Graph-based multi-sequence alignment method and system

Abstract

The invention discloses a graph-based multi-sequence alignment method, system and device and a computer readable storage medium, and the method comprises the steps: obtaining a group of generic genome sequence data, and carrying out the composition of the generic genome sequence data to obtain a generic genome coloring graph; marking and acquiring characteristics of an access state of a single node of the colored graph, and traversing the colored graph to obtain a cSupB data model after the colored graph is decomposed; obtaining a cSupB data model after colored graph decomposition, and extracting offset value data features of nodes in the cSupB data model; and performing first preprocessing on the cSupB data model based on the offset value data features to obtain an initial comparison result of the cSupB data model. The problem that a traditional multi-sequence alignment mode cannot meet the current situation when a large number of sample genomes are sequenced at present is solved.

Description

technical field [0001] The invention belongs to the field of medical technology, and in particular relates to a graph-based multiple sequence alignment method and a system thereof. Background technique [0002] The development of life sciences, medicine and other fields is closely related to the application of sequencing technology. However, due to sequencing technology, sequencing costs and even computing costs, many genome studies have many problems, such as over-reliance on reference genomes. At present, the reference genome occupies a very important position in many fields. In almost all studies involving genomes, the first thing people have to do is to construct a reference genome for the research species, and then carry out different follow-up studies based on the reference genome, such as the Comparisons of newly sequenced individual data from other species of species to reference genomes reveal differences, an approach that underlies the search for the genetic origin...

AI Technical Summary

Problems solved by technology

However, due to the characteristics of high genome similarity, long sequence, and large sample size of the population, the estimation of the guide tree and the progressive alignment will inevitably lead to many redundant operations, which greatly increase the complexity of the calculation, and the entire alignment process is slow. high cost

In addition, if the method of preprocessing group comparison is adopted, it will also consume a lot of time and computing resources, and directly ignore the relationship between individual sequences between groups

[0005] In order to solve the problem that the traditional multiple sequence alignment method cannot meet the current situation when faced with a large number of sequenced sample genomes, the present invention provides a graph-based multiple sequence alignment method and its system

Images