Characterization of Genetic Mutations Using DNA Walks and Multifractal Detrended Fluctuation Analysis

ABSTRACT

Monitoring genetic mutations in DNA sequences and their subsequent characterisation provide the possibility for rapid development of diagnostics and therapeutic tools. Here, it is shown that the "DNA walk" (DNAW) representation together with multifractal detrended fluctuation analysis (MFDFA), i.e. DNAW/MFDFA, form a reliable characterization method for studying local and global properties of similar DNA sequences. The DNAW/MFDFA approach allows to study the stochastic properties of genetic sequences by constructing a one-to-one map of the sequence onto a walk, and is able to uncover the self-similarity properties of DNA walks. These features are illustrated on a set of similar DNA sequences of SARS-CoV-2 virus, in which the differences in nucleotide bases arise due to genetic mutations. The results show that DNAW/MFDFA can be used to extract long-range correlation information and type and degree of fractal complexity.