Avoiding Ambiguity and Assessing Uniqueness in Minisatellite Alignment

Authors Benedikt Löwes, Robert Giegerich

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Benedikt Löwes
Robert Giegerich

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Benedikt Löwes and Robert Giegerich. Avoiding Ambiguity and Assessing Uniqueness in Minisatellite Alignment. In German Conference on Bioinformatics 2013. Open Access Series in Informatics (OASIcs), Volume 34, pp. 110-124, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


Several algorithms have been suggested for minisatellite alignment. Their time complexity is high -- close to O(n^3) -- due to the necessary reconstruction of duplication histories. We investigate the uniqueness of optimal alignments computed under the common single-copy duplication model. To this extent, it is necessary to avoid ambiguity in the algorithm employed. We re-code the ARLEM algorithm in the form of a grammar, and apply a disambiguation technique which uses a mapping to a canonical representation of minisatellite alignments. Having arrived at a non-ambiguous algorithm this way, we demonstrate that the underlying model -- independent of the algorithm -- gives rise to an exorbitant number of different, co-optimal alignments when applied to real-world data. We conclude that alignment-free methods should be considered for minisatellite comparison.
  • minisatellite alignment
  • dynamic programming
  • ambiguity


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