Gene sequence reading method and reading system

Abstract

The present invention discloses a gene sequence reading method and reading system. The method comprises: determining a suitable error correction algorithm according to relevant information of an original gene sequence, and performing error correction on the original gene sequence by using the error correction algorithm, to obtain a to-be-processed gene sequence; blocking the to-be-processed gene sequence according to a preset process quantity and a total size of the to-be-processed gene sequence, to obtain multiple blocked gene sequences; and concurrently reading the blocked gene sequence. By applying the technical scheme of the present invention, memory consumption of a stand-alone machine can be reduced, and efficiency and accuracy of reading the gene sequence are greatly improved.

Description

technical field [0001] The invention relates to the technical field of biological information, in particular to a gene sequence reading method and a reading system. Background technique [0002] In the current gene sequencing process, there are some differences in the sequence errors generated by different sequencing platforms, mainly the following four types: base substitution (substitution) error, base insertion (insertion) error, base deletion ( deletion) errors and ambiguous bases (such as using N to indicate the possible 4 bases A, C, G, T). For example, the errors of the Illumina platform are mainly base substitution errors, and the errors of the RS platforms of Roche 454, Heliscope, Ion Torrent and PacificBioscience are mainly base insertion and deletion errors. From the algorithm basis of the error correction method, there are mainly three kinds of error correction methods currently used: 1) method based on k-spectrum; 2) method based on suffix tree / suffix array; 3)...

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Problems solved by technology

[0003] However, the existing software technologies are all aimed at specific sequencing platforms and some error types of gene sequencing sequences, and there is no software technology that can be applied to most platforms and solve various sequence errors better, so it is sometimes difficult Find the right algorithm for error correction

Read the measured data directly, and the existing error sequence will consume a lot of memory

[0004] Moreover, in the current process of reading gene sequences, serial reading of files is often used to read DNA data, which requires high memory requirements for stand-alone storage; in addition, although the Abyss algorithm realizes the de Bruijn graph Distributed builds, however, do not say anything about the entire parallel file reading method

[0005] It can be seen that the prior art sequence reading method has the problems of sequencing platform limitation and high memory consumption for storing DNA data files on a single machine, which needs to be improved

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