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A comparison of periodicity profile methods for sequence analysis

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3 Author(s)
Manas Bellani ; School of Electrical Eng. and Telecommunications The University of New South Wales, Sydney, Australia ; Julien Epps ; Gavin A. Huttley

While period detection in biological sequence data has received considerable attention, it is unclear which methods may be best suited to the problem of exploratory period estimation, where the objective is to compare the relative strengths of many periods on a linear-period scale. This paper compares several promising methods for period estimation on an integer-period scale in terms of attributes such as correct identification of dominant periods, period resolution and computational complexity, using synthetic sequences. Different methods reveal very different periodicity profiles, however the exactly periodic subspace decomposition and hybrid autocorrelation-IPDFT methods seem to provide good performance with respect to the above attributes. Finally, the methods are compared for a challenging DNA sequence fragment, from P.falciparum.

Published in:

Genomic Signal Processing and Statistics, (GENSIPS), 2012 IEEE International Workshop on

Date of Conference:

2-4 Dec. 2012