A time warping approach to multiple sequence alignment

Arribas-Gil Ana and Matias Catherine ()
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Arribas-Gil Ana: Departamento de Estadística, Universidad Carlos III de Madrid, C/ Madrid, 126 - 28903 Getafe, Spain
Matias Catherine: Sorbonne Universités, Université Pierre et Marie Curie, Université Paris Diderot, Centre National de la Recherche Scientifique, Laboratoire de Probabilités et Modèles Aléatoires, 4 place Jussieu, 75252 PARIS Cedex 05, France

Statistical Applications in Genetics and Molecular Biology, 2017, vol. 16, issue 2, 133-144

Abstract: We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares.

Keywords: Alignment; dynamic time warping; multiple sequence alignment; warping (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1515/sagmb-2016-0043

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