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Optimal Sequence Alignment to ED-Strings

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Bioinformatics Research and Applications (ISBRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 13760))

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Abstract

Partial Order Alignment (POA) was introduced by Lee et al. in 2002 to allow the alignment of a string to a graph-like structure representing a set of aligned strings (a Multiple Sequence Alignment, MSA). However, the POA edit transcript (the sequence of edit operations that describe the alignment) does not reflect the possible elasticity of the MSA (different gaps sizes in the aligned string), leaving room for possible misalignment and its propagation in progressive MSA. Elastic-Degenerate Strings (ED-strings) are strings that can represent the outcome of an MSA by highlighting gaps and variants as a list of strings that can differ in size and that can possibly include the empty string. In this paper, we define a method that optimally aligns a string to an ED-string, the latter compactly representing an MSA, overcoming the ambiguity in the POA edit transcript while maintaining its time and space complexity.

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Notes

  1. 1.

    In [14, 15] the size of the ED-string \(\widetilde{T}\) is defined in a slightly different way as the actual number of letters or empty strings that appear in \(\widetilde{T}\).

  2. 2.

    The method can generalize to the case of cost \(s>0\) for skips.

  3. 3.

    In an edit distance computation framework, the match has typically null cost in order to fulfill the metric requirement that a string has zero-distance to itself; for this reason in our examples we assume \(a=0\). However, since the the dynamic programming method we design also works when one wants to compute a similarity score rather than a distance (it suffices to adapt the penalty scores and seek the maximum instead of the minimum), then in our problem statement as well as in the recurrence formula that describe our algorithm, we parametrize the score of a match with a.

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Acknowledgment

This work is part of the ALPACA project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 956229.

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Authors and Affiliations

  1. Department of Computer Science, University of Pisa, Pisa, Italy

    Njagi Moses Mwaniki & Nadia Pisanti

Authors
  1. Njagi Moses Mwaniki
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  2. Nadia Pisanti
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Correspondence to Nadia Pisanti .

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Editors and Affiliations

  1. University of Connecticut, Storrs, CT, USA

    Mukul S. Bansal

  2. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  3. University of Southern California, Los Angeles, CA, USA

    Serghei Mangul

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Mwaniki, N.M., Pisanti, N. (2022). Optimal Sequence Alignment to ED-Strings. In: Bansal, M.S., Cai, Z., Mangul, S. (eds) Bioinformatics Research and Applications. ISBRA 2022. Lecture Notes in Computer Science(), vol 13760. Springer, Cham. https://doi.org/10.1007/978-3-031-23198-8_19

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  • DOI: https://doi.org/10.1007/978-3-031-23198-8_19

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  • Online ISBN: 978-3-031-23198-8

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