Hypertension Polymorphic Position Mining Detection Based On Dynamic Short Sequence Alignment Algorithm

In recent years,the incidence of hypertension in China has increased year by year,and the incidence of hypertension is becoming younger and younger,which seriously threatens the health of residents.Because the cause of the disease is complex,most of them are the result the comprehensive effects of genetic factors,environmental factors,lifestyle and so on,so it is difficult to prevent and treat research.As a third-generation molecular marker,single nucleotide polymorphism plays an important role in the study of the relationship between expression genes and diseases.By identifying and detecting the SNPs in the genome sequence of hypertensive patients,the susceptibility genes of hypertension are determined,and the molecular mechanism of hypertension formation is explored at the gene level,which is of great significance and value for the prevention and treatment of hypertension.With the rapid development of bioinformatics and bioinformation technology,the cost of high-throughput sequencing has decreased,which makes biological data grow explosively,which brings opportunities for SNPs mining research and also brings great challenges.At present,the main problem in this field is that the existing SNPs recognition algorithm can not meet the need of big data analysis.How to quickly and accurately mine hypertensive disease-related SNPs from massive clinical medical data,and to convert complex and long base sequences into highly readable information is the focus and difficulty of current research.In this paper,through the deep study of the current mainstream SNPs recognition detection algorithm,a SNPs recognition and detection model based on dynamic short sequence alignment algorithm is proposed to accurately locate and quickly find SNPs sites.This article has been innovative in the following areas:(1)A hybrid index algorithm based on the combination of FM_index index and hash index is proposed.The sequencing sequence of sequencing results can be quickly located in the reference sequence,which can solve the problem that the sequencing data sequence is short and the number is large,and the detection of the SNPs is slow due to the short sequence data sequence in the biological large data age;(2)A local SNPs database was constructed.Based on this,a fast SNPs recognition and detection model based on dynamic programming strategy is designed.Based on the precise sequence location,the detection efficiency of hypertensive polymorphism detection was improved.In this paper,we mainly studied the detection model of SNPs in high blood pressure from short sequence location,SNPs database construction,SNPs recognition and visualization;The data of the SRA second-generation sequencing database in the NCBI public database was used to verify the accuracy and validity of the model through the original second-generation sequencing data;The R language and its visualization software package are used to visually display the test results in the form of graphic images.