Gene variation frequency calculation system based on personalized phenotypic population

Abstract

The invention discloses a gene variation frequency calculation system based on personalized phenotypic crowds. The gene variation frequency calculation system comprises a data acquisition module, a clinical phenotypic category module, a crowd phenotypic construction module, a data classification module, a data extraction module, a personalized combination module and a mark calculation module. According to the method, gene variation population frequency related to a specific phenotype can be provided, gene variation frequency data rich in phenotype can be provided by combining the genotype with the specific phenotype, reference result data of genome variation frequency of different populations can be obtained through calculation, the data can be stored and transmitted, and an existing database can be perfected.

Description

Technical Field

[0001] The present invention relates to the field of bioinformatics technology, and particularly to a gene variant frequency calculation system based on personalized phenotype populations. Background Art

[0002] With the large-scale application of genome sequencing technology and bioinformatics methods, a large amount of genomic variant data has been annotated and analyzed. These genomic variant data are of great significance for studying health and diseases. Especially for studying gene variant frequency information in populations with different populations, ages, genders, disease types, etc., it can provide strong support for revealing the history of human evolution, understanding the population distribution of disease-related variants, providing personalized medical treatment, etc.

[0003] After retrieval, a Chinese patent with the publication number CN114999573B discloses a genomic variant detection method and detection system, which proposes a technical solution for improving the accuracy of genomic variant detection by using a trained neural network model in a computer program;

[0004] A Chinese patent with the publication number CN107229841B discloses a gene variant evaluation method and system, which proposes a technical solution for obtaining a judgment result of the mutation frequency of a mutation site through stored information in a database;

[0005] The existing research on gene variant frequencies covers a variety of populations around the world, but most lack personalized phenotypic characteristics, resulting in the inability to use gene variant frequency data more effectively. Therefore, there is an urgent need for a gene variant frequency calculation system based on personalized phenotype populations. Summary of the Invention

[0006] The purpose of the present invention is to solve the defects existing in the prior art, and to propose a gene variant frequency calculation system based on personalized phenotype populations.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions:

[0008] A gene variant frequency calculation system based on personalized phenotype populations, comprising:

[0009] A data acquisition module, configured to connect to a corresponding database through a wireless communication method, obtain data samples, and transmit them to a corresponding terminal;

[0010] A clinical phenotype category module, configured to automatically match corresponding data and generate a classification of clinical phenotype data;

[0011] A population phenotype construction module, configured to construct a basic unit of population phenotype according to the obtained data samples, wherein the basic unit of population phenotype includes 5 phenotype categories, and each phenotype category is provided with at least one grouping;

[0012] A data classification module, which is used to group the collected data. At the same time, match the collected data samples to the corresponding basic population phenotype units;

[0013] A data extraction module, which is used to extract the genomic variation annotation data of the population that meets the definition of the population phenotype construction module;

[0014] A personalized combination module, which is used to manually establish a classification logic for personalized phenotype categories, generate personalized phenotype categories, and match and detect the corresponding data for automated detection;

[0015] A marker calculation module, which is used to establish a mutation site judgment logic, calculate the gene mutation frequency equivalent value for each of the obtained basic population phenotype units one by one, and generate a personalized phenotype population gene mutation frequency annotation matrix.

[0016] Further, in step 1, the phenotype feature grouping categories include: gender, age, ethnicity, region, and disease classification.

[0017] Further, in step S4, for the actually obtained basic population phenotype units, the specific steps for calculating the gene mutation frequency equivalent value one by one are as follows:

[0018] Obtain the VCF file of the total population, and extract the genotype data of the samples contained in the basic population phenotype unit according to the sample ID;

[0019] Calculate the allele count, allele number, allele frequency, number of homozygous reference individuals, number of heterozygous variant individuals, and number of homozygous variant individuals for each mutation site in each sample of the basic population phenotype unit one by one, and construct a personalized phenotype population gene mutation frequency annotation matrix.

[0020] Further, in step S4, if the genotype is '0 / 0', then allele count + 0, allele number + 2, and the number of homozygous reference individuals + 1;

[0021] If the genotype is '0 / 1' or '1 / 0', then allele count + 1, allele number + 2, and the number of heterozygous variant individuals + 1;

[0022] If the genotype is '1 / 1', then allele count + 2, allele number + 2, and the number of homozygous variant individuals + 1;

[0023] After summarizing the statistical values, calculate the allele frequency: the formula is allele frequency = allele count / allele number.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] It can provide the population frequency of gene variations related to specific phenotypes. By combining genotypes with specific phenotypes, it provides rich phenotyped gene variation frequency data, calculates the result data of the reference genomic variation frequencies of different populations, stores and transmits the data, and can improve the existing database. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention.

