Cloud computing-based method for quality control and management of gene sequence data

Abstract

The invention relates to a cloud computing-based method for quality control and management of gene sequence data. The method includes sample clinical information management, experimental data management, data whole process quality control and analysis result management. Testing items of the sample clinical information management includes genomic analysis and transcriptomics analysis, and the genomic analysis includes whole genome sequencing, whole exome sequencing and whole exome sequencing; the transcriptomic analysis includes gene fusion, variable splicing and differential expression analysis. Experimental links are closely connected with analytical links, an analyst can comprehensively understand clinical information, sample information and experimental results, subsequent analysis is facilitated, the accuracy of the analysis result is improved, and the method can help experimenters to understand the quality of sequencing data and thus reflect on shortcomings in the experimental process, the experimental quality is thus improved, and the need of practical use can be applied well.

Description

technical field [0001] The invention belongs to the technical field of genetic engineering, and in particular relates to a method for quality control and management of gene sequence data based on cloud computing. Background technique [0002] With the maturity and improvement of next-generation sequencing technology, genome sequencing has been widely used in the field of tumor research. Tumor samples can be divided into fresh frozen tissue, paraffin section tissue, blood and saliva according to the sampling source. Genome sequencing can be divided into whole genome sequencing, exome sequencing and target region capture sequencing according to the sequencing type. Whole Genome Sequencing (WGS) is the sequencing of the whole genome of different individuals or populations of humans. By comparing with the human reference genome, a wealth of genome-wide variation information is obtained, and biological information is carried out at the individual or population level. analyze. W...

AI Technical Summary

Problems solved by technology

Separating the sample processing from the experiment link and the analysis link into two links, the experimenters do not understand the data quality, and cannot find deficiencies from the sequencing data. The analysts do not understand the experimental process and sample information, and cannot grasp all the information of the data. Subsequent analysis is bound to be unfavorable, so this process is not beneficial to both parties and has great limitations

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