The success of genomic sequencing is impossible without the development of information technologies and mathematical methods for data processing to establish various features in the analyzed objects (nucleic acids) and trends in their changes. The volume of experimental data in the research of the genome has grown significantly, and new methods and algorithms are required for their processing. The primary stage of processing the data of devices for genomic parallel sequencing is the evaluation of the parameters of images obtained from video cameras in the form of electrical signals. The next stage of processing is the construction of a sequence of nucleotides according to algorithms that depend on the principle of operation of the device for sequencing nucleic acids. When performing this stage, algorithms for evaluating quality indicators for all individual readings (reads) are important. One of the ways to assess quality is to use algorithms based on the k-measure analysis methodology. The calculation of the number of occurrences of k-measures during the experiment on the parallel sequencing system makes it possible to assess the reliability of the analysis. In this article, algorithms for processing genetic analyzer data are considered. Keywords: sequencing, nucleic acid, data processing, image processing.