Wavelet-based time series analysis of circadian rhythms
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Updated: May 29, 2026

A Computational Method to Quantify Fly Circadian Activity
Published on: October 28, 2017
Tanya L Leise1, Mary E Harrington
1Department of Mathematics, Amherst College, Amherst, MA 01002, USA. tleise@amherst.edu
Abstract:
Analysis of circadian oscillations that exhibit variability in period or amplitude can be accomplished through wavelet transforms. Wavelet-based methods can also be used quite effectively to remove trend and noise from time series and to assess the strength of rhythms in different frequency bands, for example, ultradian versus circadian components in an activity record. In this article, we describe how to apply discrete and continuous wavelet transforms to time series of circadian rhythms, illustrated with novel analyses of 2 case studies involving mouse wheel-running activity and oscillations in PER2::LUC bioluminescence from SCN explants.
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