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bayesian-inference

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Frames Bayesian phylogenetics as approximating a posterior distribution over trees conditioned on data AND priors via an MCMC that must be proven to have converged, using MrBayes, BEAST2, RevBayes, and PhyloBayes-MPI. Covers why convergence (ESS, PSRF, ASDSF, topology vs scalar) is the load-bearing claim, why posterior probabilities are systematically higher than bootstrap and overconfident under model misspecification, why the default branch-length prior inflates tree length, why the harmonic-mean estimator must never select models (use stepping-stone), and when site-heterogeneous CAT-GTR is required at depth. Use when needing posterior clade support, model averaging, marginal-likelihood model comparison, or CAT models for deep phylogeny. Routes topology-only ML to modern-tree-inference, divergence times to divergence-dating, and tree summarization to tree-io.

When to use

• | Factor | ML (modern-tree-inference) | MrBayes | BEAST2 | RevBayes | PhyloBayes-MPI | |--------|----------------------------|---------|--------|----------|----------------| | Reach for it when | topology, fast, IC model selection, bootstr…

When not to use

• topology-only ML
• bootstrap
• IC model selection
• divergence times
• clock models
• node/tip calibration
• fossilized birth-death
• multispecies-coalescent species trees under ILS

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