WO2020147557A1

WO2020147557A1 - Method and device for processing intestinal microorganism sequencing data, storage medium, and processor

Info

Publication number: WO2020147557A1
Application number: PCT/CN2019/129426
Authority: WO
Inventors: 张东亚; 夏慧华; 张陈陈; 刘洋荧; 薛文斌
Original assignee: 深圳碳云智能数字生命健康管理有限公司; 深圳数字生命研究院
Priority date: 2019-01-15
Filing date: 2019-12-27
Publication date: 2020-07-23
Also published as: CN111161795A

Abstract

A method and device for processing intestinal microorganism sequencing data, a processor, and a memory. The method comprises: obtaining sequencing data of intestinal microbial flora of a target object (S102); annotating the sequencing data according to a standard gene database to obtain an annotation result (S104); evaluating the intestinal microbial flora of the target object according to the annotation result to obtain functional information of intestinal microorganisms of the target object (S106). A relatively comprehensive and diverse analysis of intestinal microorganisms of an individual is implemented by using a metagenome gene analysis method, and the method can better satisfy the needs of personalized analysis compared with existing methods.

Description

Intestinal microbial sequencing data processing method, device, storage medium and processor

Technical field

This application relates to the field of gene sequencing data analysis, and in particular to a method, device, storage medium and processor for processing intestinal microbial sequencing data.

Background technique

With the development of the Human Microbiome Project (HMP) and Human Intestinal Metagenomics (MateHIT) 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 disease The 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.

16S rRNA (Small subunit ribosomal RNA) gene is the most commonly used molecular marker (Biomarker) in the study of phylogenetic classification of prokaryotic microorganisms, and is widely used in microbial ecology research. In recent years, with the continuous progress of high-throughput sequencing technology and data analysis methods, a large number of studies based on 16S rRNA genes have led to rapid development of microbial ecology research, and it has also been widely used in intestinal microbial research. However, The 16S rRNA gene data analysis method also has many problems, such as horizontal gene transfer, multi-copy heterogeneity, differences in gene amplification efficiency, and the choice of data analysis methods. These problems affect the composition and diversity analysis of microbial communities. Time accuracy.

Metagenome, also known as "metagenome", refers to the sum of the genetic material of all tiny organisms in a specific environment. The metagenomic sequencing method takes the entire microbial community in a specific environment as the research object. It does not require the isolation and culture of microorganisms, but extracts the total DNA of environmental microorganisms for research, and uses a new generation of high-throughput sequencing technology to analyze the DNA of environmental microbial samples Direct sequencing. Due to the superiority of gene metagenomics in studying microbial ecology, more and more studies have adopted metagenomic gene analysis methods to study microbial ecology.

However, at present, only the relative abundance of genes is analyzed by using metagenomic gene analysis methods, and the analysis results are single, so the information provided is limited and cannot meet the needs of personalized analysis.

Summary of the invention

This application provides an intestinal microbial sequencing data processing method, device, storage medium and processor to solve the problem that the analysis result of the metagenomic gene data analysis method in related technologies is single, and the information provided is limited, which cannot meet the needs of personalized analysis The problem.

According to one aspect of the present application, a method for processing intestinal microbial sequencing data is provided. The method includes: obtaining the sequencing data of the gut microbial flora of the target object; annotating the sequencing data according to the standard gene database to obtain the annotation result; according to the annotation result, analyzing the gut microbial flora of the target object Perform evaluation to obtain functional information of the intestinal microbes of the target object.

According to another aspect of the present application, a device for processing intestinal microbial sequencing data is provided. The device includes: a first acquisition module, configured to acquire sequencing data of the gut microbial flora of the target object; an annotation module, configured to annotate the sequencing data according to a standard gene database to obtain an annotation result; and a second acquisition module, It is configured to evaluate the intestinal microbial flora of the target object according to the annotation result, and obtain functional information of the intestinal microbe of the target object.

According to another aspect of the present application, a storage medium is provided, the storage medium includes a stored program, wherein the program executes the intestinal microbial sequencing data processing method described in any one of the above.

According to another aspect of the present application, there is provided a processor for running a program, wherein the intestinal microbial sequencing data processing method described in any one of the above is executed when the program is running.

Through this application, the following steps are adopted: acquiring the sequencing data of the intestinal microbial flora of the target object; annotating the sequencing data according to the standard gene database to obtain the annotation result; according to the annotation result, analyzing the intestine of the target object The tract microbial flora is evaluated to obtain functional information of the intestinal microbes of the target object. Compared with the related prior art, the above-mentioned method of the present application can not only analyze the relative abundance of genes, but also can analyze the status of the intestinal microbial flora and flora of the target object based on the relative abundance information of each gene. Evaluation, and then obtain relatively complete information about the function of the gut microbes of the target object. That is, the information provided by the above method of the present application is relatively more comprehensive and diversified, and can meet individual needs.

BRIEF DESCRIPTION

The drawings forming a part of the application are used to provide a further understanding of the application. The schematic embodiments and descriptions of the application are used to explain the application, and do not constitute an undue limitation on the application. In the drawings:

Fig. 1 is a first flow chart of a method for processing intestinal microbial sequencing data according to an embodiment of the present application;

2 is a second flowchart of a method for processing intestinal microbial sequencing data according to an embodiment of the present application;

Fig. 3 is a schematic diagram of a processing device for intestinal microbial sequencing data provided according to an embodiment of the present application;

Figure 4 is a schematic diagram of a gene abundance file in an embodiment of the present application;

Figure 5 is a schematic diagram of an IGC KO annotation file in an embodiment of the present application;

Fig. 6 is a schematic diagram of the relative abundance file of KO in an embodiment of the present application.

detailed description

It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other if there is no conflict. The application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of this application, but not all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work should fall within the protection scope of this application.

It should be noted that the terms “first” and “second” in the description and claims of the present application and the above drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances for the purposes of the embodiments of the present application described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, processes, methods, systems, products or devices that contain a series of steps or units need not be limited to those clearly listed Those steps or units may instead include other steps or units that are not explicitly listed or inherent to these processes, methods, products, or equipment.

For ease of description, some terms or terms involved in the embodiments of this application are described below:

Standard gene database, that is, a database that contains a large number of gene sequences and the genes corresponding to each gene sequence and the functional information related to the gene. Standard gene databases include but are not limited to IGC (Integrated Gene Catalog), KEGG (Kyoto Encyclopedia of Genes and Genomes) , GO (Gene Ontology), EggNOG: (evolutionary genealogy of genes: Non-supervised Orthologous Groups), CAZy (carbohydrate-active enzymes database), ARDB (Antibiotic Resistance Genes Database) and other databases.

Target gene: refers to the specific gene of the microorganism to which the specific gene only exists, or the sequence of the specific gene only corresponds to the sequence of the species after artificial correction.

Note: The sequence information to be obtained will be compared in the standard gene database to obtain the gene corresponding to each sequence information, as well as the function and biological source information of the gene.

Antibiotic resistance genes refer to genes that make bacteria resistant to antibiotics. Such genes are often produced through genetic mutations, that is, when humans use antibiotics to kill bacteria, they will induce bacteria to evolve resistance genes and transfer and spread in the bacterial community.

