Detection and 2-Dimensional display of short tandem repeats based on signal decomposition

Authors:
Rong Jiang;Hong Yan
Affiliations:
School of Electrical and Information Engineering, University of Sydney, NSW 2006, Australia.;Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2011

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Abstract

This paper presents a wavelet-based Empirical Mode Decomposition (EMD) to detect short tandem repeats in DNA sequences. A wavelet subspace algorithm combined with EMD is introduced as a pre-processor and a Cross-Correlation Analysis (CCA) is applied as a post-processor to create subspaced Intrinsic Mode Functions (IMFs). The new proposed method is called the Empirical Mode and Wavelet Decomposition (EMWD). The algorithms can display the power spectral density in the two-dimensional frequency-time (f-t) plane efficiently for both very long signals and short signals. Simulations are applied on the real human DNA sequences from public data source Genbank (http://www.ncbi.nlm.nih.gov/Genbank/). Application of the EMWD algorithms to the short tandem repeat detection has achieved an averaged accuracy of 98.5%.