Statistical Analysis of Biological Rhythm Data

The author has developed an ensemble of digital signal analysis techniques applicable to biological time series containing circadian and ultradian periodicities that is of very high resolution and functions well even in the presence of extreme noise and trend. A method for quantifying the significance, strength, and regularity of the rhythmic process is included. To illustrate these techniques, the author presents analyses of artificial periodic data containing varying amounts of noise, trend, and multiple periodicities. The periods and amplitudes of circadian and, where included, ultradian periodicities, and all other components of the test signals are known exactly. Analyses are illustrated in a step-by-step manner and the results are compared with the known input parameters. Trends are removed; spectra, autocorrelation functions, and rhythmicity indices are produced and discussed. References covering theory and details of all analyses are supplied. All programs employed are available from the author free of charge.