The Metropolized Partial Importance Sampling MCMC Mixes Slowly on Minimum Reversal Rearrangement Paths

Authors:
Istvan Miklos;Bence Melykuti;Krister Swenson
Affiliations:
Renyi Institute of Mathematical Sciences , Budapest;University of Oxford, Oxford;EPFL, Lausanne
Venue:
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Year:
2010

Citing 16
Cited 1

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Abstract

Markov chain Monte Carlo has been the standard technique for inferring the posterior distribution of genome rearrangement scenarios under a Bayesian approach. We present here a negative result on the rate of convergence of the generally used Markov chains. We prove that the relaxation time of the Markov chains walking on the optimal reversal sorting scenarios might grow exponentially with the size of the signed permutations, namely, with the number of syntheny blocks.