rationale that the likelihood might be approximated through the use of simulation and simulation summary statistics2, and that the evaluation of model fit to a dataset can be identified through a comparison of Ss derived from simulated scenarios and calculation of those same summaries on an observed, empirical dataset. In theory, simulation summaries are selected to provide maximal distinction amongst competing models. In practice, identifying these summaries isn’t always easy, and is the object of continued research3

For an introduction to ABC, and a description of the new approach, go read the whole thing.◼

Running for marriage equality

Regular readers will be well aware that two of my principle extracurricular activities are running and volunteering on the campaign against an anti-gay-marriage amendment to the Minnesota state constitution. Now, with the election drawing closer, I’m going to combine the two, and run in support of marriage equality.

There is, of course, a long and storied history of homosexuals running for truth, justice, and the (North) American way, as the Kids in the Hall remind us.

This faggot will be running in not one but two events before the election: the 5k Big Gay Race on Saturday, 29 September; and then the Mankato Marathon on Sunday, 21 October. (That’ll be my fifth marathon!) I propose that you, my dozens of readers, commemorate these efforts and help keep bigotry out of Minnesota’s constitution by contributing to Minnesotans United for All Families, the campaign against the amendment.

I suggest you donate $5 ($1/kilometer) to sponsor the 5k; or either $26.21 ($1/mile) or $42.19 ($1/kilometer) to sponsor the marathon. I’ll even add an extra inducement: anyone who donates at least $5 and lets me know via e-mail will go into a drawing to recieve a free D&T tee shirt of his or her choice.

Ready? Set? Go donate.◼

Postscript: For meditation on the appropriateness of the use of the word “faggot” in this context, please direct your attention/questions/objections to Scott Thompson and Lexicon Valley, in that order.

Science online, organic marmots edition

Fresh Organic Strawberries Organic strawberries. Photo by VancityAllie.

The Molecular Ecologist: Isolating isolation by distance

Linanthus parryae population Linanthus parryae. Photo by naomi_bot.

And now I present my first “real” post as a contributor at the Molecular Ecologist, a discussion of a new review article pointing out that population geneticists aren’t doing a great job dealing with one of the best-known patterns in population genetics, isolation by distance, or IBD. You may recall that I discussed IBD in a more historical context way back in the day on this very website. It’s simply a pattern in which populations located close to each other are more genetically similar than populations farther away from each other, which arises because most critters (or their seeds, or larvae, or pollen) are less likely to move longer distances. But IBD can be conflated with a number of other patterns population geneticists often try to detect:

So let’s say you’ve collected genetic data from sites on either side of a line you think might be biologically significant—a pretty standard-issue population genetics study. You run your data through Structure, and find two clusters of collection sites that line up pretty well with that Line of Hypothesized Biological Significance. As a followup, you conduct an AMOVA with the collection sites grouped according to their placement by Structure, and you find that the clusters explain a significant fraction of the total genetic variation in your data set. Therefore, you conclude that the LHBS is, in fact, a significant barrier to dispersal.

Except that as we’ve just discussed, everything you’ve just found could be a consequence of simple IBD plus the fact that you’ve structured your sampling so that your LHBS happens to bisect the landscape you’re studying. And just to add to the frustration, even if you’d started out by testing for IBD before you started with all of the tests for population structure, a significant result in a Mantel test for IBD wouldn’t necessarily mean that population structure wasn’t there.

To find out how the author of the new review article suggests we deal with the complications outlined above, go read the whole thing.◼

Big, bloggy news

Starting today, I’m officially part of the crew at the Molecular Ecologist, the group blog associated with the journal Molecular Ecology, as both a contributor and a sort of coordinator/administrator.

Molecular Ecology‘s managing editor Tim Vines first approached me about joining the site back at Evolution 2012, and I’m excited to start talking about the many wonderful uses of molecular genetic data with Holly Bik, Mark Christie, Nick Crawford, and Peter Fields. We’re hoping to bring in lots of guest posters as well. (And if you’re interested, send me an e-mail.) Although the Molecular Ecologist is affiliated with Molecular Ecology, the vision of the site is not to promote the journal itself, but to build a space for the community of scientists interested in the journal’s subject matter. As part of that effort, we’ve launched a Molecular Ecologist page on Facebook, and I’m taking over @molecologist on Twitter.

This doesn’t mean I’ll stop posting at Nothing in Biology Makes Sense!, much less here at D&T; the Molecular Ecologist is aimed at a somewhat different audience than either of my other online locales, and while this may spread me a little thinner, I expect I’ll be covering different topics at each site.◼