Enteric microorganism detection data analysis method, automatic interpretation system and medium

Abstract

The invention discloses an enteric microorganism detection data analysis method, an automatic interpretation system and a medium. The method comprises the following steps: acquiring enteric microorganism sequencing data of a user; extracting sample data from the sequencing data, and filtering the sample data; performing species annotation classification and function annotation classification on the filtered sequencing data to obtain an annotation result; performing conventional analysis on the annotation result, wherein the conventional analysis comprises diversity analysis and probiotics content and pathogenic bacteria content analysis; and obtaining a flora function and disease association database, and based on the annotation result, automatically interpreting the conventional analysisresult according to the flora function and disease association database. According to the method, analysis and interpretation can be automatically executed, so that the working pressure is reduced, the generated analysis results are diversified in form and good in readability, the requirements of users are met, process and batch operations are conveniently carried out, and the workload of manual interpretation is small, visual and convenient.

Description

technical field [0001] The invention relates to the technical field of biological information analysis, in particular to a data analysis method for intestinal microorganism detection, an automatic interpretation system and a medium. 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 growth and development, nutritional metabolism and health levels of the human body are not only controlled by their own genes (host genome), It is also influenced by the commensal microorganisms in the human body, especially the intestinal flora. There are many diseases and conditions, such as colorectal cancer, obesity, diabetes, autism, drug reactions, etc., that are closely related to the gut microbiota. [0003] The emergence of large-scale sequencing technology provides a powerful tool for the study of intestinal flora. At present, there are two main methods...

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Problems solved by technology

[0006] In view of the above technical problems, the purpose of the present invention is to provide a data analysis method for intestinal microorganism detection, an automatic interpretation system and a medium, so as to solve the problem that the existing intestinal microorganism information analysis technology is not suitable for process and batch operation or analysis results incomplete problem

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