Skip Navigation



Bioinformatics Advance Access published online on November 22, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti789
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow Supplementary Data
Right arrow All Versions of this Article:
22/3/310    most recent
bti789v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Glynn, E. F.
Right arrow Articles by Mushegian, A. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Glynn, E. F.
Right arrow Articles by Mushegian, A. R.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 13, 2005
Revised October 26, 2005
Accepted November 15, 2005

Article

Detecting periodic patterns in unevenly spaced gene expression time series using Lomb-Scargle periodograms

Earl F. Glynn 1, Jie Chen 2 *, and Arcady R. Mushegian 3

1 Stowers Institute for Medical Research, 1000 East 50th Street, Kansas City, MO 64110, USA
2 Stowers Institute for Medical Research, 1000 East 50th Street, Kansas City, MO 64110, USA; Department of Mathematics and Statistics, University of Missouri-Kansas City, 5100 Rockhill Road, Kansas City, MO 64110, USA
3 Stowers Institute for Medical Research, 1000 East 50th Street, Kansas City, MO 64110, USA; Department of Microbiology, Immunology and Molecular Genetics, University of Kansas Medical Center, Kansas City, KS 66160, USA

* To whom correspondence should be addressed.
Jie Chen, E-mail: chenj{at}umkc.edu


  Abstract

Motivation: Periodic patterns in time series resulting from biological experiments are of great interest. The commonly used Fast Fourier Transform algorithm is applicable only when data are evenly spaced and when no values are missing, which is not always the case in high-throughput measurements. The choice of statistic to evaluate the significance of the periodic patterns for unevenly spaced gene expression time series has not been well substantiated.

Methods: The Lomb-Scargle periodogram approach is used to search time series of gene expression to quantify the periodic behavior of every gene represented on the DNA array. The Lomb-Scargle periodogram analysis provides a direct method to treat missing values and unevenly spaced time points. We propose the combination of a Lomb-Scargle test statistic for periodicity and a multiple hypothesis testing procedure with controlled false discovery rate to detect significant periodic gene patterns.

Results: We analyzed the Plasmodium falciparum gene expression dataset. In the Quality Control Dataset of 5080 expression patterns, we found 4112 periodic probes. In addition, we identified 243 probes with periodic expression in the Complete Dataset, which could not be examined in the original study by the FFT analysis due to an excessive number of missing values. While most periodic genes had a period of about 48 hr, some had a period close to 24 hr. Our approach should be applicable for detection and quantification of periodic patterns in any unevenly spaced gene expression time series data.

Availability: The computations were performed in R. The R code is available from http://research.stowers-institute.org/efg/2005/LombScargle.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Nucleic Acids ResHome page
N. P. Gauthier, M. E. Larsen, R. Wernersson, U. de Lichtenberg, L. J. Jensen, S. Brunak, and T. S. Jensen
Cyclebase.org a comprehensive multi-organism online database of cell-cycle experiments
Nucleic Acids Res., January 11, 2008; 36(suppl_1): D854 - D859.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.