Data processing method of next-generation sequencing (NGS) data analysis platform (IMP)

Abstract

The invention discloses a data processing method of a next-generation sequencing (NGS) data analysis platform (IMP). The next-generation sequencing data analysis platform implements an entire next-generation sequencing processing process as a single step from inputting of short-reading long-sequences of an FASTQ file format to outputting of mutation detection of a standard VCF file format; at thesame time, the method also provides an option of outputting an intermediate result of sequence alignment in a standard SAM or BAM format; longer data searching and loading time required for I / O accessing of hard drives and SSDs can be avoided through massive memory accessing without using slow I / O to exchange data; hash table writing or reading, deletion of duplicated alignment records and mutation detection are all enabled to be faster; quick next-generation sequencing data analysis can be realized on the premise of not impacting analysis quality; and compared with speeds of existing schemes,a speed of the method is increased up to 20 times.

Description

technical field [0001] The invention relates to a data processing method of a next-generation sequencing data analysis platform. Background technique [0002] With the smooth implementation of the Human Genome Project and the rapid development of sequencing technology, the cost of sequencing has been significantly reduced, and the sequencing speed has been significantly improved. The sequencing cost of human whole genome sequencing has dropped to less than $1000, and the amount of DNA sequence data has grown exponentially. . How to quickly use and express these data, and then analyze and explain potential problems in gene sequences, and discover information beneficial to human beings from massive data has become an urgent problem to be solved. The sequence data generated by human whole-genome sequencing (WGS) is widely used, and the continuous demand for rapid analysis and processing of massive sequence data makes data analysis a new technical bottleneck. The clinical appli...

AI Technical Summary

Problems solved by technology

The advantage is that you don’t need to maintain your own hardware. The disadvantage is that you need to transmit and store massive amounts of genetic data over the network. At the same time, how to protect confidentiality and security of genetic data has become a major challenge for cloud platform solutions.

Private cloud solutions, such as building small server workstations, require specialized technicians to maintain and manage them, and the hardware and maintenance costs are high

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