Method for analyzing microbial population function by using metagenome data

Abstract

The invention provides a method for analyzing a microbial population function by using metagenome data. The method comprises the following steps: collecting all known microbial species, gene and function information, and integrating the information as a reference database; sequencing the metagenome of the to-be-tested microbial specifies, controlling the sequencing data quality, computing speciesabundance and gene abundance, analyzing the composition difference of microbes among different samples and gene level difference; annotating the gene function, clustering the genes with the same function to obtain a function module, performing adduction computation on related abundance of all non-redundancy genes in various function modules to obtain abundance values of all function modules, performing difference comparison analysis or overall evaluation on the functions of the to-be-tested sample microbes. Through the method provided by the invention, the step of respectively comparing the splicing data, the assembling data, the predicting data and the sequencing data with the single function database is saved, the time is saved, the utilization efficiency of the sequencing data is improved, and the method can be used for analyzing high-throughput microbe whole-genome sequencing data and screening the function microbe.

Description

technical field [0001] The present invention relates to the field of bioinformatics, in particular to a method for analyzing the functions of microbial populations using metagenomic data, which can save analysis steps and time and improve the utilization rate of sequencing data. Background technique [0002] With the continuous development of high-throughput sequencing technology, people have been able to explore complex biological functions from the genome level, which has given us a deeper understanding of the organism itself and disease-related research. More and more studies have found that there is a mutually beneficial balance between the microbial flora and the health of the host. Among them, the microbial flora can help the host ferment undigested food, participate in energy metabolism and nutrient absorption, provide the host with various trace elements, essential amino acids, and some antibacterial polypeptides, and decompose some toxins or harmful substances in th...

AI Technical Summary

Problems solved by technology

The sequencing and analysis of such a large sample size requires a lot of human and economic costs, which increases the difficulty of establishing such an integrated database.

[0009] Third, in terms of data utilization, the utilization rate of reads by conventional methods is too low to fully reflect the real state of the research object

Specifically, in the process of assembly and splicing of sequencing data, if there is no overlapping sequence between the reads, the splicing cannot be performed; if the splicing can be completed, if the resulting sequence is less than 500bp, it will be removed; and some obtained sequences are higher than 500bp , but cannot be predicted to have ORFs, these fragments are then removed

This process will cause a large amount of sequencing data to be lost or removed, which will lead to the situation that microbial species and functional information annotations are greatly missing compared with the actual situation.

Especially in studies with small sample sizes (20 samples or less), this loss of data will cause large errors and unreliability in the research results

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