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Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation

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  • Pal, Mayukha
  • Kiran, V. Satya
  • Rao, P. Madhusudana
  • Manimaran, P.

Abstract

We characterized the multifractal nature and power law cross-correlation between any pair of genome sequence through an integrative approach combining 2D multifractal detrended cross-correlation analysis and chaos game representation. In this paper, we have analyzed genomes of some prokaryotes and calculated fractal spectra h(q) and f(α). From our analysis, we observed existence of multifractal nature and power law cross-correlation behavior between any pair of genome sequences. Cluster analysis was performed on the calculated scaling exponents to identify the class affiliation and the same is represented as a dendrogram. We suggest this approach may find applications in next generation sequence analysis, big data analytics etc.

Suggested Citation

  • Pal, Mayukha & Kiran, V. Satya & Rao, P. Madhusudana & Manimaran, P., 2016. "Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 288-293.
    • Handle: RePEc:eee:phsmap:v:456:y:2016:i:c:p:288-293
    DOI: 10.1016/j.physa.2016.03.074
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    References listed on IDEAS

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    Cited by:

    1. Meraz, Monica & Carbó, Roxana & Rodriguez, Eduardo & Alvarez-Ramirez, Jose, 2023. "Fractal correlations in the Covid-19 genome sequence via multivariate rescaled range analysis," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Cao, Guangxi & Zhang, Minjia & Li, Qingchen, 2017. "Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 472(C), pages 67-76.

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