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Permutation test for periodicity in short time series data.

Andrey A Ptitsyn1, Sanjin Zvonic, Jeffrey M Gimble

  • 1Experimental Obesity Laboratory, Louisiana State University Pennington Biomedical Research Center, 6400 Perkins Rd,, Baton Rouge, LA 70808, USA. Andrey.Ptitsyn@pbrc.edu

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|November 23, 2006
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Summary

We developed a new computational method, the Permutated time (Pt) test, to identify circadian gene expression patterns in short microarray time series data. This method effectively detects biological rhythms despite noise and limited data points, aiding in understanding metabolic pathway regulation.

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Area of Science:

  • Genomics
  • Systems Biology
  • Chronobiology

Background:

  • Circadian rhythms regulate gene transcription in key metabolic pathways.
  • Disruptions in circadian gene expression can lead to metabolic disorders.
  • Analyzing time-series gene expression data for circadian patterns is challenging due to data limitations.

Purpose of the Study:

  • To develop a computational method for identifying circadian patterns in short microarray time series.
  • To address challenges posed by noise and limited data points in expression profiles.
  • To enable more accurate analysis of circadian gene regulation.

Main Methods:

  • Developed the Permutated time (Pt) test, a computational technique.
  • The Pt-test uses random permutation of time points to assess periodogram non-randomness.
  • Applied the Pt-test to analyze circadian expression in murine tissues and independent datasets.

Main Results:

  • The Pt-test effectively identifies periodic patterns in short time series data.
  • The method is robust against high stochastic fluctuations and irrelevant frequencies.
  • Successfully analyzed large datasets from multiple research groups, confirming its broad applicability.

Conclusions:

  • The Permutated time test is a reliable tool for detecting periodicity in microarray-derived time series.
  • The Pt-test software is available as open-source C++ programs.
  • This method facilitates the study of circadian rhythms in gene expression.