Phase-only filtering for the masses (of DNA Data): a new approach to sequence alignment

Abstract

Alignment of DNA segments containing repetitive nucleotide base patterns is an important task in several genomics applications, including DNA sequencing, DNA fingerprinting, pathogen detection, and gene finding. One of the most efficient procedures used for this task is the cross correlation method. The main computations of the procedure are the discrete Fourier transform (DFT) and a pointwise multiplication of two complex Fourier transform sequences. In this paper, the standard magnitude-and-phase cross correlation technique is compared with the lesser known but closely related phase-only cross correlation method. It is shown that for a periodic DNA sequence, the standard approach leads to significant sidelobes in the cross correlation, the magnitude of which increases with sequence length, while the phase-only approach yields a perfect cross correlation with zero sidelobes. For a DNA sequence that contains both irregularly distributed symbols and periodic patterns, the difference in performance is less pronounced, but still significant. Numerical experiments on synthesized and real data demonstrate that the phase-only approach is robust to isolated symbol insertions and deletions and that it is capable of identifying positions of matching segments in the sequence.

Optical pattern generator for efficient bio-data encoding in a photonic sequence comparison architecture

“…Sequence aligners compare two or more genetic sequences (DNA, RNA, or protein), to discover their similarities and differences. The alignment of genetic sequences is adopted in various applications, such as DNA sequencing, DNA fingerprinting, pathogen detection, gene detection, tracing disease and cancer, tracing ancestry and evolutionary, and drug designation [ 1 – 3 ]. The aforementioned variety of applications alongside the ever-increasing requirement in sequencing high volume of large biological data has led to the importance of designing a fast, accurate, and scalable sequence alignment tool.…”

Statistical Analysis of Phase-Only Correlation Functions between Real Signals with Stochastic Phase-Spectrum Differences

“…Phase-only correlation (POC) functions have been widely used in many fields for evaluating the similarity between two signals. They are quite useful to realize many high accuracy signal matching techniques, such as image registration [1]- [6], pattern recognition [7]- [9], motion estimation [10]- [12], the frame displacement for old films [13], [14], matching periodic DNA sequences [15], optics [16], and so on.…”

Statistical Analysis of Phase-Only Correlation Functions with Phase-Spectrum Differences Following Wrapped Distributions

“…Phase-only correlation (POC) functions have been widely used for evaluating similarity between two signals. They have been applied in many fields, such as image registration [1]- [6], pattern recognition [7]- [9], motion estimation [10]- [12], frame displacement for old films [13], [14], matching periodic DNA sequences [15], optics [16], and so on. It has been known that the POC function is the delta function if the phase spectra of two signals given are completely equal.…”