Biological information data analysis and result quality control automation method and system

Abstract

The invention discloses a biological information data analysis and result quality control automation method. The method comprises the steps of downloading data, inputting or acquiring standard sampledetection information, traversing unanalyzed standard samples, putting the unanalyzed standard samples into a system waiting queue, analyzing the standard samples, performing analysis result quality control and uploading an analysis file. The invention further discloses a biological information data analysis and result quality control automation system which comprises a data downloading unit, an information detection unit, an unanalyzed standard sample unit, a waiting queue unit, a biological information analysis unit, a quality control unit, an analysis file uploading unit and a backup unit.According to the invention, detection information can be automatically obtained after biological information analysis process management and biological information sequencing data downloading, qualified samples are added into a waiting queue, biological information cloud node resources occupied by unqualified sample analysis are eliminated, the analysis state is updated in time, analysis problemscan be found in time, correction is carried out in time, and the analysis result quality is controlled; unqualified samples can be analyzed and screened out, and standard samples with qualified analysis results automatically upload the analysis results.

Description

Technical field[0001]The invention relates to the technical field of comprehensive management based on cloud computing, in particular to an automated method and system for biological information data analysis and result quality control.Background technique[0002]With the rapid advancement of sequencing technology, gene sequencing institutions, medical research institutes, and biological companies have generated massive amounts of biological sequencing data. However, these original sequencing data cannot be used directly. Bioinformatics analysis technology is required to perform computational mining processing on these data to generate valuable scientific research information or related information about disease treatment drugs, as well as clear and easy-to-derive conclusions. .[0003]Bioinformatics is the storage and computational analysis of biological data in the research of life sciences using computers as the main research tool. Facing the massive data generated by high-throughput...

AI Technical Summary

Problems solved by technology

[0004] Bioinformatics analysis involves a variety of sequencing data. In the current technology, the analysis of bacterial sequencing data, fungal sequencing data, full-length transcriptome sequencing data with parameters and full-length transcriptome sequencing data without parameters is generally carried out on separate bioinformatics analysis platforms. To analyze all these data needs to build different analysis platforms on the computer, and each analysis platform involves multiple analysis software and programs, because the analysis software and programs are built into each analysis platform, resulting in analysis software and programs. There are problems of repeated installation and waste of resources in each analysis platform, and when the computer is used for data processing, unsuitable waste of resources will occupy the memory space of the computer and reduce its running speed, resulting in slow analysis process and low analysis efficiency. Moreover, users When conducting bioinformatics analysis, different sequencing data need to use different platforms, and the user experience is poor

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