KEGG, referred to as the Kyoto Genome Encyclopedia, contains many databases. For the study of gene functions, the KEGG orthology database is the most basic database.

KEGG Orthology is abbreviated as KO. For each gene with a known function, all genes that are homologous to it are grouped into one category, that is, each KO is assigned a K number. Use the function of this gene as the function of this KO. Based on the assumption that homologous genes have similar functions, the function of each gene has been expanded. For a gene whose function is clearly studied in a species, search for the homologous genes of the gene in different species, and compare these homologous genes. A gene is defined as an orthology, and the function of the gene is used as the function of the orthology; in this way, the research on the gene function of different species can be used to provide a comprehensive database for the study of gene function.

According to an embodiment of the present application, a method for processing intestinal microbial sequencing data is provided.

Fig. 1 is a first flowchart of a method for processing intestinal microbial sequencing data according to an embodiment of the present application. As shown in Figure 1, the method includes the following steps:

Step S102: Obtain sequencing data of the intestinal microflora of the target object.

Step S104: Annotate the sequencing data according to the standard gene database to obtain an annotation result.

Step S106: According to the annotation result, evaluate the intestinal microbiota of the target object to obtain functional information of the intestinal microbe of the target object.

The method for processing intestinal microbial sequencing data provided by the embodiments of the present application obtains the sequencing data of the intestinal microbial flora of the target object; annotates the sequencing data according to the standard gene database to obtain the annotation result; according to the annotation result, the target object The intestinal microbial flora of the target object is evaluated to obtain functional information of the intestinal microbes of the target object. That is, the sequencing data is annotated through the standard gene database, and the intestinal microbial flora of the target object is evaluated based on the annotation results to obtain the functional information of the intestinal microbes of the target object, and then the intestinal microbial flora can be analyzed. And to effectively analyze the status of the flora.

Therefore, compared with related technologies, the above-mentioned method of the present application can not only analyze the relative abundance of genes, but also analyze the status of the intestinal microbial flora and flora of the target object based on the relative abundance information of each gene. Evaluation, and then obtain relatively complete information about the function of the gut microbes of the target object. That is, the information provided by the above method of the present application is relatively more comprehensive and diversified, and can meet individual needs.

It should be noted that: the functional information of the gut microbes of the target object obtained above includes the functional genes of the gut microbes and the relative abundance of each functional gene. Among them, the relative abundance of functional genes is related to the same function in the sequencing data. The ratio of the sum of the relative abundance of genes to the sum of the relative abundances of related genes of each function in the sequencing data, and the relative abundances of related genes belonging to the same function are obtained according to the annotation results.

The above-mentioned "functional gene" refers to a collection of genes related to a specific biological function, where the number of genes may be one or more, depending on the specific biological function. The above-mentioned "sum of the relative abundance of genes related to each function" refers to the sum of the relative abundances of all function-related genes included in the sequencing data.

Further, after the functional information of the gut microbes of the target object is obtained, the method for processing gut microbial sequencing data provided in the embodiments of the present application further includes: performing performance analysis on the gut microbes of the target object based on the function information. At least one of the following is involved: antibiotic resistance gene analysis and intestinal function gene analysis.

That is, the method for processing gut microbial sequencing data provided by the embodiments of the present application, after obtaining the functional information of the gut microbes of the target object, analyzes the antibiotic resistance gene of the gut microbes of the target object based on the functional information. And/or performance analysis such as intestinal functional gene analysis, realizes the comprehensive and multiple analysis of individual intestinal microbes, and meets the technical effects of individual analysis requirements, thereby solving the single, single, and unique analysis result in the existing technology. The information is limited and cannot meet the technical problems of individualized analysis needs.

In view of the above-mentioned performance analysis involving the analysis of antibiotic resistance genes, the performance analysis of the gut microbes of the target object based on the functional information can be achieved through the following steps: calculate the antibiotic resistance index of the gut microbes of the target object and determine the antibiotic resistance The position of the sex index in the reference population, where the relative abundance of antibiotic resistance genes is used as the antibiotic resistance index of the antibiotic resistance.

Among them, in an optional example, the antibiotic resistance index is calculated as follows: calculate the sum of the relative abundance of the same antibiotic resistance gene of the gut microbes of the target object; compare the relative abundance of the same antibiotic resistance gene The sum of degrees is divided by the sum of the relative abundances of all antibiotic resistance genes to obtain the relative abundance of the antibiotic resistance genes.

Examples for "Analysis of Antibiotic Resistance Genes of the Intestinal Microbes of Target Objects":

First, the antibiotic resistance index of each antibiotic of the intestinal microbe of the target object is calculated.

Second, determine the position of the antibiotic resistance index of each antibiotic in the reference population. Taking erythromycin as an example, the erythromycin resistance index of the reference population (such as 100, 200, 300, 1000 or more people ( For example, the erythromycin resistance index of the intestinal microbial test results of healthy people) are sorted from small to large to determine the number of people whose erythromycin resistance index in the reference population is less than that of the target object ( i _a ), determine the position of the erythromycin resistance index of the target object in the reference population by calculating the ratio of i _a to the total number of people in the reference population (s _a )

In some predetermined test criteria, for example, if (1) (e.g.: 0) ≤c _a <b (e.g.: 0.25), gut microflora is considered a target object in a relatively erythromycin resistance index low; if (2) (e.g.: 0.25) ≤c _a <c (e.g.: 0.75), gut microflora is considered a target object at the middle level erythromycin resistance index; if (3) (e.g. : 0.75) ≤c _a <d (For example: 1), that the gut microflora of erythromycin resistance index of the target object at a high level.

In addition, the performance analysis of the gut microbes of the target object based on the function information may also include: determining the antibiotic resistance of the gut microbes of the target object based on the antibiotic resistance index of the target object and the position of the antibiotic resistance index in the reference population Resistance score, its antibiotic resistance score can be calculated as follows:

In the case where the antibiotic resistance index of the intestinal microflora of the target object is at a low level, the antibiotic resistance score = the first parameter (for example: 80) * antibiotic resistance index + the second parameter (for example: 40);

In the case that the antibiotic resistance index of the intestinal microflora of the target object is at a medium level, the antibiotic resistance score = the third parameter (for example: 40) * antibiotic resistance index + the fourth parameter (for example: 50);

In the case where the antibiotic resistance index of the intestinal microflora of the target object is at a high level, the antibiotic resistance score=fifth parameter (for example: 80)*antibiotic resistance index+sixth parameter (for example: 20).

It should be noted that the parameter data such as the first parameter, the second parameter, the third parameter, the fourth parameter, the fifth parameter and the sixth parameter in the above-mentioned preset test standards can be adaptively replaced based on the application scenario. No specific restrictions.

It should also be noted that antibiotic resistance genes are genes related to antibiotic resistance, and the resistance of each antibiotic is related to more than one gene. In the above-mentioned "Analysis of Antibiotic Resistance Genes of Intestinal Microbes of Target Objects", the following table lists 16 antibiotics and their corresponding partial gene IDs (numbers). Each gene ID corresponds to a gene sequence. See the table for details 1.

