Inversion Medians Outperform Breakpoint Medians in Phylogeny Reconstruction from Gene-Order Data View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2002-10-10

AUTHORS

Bernard M. E. Moret , Adam C. Siepel , Jijun Tang , Tao Liu

ABSTRACT

Phylogeny reconstruction from gene-order data has attracted much attention over the last few years. The two software packages used for that purpose, BPAnalysis and GRAPPA, both use so-called breakpoint medians in their computations. Some of our past results indicate that using inversion scores rather than breakpoint scores in evaluating trees leads to the selection of better trees. On that basis, we conjectured that phylogeny reconstructions could be improved by using inversion medians, which minimize evolutionary distance under an inversions-only model of genome rearrangement. Recent algorithmic developments have made it possible to compute inversion medians for problems of realistic size. Our experimental studies unequivocally show that inversion medians are strongly preferable to breakpoint medians in the context of phylogenetic reconstruction from gene-order data. Improvements are most pronounced in the reconstruction of ancestral genomes, but are also evident in the topological accuracy of the reconstruction as well as, surprisingly, in the overall running time. Improvements are strongest for small average distances along tree edges and for evolutionary scenarios with a preponderance of inversion events, but occur in all cases, including evolutionary scenarios with high proportions of transpositions. All of our tests were run using our GRAPPA package, available (under GPL) at www.cs.unm.edu/~moret/GRAPPA; the next release will include the inversion median software we used in this study. The software used includes RevMed, developed by the authors and available at www.cs.unm.edu/~acs, and A. Caprara’s inversion median code, generously made available for testing. More... »

PAGES

521-536

References to SciGraph publications

Book

TITLE

Algorithms in Bioinformatics

ISBN

978-3-540-44211-0
978-3-540-45784-8

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-45784-4_40

DOI

http://dx.doi.org/10.1007/3-540-45784-4_40

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1011497115


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