A fast and exact algorithm for the exemplar breakpoint distance

Mingfu Shao, Bernard M.E. Moret

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

1 Scopus citations

Abstract

A fundamental problem in comparative genomics is to compute the distance between two genomes. For two genomes without duplicate genes, we can easily compute a variety of distance measures in linear time, but the problem is NP-hard under most models when genomes contain duplicate genes. Sankoff proposed the use of exemplars to tackle the problem of duplicates genes and gene families: each gene family is represented by a single gene (the exemplar for that family), chosen so as to optimize some metric. Unfortunately, choosing exemplars is itself an NP-hard problem. In this paper, we propose a very fast and exact algorithm to compute the exemplar breakpoint distance, based on new insights in the underlying structure of genome rearrangements and exemplars. We evaluate the performance of our algorithm on simulation data and compare its performance to the best effort to date (a divideand- conquer approach), showing that our algorithm runs much faster and scales much better. We also devise a new algorithm for the generalized breakpoint distance problem, which can then be applied to assign orthologs. We compare our algorithm with the state-of-the-art method MSOAR by assigning orthologs among five well annotated mammalian genomes, showing that our algorithm runs much faster and is slightly more accurate than MSOAR.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 19th Annual International Conference, RECOMB 2015, Proceedings
EditorsTeresa M. Przytycka
PublisherSpringer Verlag
Pages309-322
Number of pages14
ISBN (Electronic)9783319167053
DOIs
StatePublished - Jan 1 2015
Event19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015 - Warsaw, Poland
Duration: Apr 12 2015Apr 15 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9029
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2015
CountryPoland
CityWarsaw
Period4/12/154/15/15

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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