Abstract
The success of genomic sequencing is impossible without the development of information technologies and mathematical methods for data processing to establish various characteristics of the analyzed objects (nucleic acids) and trends in their variation. The volume of experimental data from studying the genome has substantially increased, and new methods and algorithms are required for their processing. The evaluation of the parameters of images obtained from video cameras in the form of electrical signals is a primary step in processing the data from devices for genomic parallel sequencing. The next stage of processing is the construction of a nucleotide sequence according to algorithms that depend on the operation principle of a device for sequencing nucleic acids. Algorithms for assessing quality scores in all individual reads are important in this stage. The use of algorithms based on the analysis of k-mers is one of the ways to assess the quality score. Calculation of the number of occurrence of k-mers during the experiment on a parallel sequencing system makes it possible to assess the reliability of the analysis. In this paper, algorithms for processing data of a genetic analyzer are reviewed.
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Funding
The study was performed within the framework of state order no. 075-00280-21-00 from the Ministry of Science and Higher Education of the Russian Federation on topic no. 0074-2019-0013.
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Translated by O. Kadkin
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Manoilov, V.V., Borodinov, A.G., Saraev, A.S. et al. Algorithms for Image Processing in a Nanofor SPS DNA Sequencer. Tech. Phys. 67, 304–310 (2022). https://doi.org/10.1134/S1063784222050061
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DOI: https://doi.org/10.1134/S1063784222050061