Data management system for gene data multi-dimensional annotation

Abstract

The invention relates to a data management system for gene data multi-dimensional annotation, which comprises an experiment database, a clinical information annotation module, an experiment data annotation module, a data quality control annotation module, an analysis result annotation module and a follow-up information annotation module. The clinical information annotation module manages the sample clinical information and transmits the sample clinical information to the experimental data annotation module. The experimental data annotation module analyzes and processes the data and transmits the data to the data quality control annotation module. The data quality control annotation module performs full flow quality control on the data, analyzes the data and transmits the data to the analysis result annotation module; and the analysis result annotation module annotates the data and transmits the data to the experiment database for storage. According to the data management system for gene data multi-dimensional annotation, the clinical information record is standardized, the information record is more complete, the problem of the current clinical information time breakpoint is solved, the data can be standardized and managed, the foundation is laid for subsequent research, the analysis result interpretation has more sufficient significance, and all data is effectively managed.

Description

technical field [0001] The invention belongs to the technical field of genetic engineering, and in particular relates to a data management system for multi-dimensional annotation of genetic data. Background technique [0002] With the maturity and improvement of next-generation sequencing technology, gene sequencing has been widely used in the field of tumor research. Tumor sample gene sequencing can be divided into two categories: genome sequencing and transcriptome sequencing. Genome sequencing starts from basic DNA and finds gene mutations based on the reference genome, so as to further study the role and impact of mutations on tumors. Transcriptome sequencing starts from RNA, from the level of gene expression, to study abnormally expressed genes, so as to further study the relationship between abnormally expressed genes and tumors. Although the starting point of the research is different, the purpose is the same. They are all looking for gene mutations related to tumors...

AI Technical Summary

Problems solved by technology

Due to a variety of factors, the clinical information compiled by doctors varies, and most of the time the content is not organized and complete enough to provide all the clinical information required by analysts

In addition, the clinical information provided by the doctor is only limited to the clinical information before the sample is obtained, and the clinical performance of the patient is not fed back to the analyst in real time, resulting in time breaks in the information and insufficient completeness

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