Table 1 Types of antibiotics

It should be noted that the 16 antibiotics and the genes related to each antibiotic in the above table are only examples. In the specific implementation process, one or more of them can be selected as needed, and other related genes can also be selected.

In view of the above-mentioned performance analysis involving intestinal function gene analysis, the performance analysis of the gut microbes of the target object based on the function information can be implemented through the following steps: calculate the gut function index of the gut microbes of the target object and determine the intestine The position of the functional index in the reference population, where, in an optional example, the sum of the relative abundance of functional genes belonging to the same function is used as the intestinal function index of the intestinal function.

An example of "Analysis of Intestinal Function Genes of Intestinal Microbes of Target Objects":

First, calculate the intestinal function index for each function of the gut microbe of the target object, that is, the sum of the relative abundance of functional genes that belong to the same function as the intestinal function index corresponding to the function.

Secondly, determine the position of the intestinal function index corresponding to each function in the reference population. Taking energy metabolism capacity as an example, the intestinal function index of the intestinal energy metabolism capacity of the reference population (for example, 100, 200, 300, 1000 or More individual groups (such as healthy people) in the intestinal microbial test results in the energy metabolism capacity of the intestinal function index) are sorted from small to large, and determine that the intestinal function index in the reference population is less than the target object’s intestinal energy metabolism capacity The number of people with intestinal function index (i _o ), by calculating the ratio of i _o to the total number of people in the reference population (s _o ), determine the position of the target object’s intestinal function index in the reference population

Taking a certain preset test standard as an example, if (1) (for example: 0) ≤ c _o <b (for example: 0.25), the intestinal function index of the target object's intestinal energy metabolism ability is considered to be at a low level; If (2) (for example: 0.25)≤c _o <c (for example: 0.75), the intestinal function index of the intestinal energy metabolism capacity of the target object is considered to be at a medium level. If (3) (for example: 0.75) ≤ c _o <d (for example: 1), the intestinal function index of the intestinal energy metabolism capacity of the target object is considered to be at a higher level.

In addition, the performance analysis of the gut microbes of the target object based on the function information may also include: determining the gut microbes of the target object based on the gut function index of the target object and the position of the gut function index in the reference population. The score of tract function, the score of intestinal function can be calculated as follows:

In the case where the intestinal function index of the intestinal microflora of the target object is at a low level, the intestinal function score = the seventh parameter (for example: 80) * the intestinal function index + the eighth parameter (for example: 40);

When the intestinal function index of the intestinal microflora of the target object is at a moderate level, the intestinal function score = the ninth parameter (for example: 40) * the intestinal function index + the tenth parameter (for example: 50);

When the intestinal function index of the intestinal microflora of the target object is at a high level, the intestinal function score = the eleventh parameter (for example: 80) * the intestinal function index + the twelfth parameter (for example: 20 ).

It should be noted that: the seventh parameter, eighth parameter, ninth parameter, tenth parameter, eleventh parameter, and twelfth parameter in the above-mentioned preset test standards can be adaptively replaced based on application scenarios. This application does not make specific restrictions.

It should also be noted that KEGG Orthology is abbreviated as KO. For each gene with a known function, all genes homologous to it are classified into one category, that is, each KO is assigned a K number. Use the function of this gene as the function of this KO. Based on the hypothesis that homologous genes have similar functions, the function of each gene is expanded. For a gene that has a clear function in a species, search for the homologous genes of the gene in different species, and compare these homologous genes. A gene is defined as an orthology, and the function of the gene is used as the function of the orthology; in this way, the research on the gene function of different species can be used to provide a comprehensive database for the study of gene function. In the above "Intestinal function analysis of intestinal microbes of the target object", the following table lists 9 types of intestinal function analysis of intestinal functions and their corresponding partial KO sets and partial gene numbers corresponding to each KO (Gene ID), each gene number corresponds to a gene sequence, see Table 2 for details.

Table 2:

It should be noted that the 9 functions in the above table are only examples. In the specific implementation process, one or more of them can be selected according to needs, and other functions of interest and related genes can also be selected.

Further, FIG. 2 is a second flowchart of the method for processing intestinal microbial sequencing data according to an embodiment of the present application. As shown in Figure 2, the method for processing gut microbial sequencing data further includes the following steps:

Step S108a, when the performance analysis involves the analysis of antibiotic resistance genes, and the performance analysis of the gut microbes of the target object is performed based on the functional information, and the antibiotic resistance index of the gut microbes of the target object is calculated, the target The antibiotic resistance index of the gut microbes of the subject is imported into the database of the reference population for use in the next performance analysis step.

Step S108b, when the performance analysis involves the analysis of intestinal function genes, and the performance analysis of the intestinal microbes of the target object is performed based on the function information, the intestinal function index of the intestinal microbes of the target object is calculated, and the target The gut function index of the gut microbe of the subject is imported into the database of the reference population for use in the next performance analysis step.

Step S108c, when the sequencing data is annotated according to the standard gene database and the annotation result is obtained, the functional information of the target object (the functional genes of the gut microbes and the relative abundance of each functional gene) is imported into the database of the reference population for use In the next performance analysis step.

That is, after evaluating the gut microbial flora of each target object and obtaining functional information of the gut microbes of the target object, the evaluation results (functional information of the gut microbes of the target object, the functional information Including the functional genes of intestinal microbes and the relative abundance of each functional gene) are added to the database of the reference population, so that the reference range of each indicator can be updated in real time.

It should be noted that the "database of the reference population" in this application refers to a database that contains genetic information of gut microbes of multiple individuals. The genetic information of gut microbes includes functional genes of gut microbes (functional genes include antibiotics). Resistance genes, intestinal function genes, etc.), the relative abundance of each functional gene, antibiotic resistance index, intestinal function index, etc. The database may also include the volunteer’s gender, age, height, weight, living habits and Geographical information.

With the application of the method for processing gut microbial sequencing data in this application, more and more individuals are involved in the evaluation of the gut microbial flora, and the scale of the reference population stored in the database will continue to expand, thereby enabling the evaluation of the gut microbiota The results will become more and more accurate, and the reference value of intestinal microbial flora assessment based on intestinal microbial sequencing data processing methods will also increase.

Finally, when the number of reference populations stored in the database reaches a certain degree of abundance, the processing method of the gut microbial sequencing data of this application will also be based on the phenotypic characteristics of the individual to be tested (including gender, age, race, height, and weight). , Diet, living area, etc.) Select the corresponding reference population for specific intestinal microbial flora evaluation and analysis, thereby making the evaluation results more accurate and reliable.

It should also be noted that the target number of initial reference objects are initially stored in the database, and the database specifically records the phenotype information of each initial reference object (including gender, age, race, height, weight, diet, living area, etc.) ) And the evaluation information of the intestinal microbial flora (including antibiotic resistance gene analysis and intestinal functional gene analysis, etc., and can also further include the relative abundance information of each intestinal microbe).

