Development Of Genetic Testing Report System

Background: In recent years,with the vigorous development of the national economy,the lifestyle changes had become more and more large,people no longer blindly pursued material satisfaction,but instead value spiritual and physical health.At this time,genetic testing technology,which can obtain useful information from the most fundamental genetic information of human beings,this process to produce readable and understandable data.Through the large amount of genetic information obtained by sequencing,allele loci associated with specific traits were obtained by experiments and comparisons.These allele loci cause allele polymorphisms for various reasons,thereby affecting related traits.Express the results.Based on these different expression results,a genetic database was established,and the genetic information of the tester was compared with the database to obtain the degree of genetic control trait,thereby providing more objective suggestion for the diagnosis of diseases and ability genes.Among them,the SNP played an extraordinary role.Through the results of genetic testing,compared with the SNP database,the results of the related traits on the tester were obtained,and a test report was given,which can directly reflect the traits of interest and related genes of the test subject.The results of the impact and the interpretation advice of certain professional knowledge was the reasons,why the technology industry was so highly sought after.However,genetic testing reports still had many problems in the production process,including:(1)The immature reported process,low efficiency and slow speed.(2)The explanations given were very different,and it was difficult to be convincing.(3)The report had a single layout mode and it was prone to garbled situations.Therefore,a mature system process was needed to meet the needs of this technology industry.The key points for the development and detection of the gene detection report system were the first,the typesetting problem of the report,the compilation of the report used LaTeX,the one-time solution of the layout mode and the garbled phenomenon that was easy to appear,simple and effective.Second,used the python language combined with crawler technology to obtain the scientific frontiers and related knowledge data needed for reporting from professional papers,it was convenient to update and modify the report.Third,put these data into the database can facilitate the search of the test items and improve the efficiency,accuracy of the genetic test report.Fourth,used the Python language,the modules combined and spliced to give full play to the role of ’glue’,made the gene detection reporting system more comprehensive and convenient.1.Reporting template compilationUsed LaTeX language to write a large number of report templates,the compilation required includes:(1)Compilation processing of basic format modules,(2)Basic information template compilation,(3)Detection result templates corresponded to genetic detection results.Because the number of detection items was large,the result template generated by the matching result also needed to be satisfied by the corresponding number.A total of 100 templates were compiled for use.The template can be compiled using ATOM or TEXlive software.Ability to generate the required report pdf format directly used the template to generate reports quickly and accurately.2.Acquisition of SNP related data informationCompiling the test result template required a large amount of relevant biological knowledge and technical support,which was mainly obtained from MEDLINE(Biomedical Database)or ncbi papers.Obtained includes the required:(1)SNP locus,whose associated traits were what we need.(2)How the polymorphism of its locus affected the relevant traits and even the individual.Medical significance.(3)Combined the information to give more professional advice.The acquired data needs to be reflected in the test result template.The subject collected a total of 120 SNP loci and their associated traits.In order to obtain these data,python scripts were combined with web crawler technology to obtain the required information from the PubMed database.After processing according to the database format requirements,it was stored in the database for use to achieve ’filtering’ when calling the template.3.the construction of the databaseThe database was built using Mysql to build the library,the reason for use was(1)Simple and convenient.(2)Can be interoperated by using python language.(3)It was quick and convenient to query the number of detection results and individuals in the database,it can quickly query whether there were detection items required by the person to be tested.(4)It was through the database that the calling process can be simplified when the detection result template was called,and all the detection result templates can be ’filtered’ before the required template was called,and only the detection result templates related to the detection items were put together for input.The information was matched using the call.This shortens the time it took to call the template and increased efficiency,which in turn improved the accuracy of the calling template.Conclusion: The built genetic detection reporting system used LaTeX language to compile report templates,which can better solve the garbled problems in the word compilation process,increased the template style,and be neat and tidiness.used python language to write web crawler technology scripts to obtain data.And primary screened,the required SNP and its related traits and their impact information were stored,and the obtained information was stored in the Mysql database according to a certain format,which was convenient for querying and calling the template.Introduction to use:(1)Determine the format of the input file.(2)Divide the input file into two parts: the basic information part,the test result,and enter the system separately.(3)Used the basic information template and the test result template to form the final template,generated a pdf file,and generate a report.This reporting system was a good complement to the use of genetic testing technology.