[0027] Figure 1 It is an implementation logic diagram of a gene variation frequency calculation system based on personalized phenotype populations proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0029] As Figure 1 shown, for a gene variation frequency calculation system based on personalized phenotype populations, the method uses an auxiliary system;

[0030] The method includes the following steps:

[0031] S1: Collect data samples, and group the population according to the clinical phenotype categories and grouping information of the samples according to different phenotype characteristics;

[0032] S2: Group the population according to different phenotype characteristics and preset it as different basic units of population phenotypes;

[0033] S3: For the obtained basic units of population phenotypes, respectively extract the genomic variation annotation data of the population that conforms to its phenotype definition;

[0034] S4: Construct a gene variation frequency annotation matrix for personalized phenotype populations according to specific gene variation data, and export the result data to a specified terminal.

[0035] As a preferred embodiment of the present application, in step 1, the phenotype characteristic grouping categories include: gender, age, ethnicity, region, and disease classification;

[0036] In a specific embodiment of the present application, the auxiliary system includes:

[0037] A data collection module, which is used to connect to the corresponding database through wireless communication, obtain data samples, and transmit them to the corresponding terminal;

[0038] It should be noted that the database includes gnomAD.

[0039] Clinical phenotype category module, which is used to automatically match corresponding data and generate clinical phenotype data classification;

[0040] It should be noted that the clinical phenotype categories are: age, gender, ethnicity, region, disease type;

[0041] Among them, age can be divided into 5 groups: 0 - 6, 7 - 18, 19 - 50, over 50, NA;

[0042] Gender is divided into 3 groups: male, female, NA;

[0043] Ethnicity is divided into 47 groups: 46 ethnic groups are classified separately (the classification includes Han, Zhuang, Hui...), NA;

[0044] Region is divided into 8 groups: Northeast, East China, North China, Central China, South China, Northwest, Southwest, NA;

[0045] Disease type is divided into 14 groups: Central Nervous System, Cardiovascular System, Respiratory System, Digestive System, Otolaryngology, Ophthalmology, Oral and Maxillofacial System, Hematological System, Urogenital System, Skeletal Muscle System, Endocrine and Metabolic System, Rheumatological and Immunological System, Dermatology and Normal.

[0046] Population phenotype construction module, which is used to construct basic population phenotype units according to the obtained data samples. Among them, the basic population phenotype units include 5 phenotype categories, and at least one group is set for each phenotype category;

[0047] Data classification module, which is used to group the collected data, and at the same time, match the collected data samples to the corresponding basic population phenotype units;

[0048] Data extraction module, which is used to extract genomic variant annotation data of the population that meets the definition of the population phenotype construction module;

[0049] Personalized combination module, which is used to manually establish personalized phenotype category classification logic, generate personalized phenotype categories, and match and detect corresponding data for automated detection;

[0050] It should be noted that: it includes several personalized phenotype categories of custom combinations, for example:

[0051] Combination 1: Age: 0 - 6, Gender: Female, Ethnicity: Han, Region: North China, Disease Type: Otolaryngology, and the basic phenotype unit is defined as: G1_A1_N17_R3_D5

[0052] Combination 2: Age: 7 - 18, Gender: Female, Ethnicity: Han, Region: North China, Disease Type: Central Nervous System, the basic phenotypic unit is defined as: G1_A2_N17_R3_D1

[0053] Combination 3: Age: 19 - 50, Gender: Male, Ethnicity: Zhuang, Region: Northeast China, Disease Type: Digestive System, the basic phenotypic unit is defined as: G2_A3_N46_R1_D4

[0054] The marker calculation module is used to establish the judgment logic of variant sites, and calculate the gene variant frequency equivalents for each obtained basic population phenotypic unit one by one, generating a personalized phenotypic population gene variant frequency annotation matrix.

[0055] Among them, the data collection module is respectively connected to the data classification module, the clinical phenotype category module and the population phenotype construction module. The data classification module is connected to the data extraction module, and both the clinical phenotype category module and the population phenotype construction module are connected to the personality combination module. The personality combination module is respectively connected to the data extraction module and the marker calculation module.