In addition, it is also necessary to describe step S102 of the method for processing intestinal microbial sequencing data of this application:

In an optional example, obtaining the sequencing data of the gut microbial flora of the target object in step S102 can be achieved in the following manner:

Step A1: Perform genetic sequencing on the gut microbes of the target object to obtain the original sequencing data of the gut microbe flora of the target object (raw reads, usually in fasq format, the fastq file contains the quality information of all bases in the sequencing sequence) ；

Step A2, the quality of the original sequencing data is monitored, that is, the number of fuzzy bases N in the original sequencing data is greater than a preset value (the preset value can be 3, 4, 5 or more, specifically It can be reasonably adjusted according to actual application conditions) to remove reads, and to remove low-quality reads in the original sequencing data (for example, continuous bases with a quality value less than a specific value at the end of the reads can be removed according to the quality information in the reads. The specific value at can be 20, 25, 30 or other higher values, which can be adjusted reasonably according to actual needs; further, reads whose lengths are less than a specific length after excluding the above-mentioned consecutive bases are excluded. The length can be 30bp, 35bp or longer, which can be adjusted based on application scenarios. Existing software with the above functions can be used to remove low-quality reads, such as fastx software);

Step A3: Remove the host gene sequence from the original gene data to obtain the sequencing data of the gut microbial flora of the target object, where the host gene sequence is the gene sequence of the target object. The software used in this step can use soap software.

In addition, step S104 of the method for processing intestinal microbial sequencing data of this application needs to be described:

In an optional example, step S104 annotates the sequencing data according to the standard gene database, and obtaining the annotation result can be achieved in the following manner:

Step B1: Compare the reads (gene sequences) in the sequencing data to a standard gene database (for example: the integrated gene set IGC of the human gut microbial metagenomics), and determine the relative abundance of each gene sequence contained in the sequencing data ( For example: determine the gene abundance file corresponding to the sequencing data, where the file contains two columns of data, the data in the right column is the gene ID, and the data in the left column is the relative abundance of genes corresponding to the gene ID in turn);

Step B2, based on the annotation information of each gene sequence recorded in the standard gene database (annotation information includes: the resistance gene information corresponding to each antibiotic, which can form an antibiotic resistance gene annotation file), and each type contained in the sequencing data The relative abundance of the gene sequence, determine the relative abundance of each antibiotic resistance gene sequence contained in the sequencing data, (for example, determine the corresponding antibiotic resistance gene abundance file in the sequencing data, where the file contains two columns of data, The data in the left column of the file is the information of various antibiotic resistance genes, and the data in the right column is the relative abundance of the resistance genes on the left. The specific calculation method can be, for example, according to the gene abundance file of step B1 and step B2 Add the relative abundance of genes belonging to the same antibiotic resistance gene in the annotation file of antibiotic resistance genes generated in the sample, and then divide by the sum of the relative abundances of all antibiotic resistance genes in the sample. The result is this Relative abundance of antibiotic resistance genes);

Step B3, based on the annotation information of each gene sequence recorded in the standard gene database (the annotation information includes: the gene information corresponding to each biological function, wherein the number of genes corresponding to each biological function is one or more, Depending on the specific biological function, the number of genes also differs), and the relative abundance of each gene sequence contained in the sequencing data, determine the relative abundance of each biological function gene contained in the sequencing data, (e.g. : Determine the biological function gene abundance file corresponding to the sequencing data. The file contains two columns of data. The data in the left column of the file is the gene information corresponding to various biological functions, and the data in the right column is the various organisms on the left The relative abundance of the genes corresponding to the scientific function in turn, the specific calculation method can be, for example, adding the relative abundance of genes belonging to the same function, and then dividing the relative abundance of each function-related gene by The sum of the relative abundance of related genes corresponding to all the functions of the sample is the relative abundance of each functional gene).

Example one

(1) Obtain the sequencing data (reads) of the gut microbes of the target object A, and process the sequencing data as follows:

1.1 Filter reads (filtered data), the fastq format sequencing data read sequence contains more than 3 fuzzy bases "N".

1.2 Trim reads (remove low-quality reads), use Fastx software to remove the reads with a quality value less than 20 at the end of the sequencing data after 1.1 processing; then remove reads with a read length of less than 30bp after removing low-quality consecutive bases.

1.3 Remove host reads (remove host sequence), use soap software to compare reads and host sequence, and remove reads whose sequence can be compared to host sequence.

1.4 Mapped to IGC (comparison with IGC) and Function annotation (function annotation), use soap software to compare the processed reads sequence with the IGC sequence, and get the target's gut microbial gene abundance (gene abundance) File and IGC KO annotation file, the gene abundance file (as shown in Figure 4) consists of two columns of data, the left column is the gene ID, the right column is the gene abundance corresponding to the gene ID; the IGC KO annotation file (such as Figure 5) consists of two columns of data, the left column is the gene ID, and the right column is the KO information corresponding to the gene ID. The gene abundance (gene abundance) that can be annotated to the same KO is added and calculated, and then normalized to calculate the abundance (relative abundance) of each KO, and output the relative abundance file of each KO (Figure 6) As shown), the file consists of two columns of data, the left column is the KO number (each KO number corresponds to one KO related information), and the right column is the relative abundance value of the KO corresponding to the KO number. That is, according to the input gene abundance file and KO annotation file, the relative abundance of genes belonging to the same KO is added, and then divided by the sum of all KO gene abundances in the sample for normalization, and the result is The relative abundance of KO.

(2) Analysis of intestinal microbial function

2.1 Analysis of antibiotic resistance genes

2.1.1 Antibiotic resistance index (relative abundance of antibiotic resistance genes) analysis

This antibiotic resistance index analysis analyzes the resistance index of Cefoxintin and Netilmicin of the gut microbes of the target object A. Among them, Cefoxintin and Netilmicin ) The corresponding Gene ID in IGC is shown in Table 3 below:

table 3:

Through the above 1.4 Mapped to IGC (comparison with IGC) and Function annotation (function annotation), the sum of the relative abundance of all antibiotic resistance genes of the target object A is 0.354, which is the relative abundance corresponding to each Gene ID in Table 3. See Table 4 below.

Table 4:

Gene IDGene ID	相对丰度Relative abundance
32254883225488	00
61221026122102	00
92966529296652	00

17775981777598	00
15610481561048	00
76807597680759	0.00006010.0000601

2.1.2 Calculate the resistance index of Cefoxintin and Netilmicin:

Cefoxintin (Cefoxitin) resistance index=0+0+0+0+0=0

Netilmicin (netilmicin) resistance index = 0.000601

2.1.3 Determine the position of the resistance index of Cefoxintin and Netilmicin of the target object A in the reference population:

The reference population has currently included 346 individuals with an antibiotic resistance index. The resistance index of Cefoxintin (cefoxitin) 0 is sorted from small to large in the reference population, ranking 0th, Netilmicin (netilmicin) The resistance index 0.0006001 of star) is ranked 13th in the reference population in descending order. Therefore, the position of the Cefoxintin index of the target object A in the reference population (c _a ) 0/346=0; the resistance index of the Netilmicin (netilmicin) of the target object A is in the reference population The position of (c _a )=13/346=0.376.

2.1.4 Confirm the resistance scores of Cefoxintin and Netilmicin (netilmicin) of the gut microbes of the target object A:

According to the preset test standards, the detection level is determined as:

① If 0≤c _a <0.25, the detected human intestinal flora antibiotic resistance gene at a low level:

② If 0.25≤c _a <0.75, detecting a human intestinal flora at the middle level of antibiotic resistance genes:

③ If 0.75≤c _a <1, is detected human intestinal flora antibiotic resistance gene at a high level.

