Simulation modelling of single nucleotide genetic polymorphisms

  • Mikalai M.   Yatskou Belarusian State University, 4 Niezaliezhnasci Avenue, Minsk 220030, Belarus
  • Vladimir V. Apanasovich Independent researcher, Minsk, Belarus
  • Vasily V. Grinev Belarusian State University, 4 Niezaliezhnasci Avenue, Minsk 220030, Belarus

Abstract

We propose an approach for the identification of single nucleotide polymorphisms (SNPs) in DNA sequences, based on the simulation modelling of sites of single nucleotides using the generation of random events according to the beta or normal distributions, the parameters of which are estimated from the available experimental data. The developed approach improves the accuracy of determining SNPs in DNA molecules and permits to investigate the reliability of specific experiments as well as to estimate the errors of determination of the parameters obtained in real experimental conditions. The verification of the simulation model and analysis methods is carried out on a set of reference human genomic DNA sequencing data provided by the Genome in a Bottle Consortium. The comparative analysis of the existing statistical SNP identification algorithms and machine learning methods, trained on the simulated data from the genomic sequencing of human DNA molecules, is carried out. The best results are obtained for machine learning models, in which the accuracy of SNP identification is 2–5 % higher than for classical statistical methods.

Author Biographies

Mikalai M.   Yatskou, Belarusian State University, 4 Niezaliezhnasci Avenue, Minsk 220030, Belarus

PhD (physics and mathematics), docent; head of the department of systems analysis and computer simulation, faculty of radiophysics and computer technologies

Vladimir V. Apanasovich, Independent researcher, Minsk, Belarus

doctor of science (physics and mathematics), full professor; independent researcher

Vasily V. Grinev, Belarusian State University, 4 Niezaliezhnasci Avenue, Minsk 220030, Belarus

PhD (biology), docent; associate professor at the department of genetics, faculty of biology

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Published
2024-08-02
Keywords: single nucleotide polymorphism, SNP, SNP identification, simulation modelling, machine learning
Supporting Agencies This work was carried out in the framework of the state programme of scientific research «Convergence-2025» (grant No. 3.04.3.1, state registration No. 20211918).
How to Cite
Yatskou, M. M.  , Apanasovich, V. V., & Grinev, V. V. (2024). Simulation modelling of single nucleotide genetic polymorphisms. Journal of the Belarusian State University. Mathematics and Informatics, 2, 104-112. Retrieved from https://journals.bsu.by/index.php/mathematics/article/view/6114
Issue
No 2 (2024): Journal of the Belarusian State University. Mathematics and Informatics
Section
Theoretical Foundations of Computer Science

Copyright (c) 2024 Journal of the Belarusian State University. Mathematics and Informatics

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