Specificity Analysis of Genome Based on Statistically Identical K-Words with Same Base Combination

Hyein Seo, Yong Joon Song, Kiho Cho, Dong Ho Cho

Research output: Contribution to journalArticlepeer-review

Abstract

Goal: Individual characteristics are determined through a genome consisting of a complex base combination. This base combination is reflected in the k-word profile, which represents the number of consecutive k bases. Therefore, it is important to analyze the genome-specific statistical specificity in the k-word profile to understand the characteristics of the genome. In this paper, we propose a new k-word-based method to analyze genome-specific properties. Methods: We define k-words consisting of the same number of bases as statistically identical k-words. The statistically identical k-words are estimated to appear at a similar frequency by statistical prediction. However, this may not be true in the genome because it is not a random list of bases. The ratio between frequencies of two statistically identical k-words can then be used to investigate the statistical specificity of the genome reflected in the k-word profile. In order to find important ratios representing genomic characteristics, a reference value is calculated that results in a minimum error when classifying data by ratio alone. Finally, we propose a genetic algorithm-based search algorithm to select a minimum set of ratios useful for classification. Results: The proposed method was applied to the full-length sequence of microorganisms for pathogenicity classification. The classification accuracy of the proposed algorithm was similar to that of conventional methods while using only a few features. Conclusions: We proposed a new method to investigate the genome-specific statistical specificity in the k-word profile which can be applied to find important properties of the genome and classify genome sequences.

Original languageEnglish (US)
Article number9140328
Pages (from-to)214-219
Number of pages6
JournalIEEE Open Journal of Engineering in Medicine and Biology
Volume1
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Alignment-free
  • genetic algorithm
  • k-word
  • microbial pathogenicity
  • statistical specificity in k-word profile

ASJC Scopus subject areas

  • Biomedical Engineering

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