Comparison gene sequencing data compression method and system and computer readable medium

Abstract

The invention discloses a comparison gene sequencing data compression method and system and a computer readable medium. The compression method comprises the steps that initial gene character string CS0 is selected for each read R in a gene sequencing data sample; a short string K-mer with the length being k is generated according to the sequence, the short string K-mer and a reference-based genomeare sequentially compared so as to obtain the adjacent predicting characters c of the short string K-mer in the plus strand or the minus strand of the reference-based genome, and a predicting character set PS composed of all predicting characters c is obtained; invertible computation is conducted through an invertible function after the Lr-k locus of the read R and the predicting character set PSare encoded; and the plus / minus strand type d of the read R, CS0 and the invertible computation result serve as three data streams to be compressed and output. The method has the advantages of low compression rate, short compression time and stable compression property, does not need to conduct precise comparison on the gene data, and has the high computation efficiency, and the higher the precision degree is, the lower the compression rate is.

Description

technical field [0001] The present invention relates to gene sequencing and data compression technology, in particular to a comparative gene sequencing data compression method, system and computer readable medium. Background technique [0002] In recent years, with the continuous advancement of Next Generation Sequence (NGS), gene sequencing has become faster and cheaper, and gene sequencing technology has been used in a wider range of biological, medical, health, criminal investigation, agriculture, etc. Many fields have been promoted and applied, resulting in the explosive growth of the amount of raw data generated by gene sequencing at a rate of 3 to 5 times or even faster every year. Moreover, the data of each gene sequencing sample is very large, for example, the 55x whole genome sequencing data of a person is about 400GB. Therefore, the storage, management, retrieval and transmission of massive genetic test data face technical and cost challenges. [0003] Data compr...

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Problems solved by technology

[0009] According to the comparative research results of the researchers on the existing gene sequencing data compression methods, whether it is a general compression algorithm, a compression algorithm without a reference genome, or a compression algorithm with a reference genome, there are problems as follows: 1. The compression rate has further There is room for decline; 2. When a relatively good compression rate is obtained, the compression / decompression time of the algorithm is relatively long, and the time cost becomes a new problem

However, for a compression algorithm with a reference genome, the selection of the reference genome will lead to the stability of the algorithm performance, that is, when processing the same target sample data, when different reference genomes are selected, the performance of the compression algorithm may be significantly different; while using the same The reference genome selection strategy, when dealing with the same kind of gene sequencing sample data, the performance of the compression algorithm may also have significant differences

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