Gene sequencing data compression method, system and computer readable medium

Abstract

The invention discloses a gene sequencing data compression method, system and computer-readable medium. The compression method includes traversing and obtaining read sequences with a read length of Lr, generating a short string K-mer for each read sequence, and selecting the original gene string CS 0 And determine the positive and negative chain type d, obtain the predicted character c of each short string K-mer through the predicted data model P1 to obtain the predicted character set PS, encode the Lr-k bit of the read sequence R, and the predicted character set PS through a reversible function Perform reversible operation; the positive and negative chain type d, CS of the read sequence R 0 And reversible operation results are compressed and output. The present invention has the advantages of low compression rate, short compression time, and stable compression performance. It does not require precise comparison of genetic data and has high calculation efficiency. The more repeated strings in , the lower the compression ratio.

Description

technical field [0001] The invention relates to gene sequencing and data compression technology, in particular to a 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 compression is one of the...

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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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