Practical Session: Bayesian evolutionary analysis by sampling trees (BEAST) Rebecca R. Gray, Ph.D. Department of Pathology University of Florida

BEAST: – is a cross-platform program for Bayesian MCMC analysis of molecular sequences –entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models –can be used as a method of reconstructing phylogenies, but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology –uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability

Citations The recommended citation for this program is: –Drummond AJ, Rambaut A (2007) "BEAST: Bayesian evolutionary analysis by sampling trees." BMC Evolutionary Biology 7:214 To cite the relaxed clock model in BEAST: –Drummond AJ, Ho SYW, Phillips MJ & Rambaut A (2006) PLoS Biology 4, e88 To cite the Bayesian Skyline model in BEAST: –Drummond AJ, Rambaut A & Shapiro B and Pybus OG (2005) Mol Biol Evol 22, The original MCMC paper was: –Drummond AJ, Nicholls GK, Rodrigo AG & Solomon W (2002) Genetics 161,

Basic Pipeline 1) setting up xml file (beauti) 2) running xml file (beast) 3) evaluating the performance of the run (Tracer) 4) comparing models, obtaining estimates of parameters (Tracer) 5) summarizing the tree distribution (TreeAnnotator) 6) viewing MCC tree (Figtree)

Downloading programs –Download contains beauti, BEAST, TreeAnnotator

PRACTICAL: RIFT VALLEY FEVER VIRUS

Epidemiology of RVF The virus was first identified in 1931 in the Rift Valley of Kenya Mosquito vector, primarily infects livestock 1997–1998, a major outbreak occurred in Kenya, Somalia and the United Republic of Tanzania September 2000 cases were confirmed in Saudi Arabia and Yemen (first reported occurrence of the disease outside the African continent)

Setting up xml file in beauti Requires a nexus file –Helpful to have dates with the sample name –Use the finest resolution available GUI interface allows basic selection of parameters Xml file can be manually edited to test specific hypotheses/tweak run

Beauti practical Import alignment (g_63.nex) Tip dates – use tipdates, guess dates (years since some time in the past) Site models – use GTR + G, empirical base frequencies Test hypothesis of strict vs. relaxed molecular clock Trees – coalescent tree prior – constant size 5 x 10 7 generations

BEAST Open xml file with text editor Run in beast Check mixing of the MCMC chain Open S log files in Tracer Open L and G2 log files What can we do about the trace??

Proper mixing First step – run chain longer –Open L200 files Other steps to try: –Over parameterization – reduce complexity –Temporal/phylogenetic signal –Priors are inappropriate

Model testing Bayes factors: –Compare estimates of the marginal likelihoods of the models of interest –2*(ln marginal likelihood model 1 – ln marginal likelihood model 2) –>10, strong support for alternative (more complex model) Strict clock vs. relaxed clock –Also consider the coefficient of variation

Summarizing tree TreeAnnotator –Burnin 10% (501 samples) –Keep median heights –MCC tree Visualizing tree: FigTree –Posterior probabilities for branches –Median heights for clades of interest

Advanced analyses Different coalescent priors –Parametric models (exponential, logistic) –Bayesian skyline plots Phylogeography –Lemey et al, 2009, Plos Computational Biology Site specific rates of variation

Change in effective population size over time Log10 Ne

16 Bayesian Genealogy Of G Gene 1916 ( )

Additional resources Tutorials on the beast website, google group 16th International BioInformatics Workshop on Virus Evolution and Molecular Epidemiology –Johns Hopkins University, Baltimore –29 August - 03 September 2010, Bethesda, USA –