A method and device for determining HLA type

Abstract

The present application is applicable to the field of bioinformatics, and provides an HLA type determination method and device, including: comparing and screening HLA second-generation sequencing data samples after quality control processing with gene features of an HLA type database, and gene classification of the screened data; determining the candidate type range of each gene according to the gene-classified data and the HLA type database; comparing the gene-classified data with a preset gene sequence to determine the difference site; chaining the difference sites into chains, and comparing them with the difference site database to obtain accurate candidate types; determining the HLA type result according to the candidate type range and the accurate candidate type; the present application can directly analyze the HLA type result for normal HLA second-generation sequencing data samples without manual intervention, and will give corresponding prompt information for abnormal data such as HLA new type samples, suspected mixed samples, and data unqualified samples.

Description

Technical Field

[0001] The present application belongs to the field of bioinformatics, and in particular, relates to a method and device for determining HLA type. Background Art

[0002] HLA (Human Leukocyte Antigen) is a group of highly polymorphic protein molecules that exist on the surface of human cells and play a key role in the immune system. HLA molecules are mainly present on the surface of immune cells, especially T cells, B cells and antigen-presenting cells, as well as cells in other tissues. They play an important role in identifying and presenting antigens, regulating immune responses, and immune rejection of tissue transplants.

[0003] The HLA gene is located on the short arm of chromosome 6, which is about 4000Kb long. HLA has dozens of gene loci, each of which has dozens of alleles, and is co-dominantly expressed. Since the HLA gene is located on the same chromosome, the genotype combination on its multi-gene loci is relatively stable, and exchange between homologous chromosomes rarely occurs, which constitutes an inheritance characterized by a haplotype (HAPLOTYPE, that is, a special combination of a series of alleles closely linked on the same chromosome).

[0004] There are multiple types of HLA genes (i.e. alleles), and multiple types mean that each HLA locus has multiple alleles. Currently, there are 8098 HLA-A types, 9656 HLA-B types, 8084 HLA-C types, 3628 HLA-DRB1 types, 2510 HLA-DQB1 types, and 2486 HLA-DPB1 types included in the IMGT database. The differences between sequences of different types are very small, generally the difference of a few SNPs (Single Nucleotide Polymorphisms, single nucleotide polymorphisms, point mutations).

[0005] HLA molecules are mainly divided into two categories: HLA-I and HLA-II. HLA-I molecules (such as HLA-A, HLA-B, HLA-C) mainly present endogenous antigens on the cell surface and interact with CD8+ T cells. HLA-II molecules (such as HLA-DP, HLA-DQ, HLA-DR) mainly present exogenous antigens on the surface of antigen-presenting cells and interact with CD4+ T cells. Type III molecules are the complement system, including C2 and C4 sites, and are present in serum. Type IV molecules may be some differentiation antigens that only exist in lymphocytes, certain cytotoxic T cells, and white blood cells.

[0006] HLA typing technology has gone through a development process from serological and cytological typing with low resolution and accuracy to genotyping with high resolution and accuracy. The commonly used genotyping technology has developed with the application of polymerase chain amplification technology (PCR), mainly including restriction fragment length polymorphism (PCR-RFLP), sequence-specific oligonucleotide probe (PCR-SSO), sequence-specific primer (PCR-SSP), direct sequencing typing (PCR-STB), etc. Among them, SBT is an HLA typing method based on Sanger sequencing (dideoxy chain ddNTP terminal termination sequencing method). This method has high resolution, can directly read the allele DNA sequence, and the reading accuracy of each base is as high as 99.99%. It can directly discover new alleles. It is the "gold standard" of HLA typing methods recommended by the World Health Organization (WHO); the disadvantages are high cost, long time consumption, low throughput, and due to the presence of heterozygotes, it is impossible to distinguish the unit type, which will result in ambiguous results.

[0007] Currently, the only registered HLA typing tool on the market is a software from OMIXON in the United States. It is a commercial software that is visualized and requires manual analysis. Its disadvantage is that it is necessary to manually identify the HLA type based on the software's visualized graphics and recommended possible types, which can lead to misjudgment caused by human factors. In addition, this software cannot accurately analyze new types that are not in the HLA database, which can cause misjudgment and misjudge new types as other known types. Summary of the invention

[0008] The purpose of the embodiments of the present application is to provide a method and device for determining HLA types, aiming to solve the problem that the existing HLA typing technology is prone to misjudgment due to human factors and cannot accurately analyze new types.

