Method for analyzing Granger causality among multiple florae based on pathogenic microorganism metagenome

Abstract

The invention discloses a pathogenic microorganism metagenome-based inter-flora Granger causality analysis method, and the method comprises the following steps: performing clustering analysis on acquired pathogenic microorganism metagenome data, dividing each strain, and calculating the species abundance of each strain at a corresponding disease development time node; and then establishing a timesequence of each group of variables for each time node and correcting, and finally performing Granger causality analysis on the corrected data to find out main pathogenic bacteria. Various bacteria are identified by utilizing a high-throughput sequencing platform, and then the causal action relationship among the bacteria is found out by combining a Granger causal analysis method, so that a rapididentification method is provided for finding out one or more pathogenic bacteria from a pathogenic microorganism sample, and clinicians are helped to carry out analysis and judgment more rapidly to realize clinical diagnosis.

Description

technical field [0001] The invention relates to the field of high-throughput sequencing and the field of analysis technology, in particular to a method for Granger causality analysis among various bacterial groups based on the metagenomic group of pathogenic microorganisms. Background technique [0002] Diagnosis of infected patients with unexplained fever, difficult and critical illnesses, and immunodeficiency has always been a difficult problem for clinicians. There are three common causes of infection: infection, rheumatic immune disease, and malignant tumors. These patients generally have pathogens that are difficult to diagnose and are numerous. For complex problems, because the pathogen cannot be identified, the treatment is mostly limited to empirical anti-infection, and it cannot be precisely treated. Therefore, accurate and early identification of pathogens and targeted anti-infective treatment are crucial to the prognosis of such patients. [0003] Metagenomics (M...

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Problems solved by technology

[0002] Diagnosis of infected patients with unexplained fever, difficult and critical illnesses, and immunodeficiency has always been a difficult problem for clinicians. There are three common causes of infection: infection, rheumatic immune disease, and malignant tumors. These patients generally have pathogens that are difficult to diagnose and are numerous. Complex problems, because the pathogen cannot be clearly defined, the treatment is mostly limited to empirical anti-infection, and it cannot be precisely treated

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