[0056] As a preferred embodiment of the present application, in step S4, for the actually obtained basic population phenotypic unit, the specific steps of calculating the gene variant frequency equivalents one by one are as follows:

[0057] Obtain the VCF (Genomic Variant Annotation) file of the total population, and extract the genotype data of the samples contained in this basic population phenotypic unit according to the sample ID;

[0058] Calculate the AC (Allele Count), AN (Allele Number), AF (Allele Frequency), the number of homozygous reference persons, the number of heterozygous variant persons and the number of homozygous variant persons for each variant site (determined by the CHROM, POS, REF, ALT fields) in each basic population phenotypic unit sample one by one, and construct a personalized phenotypic population gene variant frequency annotation matrix, where:

[0059] If the genotype is '0 / 0' (representing no mutation), then allele number + 2, the number of homozygous reference persons + 1;

[0060] If the genotype is '0 / 1' or '1 / 0' (representing a heterozygous mutation), then allele count + 1, allele number + 2, the number of heterozygous variant persons + 1;

[0061] If the genotype is '1 / 1' (representing a homozygous mutation), then allele count + 2, allele number + 2, the number of homozygous variant persons + 1.

[0062] In specific implementation: For a certain gene mutation, taking the total number of people as 100 and the gene GJB2 c.235delC mutation as an example;

[0063] Extract the data of this gene mutation of the specified phenotypic population from the VCF (Genome Variation Annotation File) file of the total population, and calculate the genotypes of this gene mutation site in the population, where:

[0064] The total number of people is 100: 80 people have the genotype '0 / 0';

[0065] 10 people have the genotype '0 / 1' or '1 / 0';

[0066] 10 people have the genotype '1 / 1';

[0067] Then Allele Count = 10 + 10 * 2 = 30, Allele Number = 100 * 2, Allele Frequency = Allele Count / Allele Number = 0.15, the number of homozygous reference people = 80, the number of heterozygous variant people = 10, and the number of homozygous variant people = 10;

[0068] Construct an annotation matrix form of the mutation site, as shown in Table 1 specifically.

[0069] Unit CHROM POS REF ALT AC AN AF HOM_REF HET HOM_ALT G1_A2_N17_R2_D5 chr13 20189346 AG A 30 200 0.15 80 10 10

[0070] Table 1

[0071] After obtaining the table, it is converted into corresponding readable data by the auxiliary system and sent to the corresponding terminal or server for storage, providing reference genomic variation frequency data for different populations.

[0072] The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A gene variant frequency calculation system based on personalized phenotypic populations, characterized in that Including: A data acquisition module, which is used to connect to the corresponding database through wireless communication, obtain data samples, and transmit them to the corresponding terminal; A clinical phenotype category module, which is used to automatically match the corresponding data and generate a classification of clinical phenotype data; A population phenotype construction module, which is used to construct the basic unit of population phenotype according to the obtained data samples. Among them, the basic unit of population phenotype includes 5 phenotype categories, and each phenotype category has at least one group; A data classification module, which is used to group the collected data. At the same time, the collected data samples are matched to the corresponding basic unit of population phenotype; A data extraction module, which is used to extract the genomic variant annotation data of the population that meets the definition of the population phenotype construction module; A personalized combination module, which is used to manually establish a classification logic for personalized phenotype categories, generate personalized phenotype categories, and match and detect the corresponding data for automated detection; A marker calculation module, which is used to establish a mutation site judgment logic, calculate the gene mutation frequency equivalent value for each of the obtained basic units of population phenotype one by one, and generate a personalized phenotype population gene mutation frequency annotation matrix.

2. The gene variant frequency calculation system based on personalized phenotypic populations according to claim 1, wherein In step 1, the phenotypic feature grouping categories include: gender, age, ethnicity, region, and disease classification.

3. The gene variant frequency calculation system based on personalized phenotypic populations according to claim 2, wherein In step S4, for the actually obtained basic unit of population phenotype, the specific steps for calculating the gene mutation frequency equivalent value one by one are as follows: Obtain the VCF file of the total population, and extract the genotype data of the samples contained in the basic unit of this population phenotype according to the sample ID; Calculate the allele count, allele number, allele frequency, number of homozygous reference individuals, number of heterozygous variant individuals, and number of homozygous variant individuals of each mutation site in the samples of each basic unit of population phenotype one by one, and construct a personalized phenotype population gene mutation frequency annotation matrix.

4. The gene variant frequency calculation system based on personalized phenotypic populations according to claim 3, wherein In step S4, if the genotype is '0 / 0', then allele number + 2, number of homozygous reference individuals + 1; If the genotype is '0 / 1' or '1 / 0', then allele count + 1, allele number + 2, number of heterozygous variant individuals + 1; If the genotype is '1 / 1', then allele count + 2, allele number + 2, number of homozygous variant individuals + 1; The gene mutation frequency is allele frequency = allele count / allele number.

Images