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Main Authors: Mondal, Probir, Banerjee, Pratyay, Pal, Debranjan, Basuli, Krishnendu
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2303.14994
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author Mondal, Probir
Banerjee, Pratyay
Pal, Debranjan
Basuli, Krishnendu
author_facet Mondal, Probir
Banerjee, Pratyay
Pal, Debranjan
Basuli, Krishnendu
contents We propose a new alignment-free algorithm by constructing a compact vector representation on $\mathbb{R}^{24}$ of a DNA sequence of arbitrary length. Each component of this vector is obtained from a representative sequence, the elements of which are the values realized by a function $Γ$. This function $Γ$ acts on neighborhoods of arbitrary radius that are located at strategic positions within the DNA sequence and carries complete information about the local distribution of frequencies of the nucleotides as a consequence of the uniqueness of prime factorization of integer. The algorithm exhibits linear time complexity and turns out to consume significantly small memory. The two natural parameters characterizing the radius and location of the neighbourhoods are fixed by comparing the phylogenetic tree with the benchmark for full genome sequences of fish mtDNA datasets. Using these fitting parameters, the method is applied to analyze a number of genome sequences from benchmark and other standard datasets. Our algorithm proves to be computationally efficient compared to other well known algorithms when applied on simulated dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2303_14994
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Similarity analysis of DNA sequences through local distribution of nucleotides in strategic neighborhood
Mondal, Probir
Banerjee, Pratyay
Pal, Debranjan
Basuli, Krishnendu
Data Structures and Algorithms
We propose a new alignment-free algorithm by constructing a compact vector representation on $\mathbb{R}^{24}$ of a DNA sequence of arbitrary length. Each component of this vector is obtained from a representative sequence, the elements of which are the values realized by a function $Γ$. This function $Γ$ acts on neighborhoods of arbitrary radius that are located at strategic positions within the DNA sequence and carries complete information about the local distribution of frequencies of the nucleotides as a consequence of the uniqueness of prime factorization of integer. The algorithm exhibits linear time complexity and turns out to consume significantly small memory. The two natural parameters characterizing the radius and location of the neighbourhoods are fixed by comparing the phylogenetic tree with the benchmark for full genome sequences of fish mtDNA datasets. Using these fitting parameters, the method is applied to analyze a number of genome sequences from benchmark and other standard datasets. Our algorithm proves to be computationally efficient compared to other well known algorithms when applied on simulated dataset.
title Similarity analysis of DNA sequences through local distribution of nucleotides in strategic neighborhood
topic Data Structures and Algorithms
url https://arxiv.org/abs/2303.14994