Frequently Asked Questions

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发布时间:2025-07-10 13:34

How do I run BEAST without data to sample the Prior?

In BEAUti, on the MCMC tab, click the checkbox 'Sample from prior only - create empty alignment', save the XML and run with BEAST. Alternatively, in the XML file, remove (or comments out) the entries in the <likelihood> block.

How do I tell BEAST to use an outgroup?

The simple answer is that you may not want to - BEAST will sample the root position along with the rest of the nodes in the tree. If you then calculate the proportion of trees that have a particular root, you obtain a posterior probability for this root position. However if you have a strong prior for an outgroup then you can constrain the ingroup to be monophyletic.

Which non-parametric demographic model should I use to analyse a single gene?

A description of the coalescent tree priors (or demographic priors) can be found here. There are essentially three different non-parametric demographic priors available: the Bayesian Skyline, the (GMRF) Bayesian Skyride and the Bayesian Skygrid. Basically, we suggest using Skyride over Skyline as it is a straightforward development of the Skyline with fewer user specified options.

The question of Skygrid vs Skyride is more complex. Skyride, like the original Skyline, scales its demographic curve to the height/age of the tree, with the changes in population sizes being concordant with the nodes in the tree. That is, as the tree grows and shrinks over the course of the MCMC, the Skyride timescale does too. Skygrid on the other hand requires you to define a fixed time line and grid points where the population size changes. The tree scales within this grid (i.e., the grid doesn't change even though the tree does). This is useful when you know what the timeline of the process is. Skygrid allow allows multi-locus analysis but this is probably not useful for viruses (unless they are independent epidemics being controlled by the same process). Finally, Skygrid allows covariates of the population dynamics to be incorporated and tested.

Does it matter what order the Priors & Likelihoods come in the XML?

Yes. BEAST will evaluate each component in order starting with the priors. If any of these are zero, then the rest of the posterior is not calculated. Thus it is particularly important that constraints, like <booleanLikelihood> and <uniformPrior> which may give zero probabilities, are put at the beginning of the <prior> section: <mcmc chainLength="1000000" autoOptimize="true"> <posterior> <prior> <uniformPrior lower="90.0" upper="100.0"> <parameter idref="rootHeight"/> </uniformPrior> <coalescentLikelihood idref="coalescent"/> </prior> <likelihood> <treeLikelihood idref="treeLikelihood"/> </likelihood> </posterior>