Enteric microorganism information analysis method and system

Abstract

The invention discloses an enteric microorganism information analysis method and system. The method comprises the steps of splitting and filtering offline sample data after sequencing to obtain filtered sample sequences; performing clustering comparison and species annotation classification on the filtered sample sequences; performing spectral analysis on a species annotation classification result; and performing automatic interpretation on a spectral analysis result according to flora functions and a disease correlation database, and automatically submitting an automatic interpretation result and the spectral analysis result to a visual platform for performing visual display and auditing. The system comprises a splitting and filtering module, a clustering comparison and classification module, a spectral analysis module, and an automatic interpretation and visual display module. The method and the system have the advantages of convenient process and batch operations, small artificial interpretation workload, intuitiveness and convenience, and can be widely applied to the field of biological information analysis.

Description

Technical field [0001] The invention relates to the field of biological information analysis, in particular to an intestinal microbial information analysis method and system. Background technique [0002] With the development of the Human Microbiome Project (HMP) and Human Intestinal Metagenomics (MetaHIT) projects, more and more studies have shown that the human body’s physiological metabolism and growth are not only controlled by its own genes, but there are many phenomena, such as diseases Susceptibility, drug reaction, etc. cannot all be explained by differences in human genes. This is because a large number of microorganisms live in the human body, and their composition and activities are closely related to human growth and development, birth, aging, sickness and death. The metagenome, also known as "metagenome", refers to the sum of the genetic material of all tiny organisms in a certain environment. The metagenomic sequencing method takes the entire microbial community i...

AI Technical Summary

Problems solved by technology

[0004] 1) It needs to be manually operated step by step in the QIIME software, which is not suitable for process and batch operations;

[0005] 2) In the analysis results, the relevant information about the function of the bacteria and the association with the disease is not given, so that the interpreters need to read the literature to annotate the functions of the tested bacteria every time they issue a report, which increases the workload of manual interpretation ;

[0006] 3) Lack of a visual display platform, it is difficult to intuitively process and review the results, which is not intuitive and convenient enough

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