Analysis method for detecting microorganisms by using metagenome or metatranscriptome

Abstract

The invention discloses an analysis method for detecting microorganisms by using a metagenome or a metatranscriptome. The analysis method comprises the following steps: performing data quality controlon sequencing off-line data, and performing filtering to obtain high-quality data; performing assembly and double-end splicing (single end is not spliced) in a parallel manner, comparing the data obtained by assembly and splicing to a microorganism reference database based on a bwa algorithm, and identifying microorganism species and abundance information thereof in a sample; filtering low-quality results and then integrating analysis results. The method is wide in application range, various types of microorganisms can be detected, and the method is compatible with various mainstream sequencing platforms, and gives consideration to the characteristics of single-ended and double-ended sequencing data and long-read and short-read sequence data; and microorganism species and abundance thereof in a sample from various types of sequencing data can be accurately detected. The method provided by the invention can effectively reduce false positive, overcome the difficulty that most microorganisms cannot be cultured, and accurately, quickly and comprehensively detect microorganisms in various types of samples.

Description

technical field [0001] The invention relates to the technical field of biological detection, and more specifically, relates to an analysis method for detecting microorganisms using a metagenome or a metatranscriptome. Background technique [0002] Microorganisms widely exist in nature, most of which are single-celled organisms. Microorganisms usually include viruses, bacteria, fungi, protozoa, and some algae. The vast majority of microorganisms are beneficial to humans, animals and plants, and are beneficial to industry, agriculture, and pharmaceutical production, but they also have a side that is harmful to humans, such as mildew and deterioration of food and industrial and agricultural products, and contamination of animal and plant cells or pure cultures of microorganisms in laboratories. , the pollution of miscellaneous bacteria in the fermentation industry; animals and plants are infected by pathogenic microorganisms and suffer from various infectious diseases, etc. B...

AI Technical Summary

Problems solved by technology

The sequences of some microorganisms have multiple repetitive sequences, and the sequence analysis after a single assembly method cannot avoid the occurrence of assembly errors

[0011] In summary, there are still bottlenecks in the data analysis of current metagenomics, and the specific performance is as follows: (1) High-throughput metagenomics detection is sensitive, but a single assembly method often causes too many false positives in the detection results and poor specificity, It cannot meet the needs of identification methods with high specificity requirements; (2) The existing metagenomic data analysis methods have poor data compatibility and cannot be generally applied to various sequencing types; (3) The existing metagenomic sequencing data analysis methods are still difficult to take into account On the basis of different sequencing data types, the accuracy of the identification results is guaranteed; (4) The existing metagenomic sequencing data analysis methods are still difficult to greatly speed up the analysis speed and shorten the analysis time on the basis of ensuring the accuracy of the identification results

The above problems seriously restrict the development and application of metagenomics in the detection of microorganisms.

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