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Phylogenetic analysis of DNA sequences based on fractional Fourier transform

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  • Qian, Kun
  • Luan, Yihui

Abstract

Phylogenetic analysis of molecular sequences for inferring evolutionary relationships is an essential problem in biology. In this paper, we make an extension of Power Spectrum Moments method based on discrete fractional Fourier transform for phylogenetic analysis. DNA sequences are first converted into numeric sequences, and discrete fractional Fourier transform is then used on these numeric sequences to compute power spectra. By extracting a new j th moment feature based on power spectra, distance matrix is constructed and phylogenetic tree is built. Moreover, we give a guideline for choosing an appropriate order p of discrete fractional Fourier transform through simulation strategy and Friedman test. Our method is tested on three real datasets. Comparing with the Power Spectrum Moments method based on discrete Fourier transform and d2∗ measure, the results of phylogenetic trees demonstrate that our method is more efficient in inferring biological relationships.

Suggested Citation

  • Qian, Kun & Luan, Yihui, 2018. "Phylogenetic analysis of DNA sequences based on fractional Fourier transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 795-808.
    • Handle: RePEc:eee:phsmap:v:509:y:2018:i:c:p:795-808
    DOI: 10.1016/j.physa.2018.06.044
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    References listed on IDEAS

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    1. Li, Yushuang & Liu, Qian & Zheng, Xiaoqi, 2016. "DUC-Curve, a highly compact 2D graphical representation of DNA sequences and its application in sequence alignment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 256-270.
    2. Yu, Hong-Jie & Huang, De-Shuang, 2012. "Novel graphical representation of genome sequence and its applications in similarity analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 6128-6136.
    3. Ying Wang & Lin Liu & Lina Chen & Ting Chen & Fengzhu Sun, 2014. "Comparison of Metatranscriptomic Samples Based on k-Tuple Frequencies," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-19, January.
    4. Li, Chun & Yang, Yan & Jia, Meiduo & Zhang, Yingying & Yu, Xiaoqing & Wang, Changzhong, 2014. "Phylogenetic analysis of DNA sequences based on k-word and rough set theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 162-171.
    5. Hou, Wenbing & Pan, Qiuhui & He, Mingfeng, 2014. "A novel representation of DNA sequence based on CMI coding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 409(C), pages 87-96.
    6. Guangchen Liu & Yihui Luan, 2014. "Identification of Protein Coding Regions in the Eukaryotic DNA Sequences Based on Marple Algorithm and Wavelet Packets Transform," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-14, July.
    7. Liao, Bo & Xiang, Qilin & Cai, Lijun & Cao, Zhi, 2013. "A new graphical coding of DNA sequence and its similarity calculation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4663-4667.
    8. Qian, Kun & Luan, Yihui, 2017. "Weighted measures based on maximizing deviation for alignment-free sequence comparison," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 235-242.
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