Calculate the antibiotic resistance gene level score calculation:

① If _{0≤c a <0.25, score = 40} + (c a -0) * (60-40) / (0.25-0) = 80 * c a +40;

② If _{0.25≤c a <0.75, score = 60} + (c a -0.25) * (80-60) / (0.75-0.25) = 40 * c a +50;

③ If _{0.75≤c a <1, score = 80} + (c a -0.75) * (100-80) / (1-0.75) = 80 * c a +20.

Therefore, the target object A is Cefoxintin (cefoxitin) index position in the reference population _{(c a) = 0,0≤0 <0.25} , that gut microflora of the target object A Cefoxintin (cefoxitin) resistance index at a low level; a of the target object netilmicin (netilmicin) the resistance index in the position of the reference population _{(c a) = 0.0376,0≤0.0376 <0.25} , the target object a that intestinal The Netilmicin resistance index of the microbial flora is at a low level.

The Cefoxintin resistance gene level score of the target object A:

Score=40*0+50=50

The Netilmicin resistance gene level score of the target object A:

Score=40*0.0376+40=43.008

2.2 Intestinal functional gene analysis

2.2.1 Analysis of intestinal function index

This intestinal function analysis analyzes the short-chain fatty acids (short-chain fatty acid synthesis ability) and Bile Salt Hydrolase (bile salt hydrolysis ability) of the intestinal microbes of the target object A. Short-chain fatty acids (short-chain fatty acid synthesis ability) The KO and Gene ID corresponding to Bile Salt Hydrolase in IGC are shown in Table 5 below:

table 5:

Through the above 1.4 Mapped to IGC (comparison with IGC) and Function annotation (function annotation) to obtain the relative abundance of all KOs of the target object A, and calculate Short-chain fatty acids (short-chain fatty acid synthesis ability) and Bile Salt Hydrolase ( The relative abundance of KO involved in bile salt hydrolysis capacity is summed, as shown in Table 6 below.

Table 6

The sum of the relative abundance of KO involved in each function is the index of the function, so the index of Short-chain fatty acids (short-chain fatty acid synthesis capacity) is 0.00198, and the index of Bile Salt Hydrolase (bile salt hydrolysis capacity) Is 0.000588.

2.2.2 Determine the position of the target object's short-chain fatty acids (short-chain fatty acid synthesis ability) and Bile Salt Hydrolase (bile salt hydrolysis ability) index in the reference population:

The reference population has currently included 346 individual antibiotic resistance indexes. The Short-chain fatty acids index of 0.00198 is ranked in the order of small to large in the reference population, ranking 66th, Bile Salt The Hydrolase (bile salt hydrolysis capacity) index of 0.000588 ranked 269th in the reference population in descending order. Therefore, the position of the Short-chain fatty acids index of the target object A in the reference population (ck) = 66/346 = 0.191; the Bile Salt Hydrolase (bile salt hydrolysis capacity) of the target object A The position of the index in the reference population (ck)=269/346=0.77.

2.2.3 Determine the function scores of short-chain fatty acids (short-chain fatty acid synthesis ability) and Bile Salt Hydrolase (bile salt hydrolysis ability) of the target object:

The set detection value level evaluation is:

① If 0≤c _k <0.25, a certain function of the tested human intestinal flora is at a low level:

②If 0.25≤c _k <0.75, the function of detecting human intestinal flora is at a medium level:

③If 0.75≤c _k <1, a certain function of the tested human intestinal flora is at a higher level.

Rules for calculating the score of intestinal microbial function:

① If 0≤c _k <0.25, score=40+(c-0)*(60-40)/(0.25-0)=80*c+40;

②If 0.25≤c _k <0.75, score=60+(c-0.25)*(80-60)/(0.75-0.25)=40*c+50;

③If 0.75≤c _k <1, score=80+(c-0.75)*(100-80)/(1-0.75)=80*c+20.

Therefore, the position of the short-chain fatty acids (short-chain fatty acid synthesis ability) index of the target object A in the reference population (c _k ) = 0.191, 0≤0.191<0.25, it is considered that the intestinal microbial flora of the target object A Short-chain fatty acids (short-chain fatty acids synthesis ability) functional index is at a low level; the position of the Bile Salt Hydrolase resistance index of the target object A in the reference population (c _k ) = 0.777, 0.75≤0.777<1, it is considered that the functional index of the Bile Salt Hydrolase (bile salt hydrolase ability) of the intestinal microflora of the target object A is at a high level.

The short-chain fatty acids (short-chain fatty acid synthesis ability) function level score of the target object A:

Score=80*0.191+40=55.3

The functional level score of Bile Salt Hydrolase of this target object A:

Score=80*0.777+20=82.16

In summary, the method for processing gut microbial sequencing data provided by this application has achieved the following technical effects:

1. This application analyzes the data generated by metagenomic sequencing. Compared with the traditional 16SrRNA gene data analysis method, it can detect a more comprehensive content of the human intestinal microflora. Among them, the detection content not only includes the intestinal tract The species of microorganisms also contains information on the function of intestinal microorganisms.

2. In this technical solution, 16 kinds of antibiotic resistance-related genes in humans have been tested comprehensively. Through the detection of antibiotic resistance-related genes, the status of various antibiotic resistance genes in the intestinal flora of the tested person can be evaluated. Level.

3. This technical solution can obtain intestinal microbial function information of the detected target object, including: the functional genes of the intestinal microorganisms, the relative abundance of each specific functional gene, and the relative abundance of each specific functional gene in the reference population Location (the relative abundance of antibiotic resistance genes, the relative abundance of intestinal function genes, and their relative abundance respectively in the reference population), so that all the intestinal microbes and specific microbes can be fully evaluated. The status of human intestinal microbes enables comprehensive and diverse analysis of intestinal microbes and individualized analysis.

It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical sequence is shown in the flowchart, in some cases, The steps shown or described can be performed in a different order than here.

The embodiment of the present application also provides a device for processing gut microbial sequencing data. It should be noted that the device for processing gut microbial sequencing data in the embodiment of the present application can be used to execute the intestinal microbial sequencing data processing device provided by the embodiment of the present application. Ways of processing microbial sequencing data. The processing device is introduced below.

Fig. 3 is a schematic diagram of a processing device for intestinal microbial sequencing data according to an embodiment of the present application. As shown in FIG. 3, the device includes: a first acquisition module 31, an annotation module 33, and a second acquisition module 35.

The first obtaining module 31 is configured to obtain sequencing data of the intestinal microbial flora of the target object;

The annotation module 33 is configured to annotate the sequencing data according to the standard gene database to obtain the annotation result;

The second acquisition module 35 is configured to evaluate the intestinal microbial flora of the target object according to the annotation results, and obtain functional information of the intestinal microbes of the target object.