[0009] A first aspect of an embodiment of the present application provides a method for determining an HLA type, comprising:

[0010] The HLA second-generation sequencing data samples after quality control are compared and screened with the gene features of the HLA type database, and the screened data are genetically classified;

[0011] Determine the candidate type range of each gene based on the gene classification data and the HLA type database;

[0012] Compare the gene classification data with the preset gene sequence to determine the difference sites; the preset gene sequence is different from the sequence of each genotype in the HLA type database, and the difference sites with each genotype are different;

[0013] The differential sites are linked into chains and compared with the differential site database to obtain accurate candidate types;

[0014] The HLA typing result is determined based on the candidate type range and the precise candidate type.

[0015] A second aspect of an embodiment of the present application provides an HLA type determination device, comprising:

[0016] The gene classification module is used to compare and screen the HLA second-generation sequencing data samples after quality control with the gene characteristics of the HLA type database, and to perform gene classification on the screened data;

[0017] A candidate type range determination module is used to determine the candidate type range of each gene based on the gene classification data and the HLA type database;

[0018] A differential site determination module is used to compare the data after gene classification with a preset gene sequence to determine the differential site; the preset gene sequence is different from the sequence of each genotype in the HLA type database, and the differential site with each genotype is different;

[0019] An accurate candidate type determination module is used to link the differential sites into chains and compare them with the differential site database to obtain accurate candidate types; and an HLA typing result determination module is used to determine the HLA typing result based on the candidate type range and the accurate candidate type.

[0020] A third aspect of an embodiment of the present application provides a terminal device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of the HLA type determination method as described in any one of the first aspects above are implemented.

[0021] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, comprising: storing a computer program, characterized in that when the computer program is executed by a processor, the steps of the HLA type determination method as described in any one of the first aspects above are implemented.

[0022] A fifth aspect of an embodiment of the present application provides a computer program product. When the computer program product is executed on a terminal device, the terminal device executes the HLA type determination method described in any one of the first aspects above.

[0023] The HLA type determination method provided in the embodiment of the present application can directly analyze the HLA type results for normal HLA second-generation sequencing data samples without manual intervention, and will give corresponding prompt information for abnormal data such as HLA novel type samples, suspected mixed samples, and data unqualified samples, prompting manual review to check the situation of the problem samples and make corresponding processing. Compared with other HLA type analysis methods, on the one hand, the present application can identify the insertion and deletion differences between similar types and include them in the analysis, making the typing more accurate; on the other hand, the present application can identify novel type samples that are not in the HLA database, and give corresponding novel type results and prompt notes; on the other hand, the present application can identify complex sample situations such as mixed samples, contamination, and triploidy, and give prompts and notes. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of the HLA type determination method provided in the embodiment of the present application;

[0025] Figure 2 An analysis flow chart of the HLA type determination method provided in an embodiment of the present application;

[0026] Figure 3 Two possible linkage diagrams of SNPs provided in the examples of this application;

[0027] Figure 4 The SNP linkage map provided in the embodiments of the present application;

[0028] Figure 5 The abnormal data results output during the joint analysis process provided in the embodiment of the present application;

[0029] Figure 6 The HLA type analysis results provided in the examples of this application;

[0030] Figure 7 The verification results of the first-generation sequencing for the new gene samples provided in the embodiments of the present application;

[0031] Figure 8 is a schematic diagram of the structure of an HLA type determination device provided in an embodiment of the present application;

[0032] Fig. 9 It is a schematic diagram of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0034] like Figure 1-2As shown, the present application embodiment provides a method for determining HLA type, comprising the following steps:

[0035] Step S101, compare and screen the HLA second-generation sequencing data sample after quality control processing with the gene features of the HLA type database, and perform gene classification on the screened data.

[0036] In the embodiment of the present application, high-quality sequencing data is obtained by quality control and filtering of the HLA region second-generation sequencing (NGS) data samples from the offline data; conventional data filtering tools such as fastqc, SOAPnuke, and fastqp can be used to filter low-quality data and record the data quality. The effect is to eliminate the interference of low-quality data.

