Algorithms of Processing Fluorescence Signals for Mass Parallel Sequencing of Nucleic Acids

Abstract

Determination of the nucleotide sequence of DNA or RNA containing from several hundred to hundreds of millions of monomers units allows to obtain detailed information about the genome of humans, animals and plants. The deciphering of nucleic acids’ structure was learned quite a long time ago, but initially the decoding methods were low-performing, inefficient and expensive. Methods for decoding nucleotide nucleic acid sequences are usually called sequencing methods. Instruments designed to implement sequencing methods are called sequencers. Sequencing new generation (SNP), mass parallel sequencing are related terms that describe the technology of high-performance DNA sequencing in which the entire human genome can be sequenced within a day or two. The previous technology used to decipher the human genome required more than ten years to get final results. A hardware-software complex (HSC) is being developed to decipher the nucleic acid sequence (NA) of pathogenic microorganisms using the method of NGS in the Institute for Analytical Instrumentation of the Russian Academy of Sciences. The software included in the HSC plays an essential role in solving genome deciphering problems. The purpose of this article is to show the need to create algorithms for the software of the HSC for processing signals obtained in the process of genetic analysis when solving genome deciphering problems, and also to demonstrate the capabilities of these algorithms. The paper discusses the main problems of signal processing and methods for solving them, including: automatic and semi-automatic focusing, background correction, detection of cluster images, estimation of the coordinates of their positions, creation of templates of clusters of NA molecules on the surface of the reaction cell, correction of influence neighboring optical channels for intensities of signals and the assessment of the reliability of the results of genetic analysis