Identification of Microsatellites in DNA Using Adaptive S-Transform

Abstract

Microsatellites are tandem repeats of size 1-6 base pairs, associated with various diseases, DNA fingerprinting, and also useful in evolutionary studies. A signal processing algorithm for microsatellite detection, based on adaptive S-transform is proposed. The standard deviation of the Gaussian window kernel of the S-transform has been optimized for integer periods of interest by maximizing the concentration measure. The time-frequency plot is generated using optimal standard deviation values. Candidate repeats are marked by comparing the spectrogram values in the time-frequency plot with a threshold. A preprocessing phase followed by a verification phase extracts final results from the candidate repeats. Simulation studies on DNA sequences establish the superiority of this algorithm over other existing methods. Applicability of this algorithm in the analysis of DNA sequences associated with repeat expansion diseases has also been demonstrated.