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Bioinformatics Advance Access originally published online on October 17, 2008
Bioinformatics 2008 24(23):2794-2795; doi:10.1093/bioinformatics/btn521
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

WAVECLOCK: wavelet analysis of circadian oscillation

Tom S. Price 1,*, Julie E. Baggs 2, Anne M. Curtis 3, Garret A. FitzGerald 2 and John B. Hogenesch 2

1Institute of Psychiatry, Kings College London, 2Institute for Translational Medicine and Therapeutics, University of Pennsylvania and 3Bio Directorate, Science Foundation Ireland (SFI)

*To whom correspondence should be addressed.


  Abstract

Summary: Oscillations in mRNA and protein of circadian clock components can be continuously monitored in vitro using synchronized cell lines. These rhythms can be highly variable due to culture conditions and are non-stationary due to baseline trends, damping and drift in period length. We present a technique for characterizing the modal frequencies of oscillation using continuous wavelet decomposition to non-parametrically model changes in amplitude and period while removing baseline effects and noise.

Availability: The method has been implemented as the package waveclock for the free statistical software program R and is available for download from http://cran.r-project.org/

Contact: thomas.price{at}iop.kcl.ac.uk

Supplementary information: Supplementary figures are available at Bioinformatics online.

Associate Editor: Trey Ideker

Received on July 14, 2008; revised on August 26, 2008; accepted on October 5, 2008

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