Alignment gene sequencing data compression method, system and computer readable medium

Abstract

The invention discloses a comparison type gene sequencing data compression method, system and computer-readable medium. The compression method selects the original gene string CS for each read sequence R in the gene sequencing data sample. 0 , generate a short string K-mer of length k in sequence, compare the short string K-mer with the reference genome in turn to obtain the predicted character c of its adjacent position in the positive or negative strand of the reference genome, and obtain all predictions The predicted character set PS composed of character c; the Lr-k bit of the read sequence R and the predicted character set PS are encoded and then reversible operations are performed through a reversible function; the positive and negative chain types d, CS of the read sequence R 0 And the reversible operation results are compressed and output as three data streams. The present invention has the advantages of low compression rate, short compression time, and stable compression performance, does not require precise comparison of genetic data, and has high calculation efficiency. The higher the comparison accuracy, the lower the compression rate.

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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