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TraitLab is a software package for simulating, fitting and analysingtree-like binary data under a stochastic Dollo model of evolution. The modelalso allows for rate heterogeneity through catastrophes, evolutionary eventswhere many traits are simultaneously lost while new ones arise, and borrowing,whereby traits transfer laterally between species as well as through ancestralrelationships. The core of the package is a Markov chain Monte Carlo (MCMC)sampling algorithm that enables the user to sample from the Bayesian jointposterior distribution for tree topologies, clade and root ages, and the traitloss, catastrophe and borrowing rates for a given data set. Data can besimulated according to the fitted Dollo model or according to a number ofgeneralized models that allow for heterogeneity in the trait loss rate, biasesin the data collection process and borrowing of traits between lineages.Coupled pairs of Markov chains can be used to diagnose MCMC mixing andconvergence and to debias MCMC estimators. The raw data, MCMC run output, andmodel fit can be inspected using a number of useful graphical and analyticaltools provided within the package or imported into other popular analysisprograms. TraitLab is freely available and runs within the Matlab computingenvironment with its Statistics and Machine Learning toolbox, no otheradditional toolboxes are required.

TraitLab: a Matlab package for fitting and simulating binary tree-like data