The program for this years meeting is now available, complete with a heat map illustrating how keywords are distributed among concurrent sessions (see image). Because I have an 8AM slot I'd like to use this opportunity to pre-emptively accept the apologies of everyone who's going to tell me they missed my talk because they slept in.
I regret to report that one of the world's most spectacular adaptive radiations is no match for man's best friend. I had a lovely pink columbine in full bloom until my dog Eddie decided he was ready to begin his own career as a gardener. As beautiful and effective as those nectar spurs may be, they're no match for jaws. Perhaps we can get Justen Whittall to model the type of spur that might be required for specialization to a canine pollinator?
It's Friday afternoon, so I thought a little parasite distraction might be in order. Over at Mental Floss, there's a nice list of eight different parasites that affect their hosts' behavior, in order to promote their transmission: zombie snails, crabs, caterpillars, grasshoppers, fish, ants, and cockroaches. Good creepy stuff for cocktail party or coffee shop evolutionary chit-chat for sure! The last sentence is a question about whether or not there are parasites that affect human behavior. Clearly these folks need to read up on Toxoplasma!
This October 2nd-4th, the Museum of Comparative Zoology at Harvard University will host the 2009 Anolis symposium. It's been over ten years since anole biologists gathered at Penn State, so there should be plenty to discuss. Registration is only $20 and slots for presenters are still available. The recently completed genome of Anolis carolinensis which will be the subject of a satellite meeting taking place at the Broad Institute of MIT and Harvard on October 5th. Worried you don't know enough about anoles to enjoy a conference like this? Just pick up a copy of Losos's new book and you'll be an expert before you know it (it's 20% off if you order prior to it's July 9th release)! Photo credit: Anolis fowleri by Luke Mahler.
Earlier this morning I gave the final exam for my course "The Tree of Life." Click the image to the right if you'd like to try your luck with the first page of my exam!
For this (unauthorized) installment of When we fail MrBayes , I’d like to step back and look at how we assess convergence in the first place. I’ve encountered a few datasets now for which convergence problems would be very difficult to diagnose without tools like AWTY . I’ve found two diagnostics in AWTY to be especially useful. First, the slide command shows the posterior probabilities of clades for non-overlapping samples of trees in the sample: basically, a sliding-window of posterior probabilities. If a coarse scale of analysis shows posterior probabilities that vary widely during the course of a single run, this is strong evidence that runs have not converged. I am also a big fan of the compare command, which plots pairwise split frequencies for a series of independent MCMC runs. As a friend asked yesterday, why aren’t more folks using AWTY to assess convergence? As far as I am aware, this is the only general diagnostic tool out there that is geared towards assessing convergence of topologies, rather than convergence of molecular evolutionary parameters. As such it, is explicitly addressing the one set of parameters that are (usually) of greatest interest to systematists: the tree itself.
With this in mind, I conducted an informal survey of convergence diagnostics in the literature. I looked at all articles published in two recent issues of Molecular Phylogenetics and Evolution using Bayesian inference (mostly MrBayes, but a few using BEAST) and tabulated the convergence diagnostics used. MPE seems like it should be a reasonable gauge of methods currently used by practicing systematists, although it would not surprise me if papers in some journals (Systematic Biology?) use convergence assessment that is, on average, more rigorous. Anyway, in 25 studies:
3 studies reported only that they “examined stationarity of LnL values” or something to this effect. I hesitate to say that this is the worst possible test of convergence, because 5 studies reported no test of convergence whatsoever and another tested for convergence by ‘discarding burn-in’. I think most readers of this blog would agree that these are generally not adequate.
The most frequent class involved some variation of analyzing multiple runs (11 studies); this includes checking the standard deviation of split frequencies for independent runs (6 studies) and comparing posterior probabilities for independent runs (2 studies). I think this is a good general strategy, but the majority of these considered only 2 independent runs. This is not good. Let’s imagine that treespace for your dataset contains two (rather different) topologies of high and equal probability. At convergence, your MCMC sampler should visit both of these topologies in proportion to their posterior probability (say, ~47% of the time for each, as no other topologies are nearly as good).
A major problem arises if it takes many generations to move between these topologies. Even for a highly-optimized MCMC sampler, it does not surprise me at all that it might take many millions of generations to move between “distant” regions of treespace, particularly for large datasets. If this is true, two runs is far from adequate, because there is a 50% chance that two independent runs will find the same high-probability topology first, and – if not run for a sufficient number of generations – it will appear as though the runs have converged, based on both similarity of posterior probabilities, standard dev of split frequencies, etc. This is something of a worst-case scenario, because – as I’ve described it – certain clades would appear to have ~1.00 posterior probability, when in fact the true posterior probability might be closer to 0.5. Unfortunately, there appears to be no good way of determining a ‘sufficient’ number of generations a priori, so the only solution here seems to be ‘lots of runs.’
The next most frequent strategy involved checking convergence of molecular evolutionary parameters, either by estimating effective sizes of parameters (6 studies), or by checking the Gelman-Rubin proportional scale reduction factor (1 study). I am skeptical of these approaches, considered alone, because I’ve found that there is often little correspondence between convergence of molecular evolutionary parameters and convergence of topologies. Perhaps this reflects some particularly troublesome datasets that I have worked with, but it does not leave me feeling encouraged. Note that I am not claiming that monitoring these parameters is unimportant, but that it is fundamentally inadequate with respect to our interest in topologies.
Recently, I sat down at a local watering hole with my colleague, Rob Desalle and we talked about cladistics and the changing field of evolutionary biology. Along the way, Western textiles, horror movies, and a couple of colorful expletives came up…and in the end, he told me it was the most serious conversation we’d ever had.
The change in the status of science in the new White House is cause for optimism. Obama became only the fourth president to address the annual meeting of the National Academy of Sciences, where he announced the appointees to the President's Council of Advisors on Science and Technology (PCAST). 
Candace Toner, CEO of Biomatters and Steven Stones-Havas, a developer from Geneious came to the AMNH today and gave us a presentation on some new features of version 4.6 and a sneak preview of version 4.7, to be released soon. Some nifty new features include tools to help better visualize alignments and trees as well as the ability to link via "Green Button" to run things on the New Zealand Supercomputing Center (which, for geeks out there, was the same cluster used to render LOTR). Lots more plug-ins are planned as well. They were also really great about answering questions from our staff and students and took down some suggestions we had for slight improvements. They even bought us all pizza for lunch. Now that's customer service!