[0037] In an embodiment of the present application, the step of comparing and screening the HLA second-generation sequencing data sample after quality control processing with the gene features of the HLA type database, and performing gene classification on the screened data includes: comparing the HLA second-generation sequencing data sample after quality control processing with the gene features in the HLA type database, screening out data that meets the gene features, and performing gene classification in combination with a preset matching similarity threshold.

[0038] In the embodiment of the present application, the filtered data is compared with the HLA database, and the data is screened and filtered according to the characteristics of the HLA type database, only the data that meets the characteristics is retained, and the data is classified according to the HLA gene; here, BWA, SOAP, BLAST and other software can be used to compare with the entire HLA type database. Due to the high homology of each HLA gene and type and the incompleteness of some types of the HLA database, the compared data will have a single read that can be compared to different genes and different types at the same time, or the paired reads data R1 R2 are respectively compared to different genes and different types, or only one of the paired reads can be compared to a certain HLA type. The present application has formulated a set of rules based on the research on HLA characteristics, and only the data that meets the rules is selected for use, and the data that does not meet the rules will be filtered out. The rule can be to compare the data with the type sequence in the HLA type database. If multiple genes are matched, the gene classification is determined by matching the similarity threshold. The matching similarity threshold can be set according to the actual situation, such as 70%, 80%, etc. The effect is to eliminate the interference caused by data that does not meet the rules and classify the valid data by gene.

[0039] Step S102, determining the candidate type range of each gene based on the gene classification data and the HLA type database.

[0040] In an embodiment of the present application, the step of determining the candidate type range of each gene based on the data after gene classification and the HLA type database includes: calculating the coverage of all type exon ranges of the corresponding gene and the depth of each coverage site based on the data after gene classification and the HLA type database, and determining the candidate type range of each gene.

[0041] In the embodiment of the present application, the above data retained by gene classification is used to calculate the coverage of all types of exons of the corresponding gene and the depth of each coverage site to determine the possible candidate type range of the gene; here, BWA, SOAP, BLAST and other software can be used for comparison, and the reference ref (sequence) is the sequence of each HLA type, the purpose is to more accurately analyze the coverage of each possible correct type and obtain a correct candidate range. The effect is to obtain a correct typing range.

[0042] Step S103, comparing the gene-classified data with the preset gene sequence to determine the difference sites.

[0043] In the embodiment of the present application, the preset gene sequence is different from the sequence of each genotype in the HLA type database, and the difference sites of each genotype are different.

[0044] In the embodiment of the present application, the data retained by gene classification is compared with a preset gene sequence, i.e., a specific gene sequence, to obtain the difference sites between the data and the specific gene sequence. Here, software such as samtools or soapsnp can be used for operation. The effect is to obtain the difference sites between the data and the specific gene sequence.

[0045] The idea of ​​generating a specific gene sequence is to traverse all the types of sequences in the gene database to generate a specific sequence that is different from all the type sequences of the gene and all the types differ from this sequence differently, ensuring that each type of the gene can be accurately distinguished by the difference from the sequence.

[0046] Step S104, linking the differential sites into chains and comparing them with the differential site database to obtain accurate candidate types.

[0047] In the embodiment of the present application, the differential site database refers to the record of the differential sites between a specific sequence and each type. By searching the database, the differential sites obtained by aligning with the specific sequence can be matched to the corresponding type.

[0048] In the embodiment of the present application, before the step of linking the differential sites into chains and comparing them with the differential site database to obtain accurate candidate types, it also includes: performing noise reduction on the differential sites. Because the high homology of HLA causes the experiment to amplify homologous sequences when amplifying DNA fragments, the differential sites found are not all differential sites brought by the real HLA type, but some are "false" points brought by homologous sequences, which will cause great interference to the subsequent typing, so it is necessary to perform noise reduction on the differential sites according to the characteristics of HLA. The effect is to eliminate the analysis interference caused by noise.

[0049] In an embodiment of the present application, the step of linking the differential sites into chains and comparing them with the differential site database to obtain accurate candidate types includes: linking the differential sites into chains to determine the linkage relationship between the differential sites; according to the linkage relationship between the differential sites, connecting two adjacent differential sites in sequence and continuously extending them to determine the differential site linkage relationship of the entire exon and the target linkage chain; comparing the target linkage chain with the differential site database to obtain accurate candidate types.