In the apparatus for processing gut microbial sequencing data provided by the embodiment of the present application, the sequencing data of the gut microbial flora of the target object is obtained through the first obtaining module 31; and then the annotation module 33 is executed to annotate the sequencing data according to the standard gene database to obtain Annotation results; finally the second acquisition module 35 is executed. According to the annotation results, the intestinal microbial flora of the target object is evaluated, and the functional information of the intestinal microbes of the target object is obtained. The microbial flora is evaluated, so as to obtain the flora information of the intestinal microbes of the target object, and then to achieve the technical effect of effective analysis of the intestinal microflora and the state of the flora. Compared with the defect that the processing device of the prior art can only provide a single result and limited information, the processing device of this embodiment provides relatively more comprehensive and diversified information, and thus can meet individual needs.

It should be noted that in the apparatus for processing gut microbial sequencing data provided in the embodiments of the present application, the functional information of the gut microbes of the target object includes the functional genes of the gut microbes and the relative abundance of each functional gene. Among them, the function The relative abundance of genes is the ratio of the sum of the relative abundances of genes belonging to the same function in the sequencing data to the sum of the relative abundances of all genes in the sequencing data. The relative abundance of genes belonging to the same function is based on the annotation The result is obtained.

Further, the device for processing gut microbial sequencing data provided in the embodiment of the present application further includes: a performance analysis module configured to perform performance analysis on the gut microbes of the target object based on the function information, and the performance analysis involves at least one of the following: Antibiotic resistance gene analysis and intestinal function gene analysis.

The processing device including the above-mentioned analysis module, after obtaining the functional information of the gut microbes of the target object through the second acquisition module, can also perform antibiotic resistance gene analysis on the gut microbes of the target object based on the functional information through the performance analysis module And/or performance analysis such as intestinal functional gene analysis, realizes the comprehensive and multiple analysis of individual intestinal microbes, and meets the technical effects of individual analysis requirements, thereby solving the single, single, and unique analysis result in the existing technology. The information is limited and cannot meet the technical problems of individualized analysis needs.

Optionally, in the device for processing intestinal microbial sequencing data provided by the embodiment of the present application, in the case that the performance analysis involves antibiotic resistance gene analysis, the performance analysis module includes: a first calculation module configured to calculate the target object The antibiotic resistance index of intestinal microbes, the first position determination module is set to determine the position of the antibiotic resistance index in the reference population; when the performance analysis involves intestinal functional gene analysis, the performance analysis module includes: second calculation The module is set to calculate the intestinal function index of the intestinal microbes of the target object, and the second position determination module is set to determine the position of the intestinal function index in the reference population.

Among them, in an optional example, the step of "analyzing the intestinal microbes of the target object for antibiotic resistance genes" performed by the performance analysis module is illustrated as an example:

First, the first calculation module calculates the antibiotic resistance index of each antibiotic of the gut microbe of the target object.

Second, the first position determination module determines the position of the antibiotic resistance index of each antibiotic in the reference population. Taking erythromycin as an example, the erythromycin resistance index of the reference population (such as 100, 200, 300, 1000 or The erythromycin resistance index of the intestinal microbial test results of more individual groups (such as healthy people) is sorted from small to large, and it is determined that the erythromycin resistance index in the reference population is less than that of the target object. The number of people with sex index (i _a ), the position of the target object’s erythromycin resistance index in the reference population is determined by calculating the ratio of i _a to the total number of people in the reference population (s _a )

In addition, after the performance analysis module determines the antibiotic resistance index of the target object and the position of the antibiotic resistance index in the reference population based on the first position determination module, it may also include an antibiotic resistance scoring module: the antibiotic resistance scoring module is used To determine the antibiotic resistance score of the gut microbes of the target object, the antibiotic resistance score module calculates the antibiotic resistance score by executing the following method:

It should also be noted that the foregoing Table 1 exemplarily lists 16 antibiotics and their corresponding partial gene IDs (numbers), and each gene ID corresponds to a gene sequence. In actual research applications, one or more of them can be selected according to different research directions or purposes, or other related genes can be selected.

In an optional example, the performance analysis module performs "intestinal functional gene analysis of the intestinal microbes of the target object" for example:

First, the second calculation module calculates the intestinal function index of each function of the gut microbe of the target object, that is, the sum of the relative abundances of functional genes related to the same function is used as the intestinal function index corresponding to the function.

Secondly, the second position determination module determines the position of the intestinal function index corresponding to each function in the reference population. Taking energy metabolism capacity as an example, the intestinal function index of the intestinal energy metabolism capacity of the reference population (for example, 100, 200 , 300, 1000 or more people (such as healthy people) in the intestinal microbial test results in the intestinal function index of energy metabolism) in order from small to large, determine the intestinal function index in the reference population is smaller than the target object The number of intestinal function index of intestinal energy metabolism capacity (i _o ), by calculating the ratio of i _o to the total number of people in the reference population (s _o ), determine the intestinal function index of intestinal energy metabolism capacity of the target object in the reference population position

In addition, the performance analysis module may further include an intestinal function scoring module after determining the intestinal function index of the target object and the position of the intestinal function index in the reference crowd based on the second calculation module and the second position determining module, respectively, The intestinal function score module is used to determine the intestinal function score of the intestinal microbes of the target object. The intestinal function score module can calculate the intestinal function score by executing the following methods:

It should also be noted that the foregoing Table 2 exemplarily lists 9 functions. In specific applications, one or more of them can be selected according to needs, and other functions of interest and related genes can also be selected.

Optionally, in the device for processing intestinal microbial sequencing data provided by the embodiment of the present application, the first calculation module includes: a first summation unit, which is set to measure the relative abundance of antibiotic resistance genes when the antibiotic resistance index is In this case, the first summation unit is used to calculate the sum of the relative abundances of the same antibiotic resistance gene of the gut microbes of the target object; the division unit is set to the sum of the relative abundances of the same antibiotic resistance gene Divide by the sum of the relative abundances of all antibiotic resistance genes to obtain the relative abundance of antibiotic resistance genes; the second calculation module includes: the second summation unit, which is set to compare the relative abundance of functional genes belonging to the same intestinal function The abundance is added to obtain the intestinal function index.

Optionally, in the device for processing intestinal microbial sequencing data provided in the embodiment of the present application, the performance analysis module further includes: a first import module configured to analyze the antibiotic resistance gene when the performance analysis is involved, and the first calculation module calculates When the antibiotic resistance index of the gut microbes of the target object is obtained, the antibiotic resistance index of the gut microbes of the target object is imported into the database of the reference population for use in the next performance analysis step; the second import module is set to In the case that the performance analysis involves intestinal function gene analysis, and the second calculation module calculates the intestinal function index of the intestinal microbes of the target object, the intestinal function index of the intestinal microbes of the target object is imported into the database of the reference population. Used in the next performance analysis step.

In the case where the above-mentioned performance analysis module further includes a first introduction module and a second introduction module, the processing device can evaluate the intestinal microflora of each target object and obtain functional information of the target object’s intestinal microbes. , It can also add the evaluation result (functional information of the gut microbes of the target object, the functional information includes the functional genes of the gut microbes and the relative abundance of each functional gene) to the database of the reference population stored in the processing device , In order to update the reference range of each indicator in real time.

With the use of the processing device for intestinal microbial sequencing data of this application, more and more individuals participate in the evaluation of the intestinal microbial flora, and the scale of the reference population stored in the database will continue to expand, thereby making the processing device more effective The results of microbial flora evaluation will also become more and more accurate, and the reference value of the processing device for the evaluation of intestinal microflora is also increasing.

