A comparison of periodicity profile methods for sequence analysis

Manas Bellani, Julien Epps, Gavin A. Huttley

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
    Pages78-81
    Number of pages4
    DOIs
    Publication statusPublished - 2012
    Event2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012 - Washington, DC, United States
    Duration: 2 Dec 20124 Dec 2012

    Publication series

    NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
    ISSN (Print)2150-3001
    ISSN (Electronic)2150-301X

    Conference

    Conference2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2012
    Country/TerritoryUnited States
    CityWashington, DC
    Period2/12/124/12/12

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