Quantifying MCMC Exploration of Phylogenetic Tree Space
نویسندگان
چکیده
منابع مشابه
Quantifying MCMC Exploration of Phylogenetic Tree Space
In order to gain an understanding of the effectiveness of phylogenetic Markov chain Monte Carlo (MCMC), it is important to understand how quickly the empirical distribution of the MCMC converges to the posterior distribution. In this article, we investigate this problem on phylogenetic tree topologies with a metric that is especially well suited to the task: the subtree prune-and-regraft (SPR) ...
متن کاملTerraces in phylogenetic tree space.
A key step in assembling the tree of life is the construction of species-rich phylogenies from multilocus--but often incomplete--sequence data sets. We describe previously unknown structure in the landscape of solutions to the tree reconstruction problem, comprising sometimes vast "terraces" of trees with identical quality, arranged on islands of phylogenetically similar trees. Phylogenetic amb...
متن کاملTransforming phylogenetic networks: Moving beyond tree space.
Phylogenetic networks are a generalization of phylogenetic trees that are used to represent reticulate evolution. Unrooted phylogenetic networks form a special class of such networks, which naturally generalize unrooted phylogenetic trees. In this paper we define two operations on unrooted phylogenetic networks, one of which is a generalization of the well-known nearest-neighbor interchange (NN...
متن کاملMCMC for State Space Models
In this chapter we look at MCMC methods for a class of time-series models, called statespace models. The idea of state-space models is that there is an unobserved state of interest the evolves through time, and that partial observations of the state are made at successive time-points. We will denote the state by X and observations by Y , and assume that our state space model has the following s...
متن کاملPhylogenetic MCMC algorithms are misleading on mixtures of trees.
Markov chain Monte Carlo (MCMC) algorithms play a critical role in the Bayesian approach to phylogenetic inference. We present a theoretical analysis of the rate of convergence of many of the widely used Markov chains. For N characters generated from a uniform mixture of two trees, we prove that the Markov chains take an exponentially long (in N) number of iterations to converge to the posterio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Systematic Biology
سال: 2015
ISSN: 1076-836X,1063-5157
DOI: 10.1093/sysbio/syv006