Finally, when the number of reference populations stored in the database reaches a certain degree of abundance, the processing device of this application will also determine the phenotypic characteristics of the individual to be tested (including gender, age, race, height, weight, diet, living area). Etc.) Select the corresponding reference population for specific intestinal microbial flora assessment and analysis, thereby making the assessment results more accurate and reliable.

It should also be noted that the target number of initial reference objects are initially stored in the database of the processing device, and the database specifically records the phenotype information of each initial reference object (including gender, age, race, height, weight, diet). , Living area, etc.) and the evaluation information of the intestinal microbial flora (including antibiotic resistance gene analysis and intestinal function gene analysis, etc., and may further include the relative abundance information of each intestinal microbe species, etc.).

In addition, it is also necessary to explain the first obtaining module 31 of the apparatus for processing gut microbial sequencing data of the present application:

In an optional example, the first obtaining module 31 obtains the sequencing data of the gut microbial flora of the target object by performing the following steps:

In addition, it is necessary to explain the annotation module 33 in the processing device of this application:

In an optional example, the annotation module 33 can be implemented by performing the following steps:

Step B2, based on the annotation information of each gene sequence recorded in the standard gene database (annotation information includes: the resistance gene information corresponding to each antibiotic, which can form an antibiotic resistance gene annotation file), and each type contained in the sequencing data The relative abundance of the gene sequence, determine the relative abundance of each antibiotic resistance gene sequence contained in the sequencing data, (for example: determine the corresponding antibiotic resistance gene abundance file in the sequencing data, where the file contains two columns of data , The data in the left column is the information of various antibiotic resistance genes, and the data in the right column is the relative abundance corresponding to the resistance genes on the left. The specific calculation method can be: according to the gene abundance file in step B1 and the generation in B2 Add the relative abundance of genes belonging to the same antibiotic resistance gene, and then divide by the sum of the relative abundances of all antibiotic resistance genes in the sample. The result is the antibiotic resistance Relative abundance of sex genes);

Step B3, based on the annotation information of each gene sequence recorded in the standard gene database (the annotation information includes: the gene information corresponding to each biological function, wherein the number of genes corresponding to each biological function is one or more According to the specific biological function, the number of genes also differs), and the relative abundance of each gene sequence contained in the sequencing data, determine the relative abundance of each biological function gene contained in the sequencing data, ( For example: to determine the biological function gene abundance file corresponding to the sequencing data, where the file contains two columns of data, the left column of data is the gene information corresponding to various biological functions, and the right column of data is the various organisms on the left The relative abundance of the genes corresponding to the scientific function in turn, the specific calculation method can be, for example, adding the relative abundance of genes belonging to the same function, and then dividing the relative abundance of each function-related gene by The sum of the relative abundance of related genes corresponding to all the functions of the sample is the relative abundance of each functional gene).

The apparatus for processing gut microbial sequencing data of the present application includes a processor and a memory. The above-mentioned first acquisition module 31, annotation module 33, and second acquisition module 35 are all stored as program units in the memory, and are executed by the processor and stored in the memory. The above-mentioned program unit in to realize the corresponding function.

The processor contains a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the intestinal microbial flora and the status of the flora can be effectively and comprehensively analyzed by adjusting the kernel parameters.

The memory may include non-permanent memory in computer-readable media, random access memory (RAM) and/or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one Memory chip.

The embodiment of the present application provides a storage medium on which a program is stored, and when the program is executed by a processor, a method for processing gut microbial sequencing data is realized.

The embodiment of the present application provides a processor, which is used to run a program, wherein the intestinal microbial sequencing data processing method is executed when the program is running.

The embodiment of the present application provides a device, which includes a processor, a memory, and a program stored on the memory and running on the processor. The processor executes the program to implement the following steps: obtain the intestinal microflora of the target object Sequencing data: Annotate the sequencing data according to the standard gene database to obtain the annotation results; according to the annotation results, evaluate the gut microbiota of the target object to obtain functional information of the gut microbe of the target object.

Optionally, the functional information of the gut microbes of the target object includes the functional genes of the gut microbes and the relative abundance of each functional gene, where the relative abundance of the functional gene is the relative abundance of genes belonging to the same function in the sequencing data The ratio of the sum of and the sum of the relative abundances of all functional genes in the sequencing data. The relative abundances of genes belonging to the same function are obtained from the annotation results.

Optionally, after obtaining the functional information of the gut microbes of the target object, the method further includes: performing performance analysis on the gut microbes of the target object based on the function information, and the performance analysis involves at least one of the following: antibiotic resistance gene analysis and Intestinal function gene analysis.

Optionally, in the case that the performance analysis involves the analysis of antibiotic resistance genes, the performance analysis of the gut microbes of the target object based on the functional information includes: calculating the antibiotic resistance index of the gut microbes of the target object and determining the antibiotic resistance The position of the index in the reference population; in the case that the performance analysis involves intestinal function gene analysis, the performance analysis of the gut microbes of the target object based on the function information includes: calculating the gut function index of the gut microbes of the target object, Determine the position of the intestinal function index in the reference population.

Optionally, the antibiotic resistance index is the relative abundance of antibiotic resistance genes, and the relative abundance of antibiotic resistance genes is calculated according to the following method: Calculate the relative abundance of the same kind of antibiotic resistance genes in the gut microbes of the target object And; divide the sum of the relative abundances of the same antibiotic resistance gene by the sum of the relative abundances of all antibiotic resistance genes to get the relative abundance of antibiotic resistance genes; the intestinal function index is calculated by the following method: belong to the same The sum of the relative abundance of the functional genes of the intestinal function is the intestinal function index.

Optionally, when the performance analysis involves the analysis of antibiotic resistance genes, and the performance analysis of the gut microbes of the target object is performed based on the functional information, and the antibiotic resistance index of the gut microbes of the target object is calculated, it also includes The antibiotic resistance index of the gut microbes of the target object is imported into the database of the reference population for the next performance analysis step; the performance analysis involves the analysis of the gut function genes, and the performance of the gut microbes of the target object is performed based on the functional information When the intestinal function index of the intestinal microbes of the target object is obtained by analysis and calculation, it also includes importing the intestinal function index of the intestinal microbes of the target object into the database of the reference population for use in the next performance analysis step. The devices in this article can be servers, PCs, PADs, mobile phones, etc.

This application also provides a computer program product, which when executed on a data processing device, is suitable for executing a program that initializes the following method steps: acquiring the sequencing data of the gut microbial flora of the target object; sequencing according to the standard gene database The data is annotated to obtain the annotation result; according to the annotation result, the gut microbial flora of the target object is evaluated to obtain the functional information of the gut microbe of the target object.

Optionally, when the performance analysis involves the analysis of antibiotic resistance genes, and the performance analysis of the gut microbes of the target object is performed based on the functional information, and the antibiotic resistance index of the gut microbes of the target object is calculated, it also includes The antibiotic resistance index of the gut microbes of the target object is imported into the database of the reference population for the next performance analysis step; the performance analysis involves the analysis of gut function genes, and the performance analysis of the gut microbes of the target object is performed based on the functional information In the case where the intestinal function index of the intestinal microbe of the target object is calculated, the intestinal function index of the intestinal microbe of the target object is also imported into the database of the reference population for use in the next performance analysis step.

Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

This application is described with reference to flowcharts and/or block diagrams of methods, devices (systems), and computer program products according to embodiments of the application. It should be understood that each flow and/or block in the flowchart and/or block diagram and a combination of the flow and/or block in the flowchart and/or block diagram may be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated A device that implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device. The device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operating steps are performed on the computer or other programmable device to generate computer-implemented processing, which is executed on the computer or other programmable device The instructions provide steps for implementing the functions specified in one block or multiple blocks of the flowchart one flow or multiple flows and/or block diagrams.

In a typical configuration, the computing device includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.

The memory may include non-permanent memory in a computer readable medium, random access memory (RAM) and/or non-volatile memory, such as read only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

Computer-readable media, including permanent and non-permanent, removable and non-removable media, can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, Magnetic tape cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media can be used to store information that can be accessed by computing devices. As defined in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

It should also be noted that the terms "include", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device that includes a series of elements includes not only those elements, but also includes Other elements not explicitly listed, or include elements inherent to this process, method, commodity, or equipment. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, commodity or equipment that includes the element.

The above are only examples of the application, and are not used to limit the application. For those skilled in the art, this application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the scope of the claims of this application.

Industrial applicability

Claims

A method for processing intestinal microbial sequencing data, wherein the method includes:

Obtain sequencing data of the gut microbial flora of the target object;

Annotate the sequencing data according to the standard gene database to obtain an annotation result;

According to the annotation result, the intestinal microbial flora of the target object is evaluated, and the functional information of the intestinal microbe of the target object is obtained.
The method according to claim 1, wherein the functional information of the gut microbes of the target object includes functional genes of the gut microbes and the relative abundance of each of the functional genes, wherein the relative abundance of the functional genes Is the ratio of the sum of the relative abundances of the genes that are related to the same function in the sequencing data to the sum of the relative abundances of the genes that are related to each function in the sequencing data, and the relative abundance of the genes that are related to the same function The abundance is obtained according to the annotation result.
The method according to claim 1 or 2, wherein after obtaining the functional information of the gut microbes of the target object, the method further comprises:

Perform performance analysis on the intestinal microbes of the target object based on the functional information, and the performance analysis involves at least one of the following: antibiotic resistance gene analysis and intestinal functional gene analysis.
The method of claim 3, wherein

In the case where the performance analysis involves antibiotic resistance gene analysis, performing performance analysis on the gut microbes of the target object based on the functional information includes: calculating an antibiotic resistance index of the gut microbes of the target object, Determine the position of the antibiotic resistance index in the reference population;

In the case where the performance analysis involves intestinal function gene analysis, the performance analysis of the gut microbes of the target object based on the function information includes: calculating the gut function index of the gut microbes of the target object, The position of the intestinal function index in the reference population is determined.
The method according to claim 4, wherein

The antibiotic resistance index is the relative abundance of antibiotic resistance genes, and the relative abundance of the antibiotic resistance genes is calculated according to the following method: Calculate the genes related to the same kind of antibiotic resistance of the gut microbes of the target object The sum of relative abundance; the sum of the relative abundance of the genes related to the same antibiotic resistance is divided by the sum of the relative abundances of all the genes related to antibiotic resistance to obtain the relative abundance of the antibiotic resistance genes ；

The intestinal function index is calculated by the following method: the sum of the relative abundances of functional genes related to the same function is the intestinal function index.
The method according to claim 4, wherein

In the case where the performance analysis involves the analysis of antibiotic resistance genes, and the performance analysis of the gut microbes of the target object is performed based on the function information, and the antibiotic resistance index of the gut microbes of the target object is calculated , Further comprising importing the antibiotic resistance index of the gut microbes of the target object into the database of the reference population for use in the next performance analysis step;

When the performance analysis involves intestinal function gene analysis, and the performance analysis of the intestinal microbes of the target object is performed based on the function information, and the intestinal function index of the intestinal microbes of the target object is calculated , It also includes importing the intestinal function index of the intestinal microbe of the target object into the database of the reference population for use in the next performance analysis step.
A processing device for intestinal microbial sequencing data, wherein the device includes:

The first obtaining module is configured to obtain sequencing data of the intestinal microflora of the target object;

An annotation module, configured to annotate the sequencing data according to the standard gene database to obtain an annotation result;

The second acquisition module is configured to evaluate the intestinal microbial flora of the target object according to the annotation results, and obtain functional information of the intestinal microbes of the target object.
7. The device according to claim 7, wherein the functional information of the gut microbes of the target object includes functional genes of the gut microbes and the relative abundance of each of the functional genes, wherein the relative abundance of the functional genes Is the ratio of the sum of the relative abundances of genes that are related to the same function in the sequencing data to the sum of the relative abundances of all the functionally related genes in the sequencing data, and the relative abundance of the genes that are related to the same function The abundance is obtained according to the annotation result.
The device according to claim 7 or 8, wherein the device further comprises: a performance analysis module configured to perform performance analysis on the gut microbes of the target object based on the function information, and the performance analysis involves the following At least one of: antibiotic resistance gene analysis and intestinal function gene analysis.
The device according to claim 9, wherein:

In the case that the performance analysis involves antibiotic resistance gene analysis, the performance analysis module includes: a first calculation module configured to calculate the antibiotic resistance index of the gut microbe of the target object, and a first position determination module, Set to determine the position of the antibiotic resistance index in the reference population;

In the case that the performance analysis involves intestinal function gene analysis, the performance analysis module includes: a second calculation module configured to calculate the intestinal function index of the intestinal microbe of the target object, and a second position determination module, It is set to determine the position of the intestinal function index in the reference population.
The device according to claim 10, wherein

The first calculation module includes: a first summation unit, configured to calculate the target object when the antibiotic resistance index is the relative abundance of antibiotic resistance genes The sum of the relative abundances of genes related to the same antibiotic resistance of the gut microbes; the division unit is set to divide the sum of the relative abundances of the genes related to the same antibiotic resistance by all antibiotic resistance related The sum of the relative abundances of the genes of, to obtain the relative abundance of the antibiotic resistance genes;

The second calculation module includes: a second summation unit configured to sum the relative abundances of functional genes related to the same function to obtain the intestinal function index.
The device according to claim 10, wherein the performance analysis module further comprises:

The first import module is configured to: when the performance analysis involves antibiotic resistance gene analysis, and the first calculation module calculates the antibiotic resistance index of the gut microbe of the target object, the target object The antibiotic resistance index of intestinal microbes imported into the database of the reference population for use in the next performance analysis step;

The second import module is configured to: when the performance analysis involves intestinal function gene analysis and the second calculation module calculates the intestinal function index of the intestinal microbes of the target object, the target object The intestinal function index of the gut microbes is imported into the database of the reference population for use in the next performance analysis step.
A storage medium comprising a stored program, wherein the program executes the method for processing gut microbial sequencing data according to any one of claims 1 to 6.
A processor for running a program, wherein the method for processing gut microbial sequencing data according to any one of claims 1 to 6 is executed when the program is running.