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Metagenome data analysis method

A metagenomics and analysis method technology, applied in sequence analysis, instrumentation, biostatistics, etc., can solve the problem of lightening, and achieve the effect of reducing pressure, improving data utilization, and reducing sequencing costs

Active Publication Date: 2022-02-08
QITAN TECH LTD CHENGDU
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  • Description
  • Claims
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Problems solved by technology

[0008] Therefore, the purpose of the present invention is to address the deficiencies of the prior art and provide a method for analyzing metagenomic data. The method provided by the present invention can well solve the above problems at the level of data analysis, and not only effectively avoid The problem of low data utilization caused by random insertion and deletion (indel) is eliminated, and at the same time, it has ultra-high sensitivity, and can accurately detect the species composition of microorganisms even under ultra-high host (host) background noise, and is effective The results of false positives are controlled, making the analysis results more accurate and efficient; at the same time, the method of the present invention reduces the pressure on the experimental technical level, does not require too much sequencing data, reduces the cost of sequencing, and fully utilizes the advantages of the third-generation sequencing data. Advantage

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Embodiment 1

[0089] Embodiment 1 uses the method analysis data of the present invention

[0090] 1. Four sets of metagenomic standards containing 0%, 30%, 50% and 90% of the human host ratio, each containing Enterococcus faecalis, Escherichia coli, Lactobacillus fermentum, Listeria monocytogenes, Salmonella enterica, Staphylococcus aureus, and the expected abundance of each bacteria in each standard is known, through the experimental library Preparation, using the third-generation nanopore sequencer model QNome-9604 for sequencing to obtain the original long-read sequencing data, the maximum read length of the data reaches 16Kb, and the average length is 7.8kb; use Porechop software and NanoFilt software to remove experimental constructs Linkers and barcode sequences added in the library process, filter low-quality read sequences below Q5 and length less than 100bp;

[0091] 2. For each read sequence in the data set of the sequence obtained in step 1, perform 20 sliding extractions (N=2...

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Abstract

The invention provides a metagenome data analysis method. The metagenome data analysis method comprises the following steps of: 1) preprocessing original data to obtain a data set with expected quality; 2) performing N times of K-mer sliding extraction on each read sequence in the data set in the step 1) to obtain N K-mer sequences; 3) classifying the K-mer sequences obtained by the same time of K-mer sliding extraction in all read sequences into a K-mer sequence subset to obtain N K-mer sequence subsets; 4) separately carrying out metagenome species analysis on each K-mer sequence subset obtained in the step 3) to obtain N data analysis results; and 5) merging the N data analysis results obtained in the step (4), and conducting analyzing to obtain information of various microorganisms in the metagenome. The method has ultrahigh sensitivity and can effectively control false positive results.

Description

technical field [0001] The invention belongs to the technical field of metagenomic analysis, and in particular relates to an analysis method of metagenomic data. More specifically, the present invention relates to an analysis method of metagenomic data based on three-generation sequencing. Background technique [0002] Metagenome, also known as microbial environmental genome, is the sum of the genetic material of all tiny organisms in the environment. Currently, it mainly refers to the sum of genomes of bacteria and fungi in environmental samples. Metagenomics (Metagenomics) is a research object that takes the genome of microbial populations in environmental samples as the research object, uses functional gene screening and / or sequencing analysis as the research method, and analyzes microbial diversity, population structure, evolutionary relationship, functional activity, and interaction. Collaborative relationship and relationship with the environment are new microbial rese...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B40/20G16B30/00
CPCG16B40/20G16B30/00
Inventor 郎继东孙继国
Owner QITAN TECH LTD CHENGDU
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