Efficient sampling of transpositions and inverted transpositions for Bayesian MCMC

István Miklós, Timothy Brooks Paige, Péter Ligeti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The evolutionary distance between two organisms can be determined by comparing the order of appearance of orthologous genes in their genomes. Above the numerous parsimony approaches that try to obtain the shortest sequence of rearrangement operations sorting one genome into the other, Bayesian Markov chain Monte Carlo methods have been introduced a few years ago. The computational time for convergence in the Markov chain is the product of the number of needed steps in the Markov chain and the computational time needed to perform one MCMC step. Therefore faster methods for making one MCMC step can reduce the mixing time of an MCMC in terms of computer running time. We introduce two efficient algorithms for characterizing and sampling transpositions and inverted transpositions for Bayesian MCMC. The first algorithm characterizes the transpositions and inverted transpositions by the number of breakpoints the mutations change in the breakpoint graph, the second algorithm characterizes the mutations by the change in the number of cycles. Both algorithms run in O(n) time, where n is the size of the genome. This is a significant improvement compared with the so far available brute force method with O(n3) running time and memory usage.

Original languageEnglish
Title of host publicationAlgorithms in Bioinformatics - 6th International Workshop, WABI 2006, Proceedings
PublisherSpringer Verlag
Pages174-185
Number of pages12
ISBN (Print)3540395830, 9783540395836
DOIs
Publication statusPublished - Jan 1 2006
Event6th International Workshop on Algorithms in Bioinformatics, WABI 2006 - Zurich, Switzerland
Duration: Sep 11 2006Sep 13 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4175 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Workshop on Algorithms in Bioinformatics, WABI 2006
CountrySwitzerland
CityZurich
Period9/11/069/13/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Miklós, I., Paige, T. B., & Ligeti, P. (2006). Efficient sampling of transpositions and inverted transpositions for Bayesian MCMC. In Algorithms in Bioinformatics - 6th International Workshop, WABI 2006, Proceedings (pp. 174-185). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4175 LNBI). Springer Verlag. https://doi.org/10.1007/11851561_17