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Directly computing Fourier power spectra at fractional periods of real sequences can be beneficial in many digital signal processing applications. In this article, we present a fast algorithm to compute the fractional Fourier power spectra of real sequences. For a real sequence of length of m = n l , we may deduce its congruence derivative sequence with a length of l. The discrete Fourier transform of the original sequence can be calculated by the discrete Fourier transform of the congruence derivative sequence. The relation of discrete Fourier transforms between the two sequences may derive the special features of Fourier power spectra of the integer and fractional periods for a real sequence. It has been proved mathematically that after calculating the Fourier power spectrum (FPS) at an integer period, the Fourier power spectra of the fractional periods related this integer period can be easily represented by the computational result of the FPS at the integer period for the sequence. Computational experiments using a simulated sinusoidal data and protein sequence show that the computed results are a kind of Fourier power spectra corresponding to new frequencies that cannot be obtained from the traditional discrete Fourier transform. Therefore, the algorithm would be a new realization method for discrete Fourier transform of the real sequence. [ABSTRACT FROM AUTHOR]

DNA sequences are fundamental for encoding genetic information. The genetic information may be understood not only from symbolic sequences but also from the hidden signals inside the sequences. The symbolic sequences need to be transformed into numerical sequences so the hidden signals can be revealed by signal processing techniques. All current transformation methods encode DNA sequences into numerical values of the same length. These representations have limitations in the applications of genomic signal compression, encryption, and steganography. We propose a novel integer chaos game representation (inter-CGR or iCGR) of DNA sequences and a lossless encoding method DNA sequences by the iCGR. In the iCGR method, a DNA sequence is represented by the iterated function of the nucleotides and their positions in the sequence. Then the DNA sequence can be uniquely encoded and recovered using three integers from iCGR. One integer is the sequence length and the other two integers represent the accumulated distributions of nucleotides in the sequence. The integer encoding scheme can compress a DNA sequence by 2 bits per nucleotide. The integer representation of DNA sequences provides a prospective tool for sequence analysis and operations. [ABSTRACT FROM AUTHOR]

Multiplexed molecular barcoded amplicon sequencing has been previously demonstrated to improve the sensitivity of low-frequency variant detection. Molecular barcoded reads can be used to identify and correct amplification biases introduced during library preparation and sequencing errors. We propose a generic workflow to improve variant calling accuracy that takes advantage of molecular barcoded sequencing reads by applying a base score correction method to duplicate or overlapping read pairs across the targeted panel. The workflow is able to reduce the false-positive rate of variant calls in homopolymer and repetitive regions where the sequencer commonly encounters phasing errors interfering with base calling. The analysis was focused on three specific regions within a custom QIAseq targeted DNA (Qiagen, USA) of 220 genes observed to have a high false-positive rate in a clinical validation study. Uncorrected and corrected datasets were compared at targeted regions to reference calls from NIST and exome data from a reference laboratory (Macrogen, USA). Base correction removed all false positives identified without the correction method and retained the true positive call in the dataset. We have shown that our workflow incorporating base correction of molecular barcoded sequencing data can be applied to germline sequencing to improve variant calling accuracy in genomic regions with certain repetitive sequence motifs. [ABSTRACT FROM AUTHOR]

According to the WHO, ebolaviruses have resulted in 8818 human deaths in West Africa as of January 2015. To better understand the evolutionary relationship of the ebolaviruses and infer virulence from the relationship, we applied the alignment-free natural vector method to classify the newest ebolaviruses. The dataset includes three new Guinea viruses as well as 99 viruses from Sierra Leone. For the viruses of the family of Filoviridae, both genus label classification and species label classification achieve an accuracy rate of 100%. We represented the relationships among Filoviridae viruses by Unweighted Pair Group Method with Arithmetic Mean (UPGMA) phylogenetic trees and found that the filoviruses can be separated well by three genera. We performed the phylogenetic analysis on the relationship among different species of Ebolavirus by their coding-complete genomes and seven viral protein genes (glycoprotein [GP], nucleoprotein [NP], VP24, VP30, VP35, VP40, and RNA polymerase [L]). The topology of the phylogenetic tree by the viral protein VP24 shows consistency with the variations of virulence of ebolaviruses. The result suggests that VP24 be a pharmaceutical target for treating or preventing ebolaviruses. [ABSTRACT FROM AUTHOR]

Alignment-free sequence analysis approaches provide important alternatives over multiple sequence alignment (MSA) in biological sequence analysis because alignment-free approaches have low computation complexity and are not dependent on high level of sequence identity. However, most of the existing alignment-free methods do not employ true full information content of sequences and thus can not accurately reveal similarities and differences among DNA sequences. We present a novel alignment-free computational method for sequence analysis based on Ramanujan-Fourier transform (RFT), in which complete information of DNA sequences is retained. We represent DNA sequences as four binary indicator sequences and apply RFT on the indicator sequences to convert them into frequency domain. The Euclidean distance of the complete RFT coefficients of DNA sequences are used as similarity measures. To address the different lengths of RFT coefficients in Euclidean space, we pad zeros to short DNA binary sequences so that the binary sequences equal the longest length in the comparison sequence data. Thus, the DNA sequences are compared in the same dimensional frequency space without information loss. We demonstrate the usefulness of the proposed method by presenting experimental results on hierarchical clustering of genes and genomes. The proposed method opens a new channel to biological sequence analysis, classification, and structural module identification. [ABSTRACT FROM AUTHOR]