[0050] Furthermore, the step of connecting two adjacent differential sites in sequence and continuously extending them according to the linkage relationship between the various differential sites to determine the differential site linkage relationship of the entire exon and the target linkage chain includes: connecting two adjacent differential sites in sequence and continuously extending them according to the linkage relationship between the various differential sites to determine the differential site linkage relationship of the entire exon; determining one or two pre-selected linkage chains with the most support according to the differential site linkage relationship and the sequence support number information of each differential site; clustering the differential site sequences according to the differential sites on the pre-selected linkage chains to divide the differential site sequences into two categories, and constructing two target linkage chains based on the comparison results of the differential site sequences.

[0051] In the present application example, the relationship between the differential sites is analyzed, all sites are linked into two chains, and possible linkages are screened according to the HLA type characteristics. The determination of the linkage relationship of the differential sites is divided into two steps. Step 1, determine the linkage relationship of the two SNP sites. In theory, there will only be two types of connection between two heterozygous SNPs, direct 1 to 1 and 2 to 2, or 1 to 2 and 2 to 1, and no other linkage methods will appear. Figure 3As shown, the linkage relationship between the two SNP sites is determined based on the sequence support number passing through each site and the sequence support number passing through the two sites at the same time. Only two linkage relationships are retained at most (because humans are diploid, there are only two types of SNP linkage at most, so there are only two cases of linkage relationship between every two sites at most). Here, try to determine the linkage relationship of two SNP sites as much as possible. Ideally, the linkage relationship of any two sites can be determined. However, due to reasons such as sequencing fragment length, sequencing depth and sequencing errors, the SNP linkage relationship of some two sites may not be determined. Step two, integrate the linkage relationship of the two SNP sites obtained in the previous step, connect the two adjacent SNP sites in sequence, and continue to extend to determine the SNP linkage relationship of the entire exon, such as Figure 4 As shown. The more SNP linkage relationships determined here, the more false positives will be generated, and screening and filtering are required according to HLA type characteristics. Finally, the chain is compared with the differential site database to obtain the candidate type, and the final typing result is obtained by joint analysis with the above candidate type range.

[0052] Among them, the linkage relationship of the differential loci (SNPs) refers to the relationship between the two SNPs that has been determined in the previous step, such as Figure 4 As shown in the figure, once the relationship between two sites such as SNP1 and SNP2, SNP2 and SNP3, and SNP1 and SNP3 is determined, the linkage relationship between the three differential sites SNP1, SNP2, and SNP3 can be determined. The relationship between SNPs can be slowly extended by analogy until the relationship between all SNPs on the entire exon is determined to form a SNP linkage chain. Because humans are diploid, ideally, homozygous genes can be linked to one SNP linkage chain, and heterozygous genes can be linked to two SNP linkage chains. However, due to the various influencing factors mentioned above, it is often possible to link multiple SNP linkage chains. In this case, reads clustering is required for further filtering and noise reduction.

[0053] In the embodiment of the present application, reads will be clustered according to the SNP linkage relationship. Through clustering, reads are divided into two categories. Clustering reads is to further determine the linkage relationship of SNP. Certain errors may occur when determining SNPs in the previous steps: 1. There may be false SNP sites, or the sites may be determined as heterozygous SNPs or heterozygous SNPs may be determined as homozygous; 2. When the SNP linkage relationship is determined, individual SNP sites cannot be determined when linked due to reasons such as the length of the second-generation sequencing read; 3. Linkage errors caused by errors introduced by PCR errors or sequencing errors. Most of the above problems can be solved through this step. Reads clustering is to select the two most likely SNP linkage relationships from the previous step, cluster reads according to the SNPs on the two linkage relationships, divide reads into two categories, and then construct two linkage chains for the comparison results of these reads. After this step, the output SNP linkage chain has a high credibility, and combined with the previous candidate type range frame, the final output type is determined. In this step, how to select the two best SNP linkage relationships for clustering is the key. It is necessary to consider various conditions based on the previously obtained preliminary SNP relationship and the number of sequence support for each SNP site. Among them, SNPs are all on reads. When the chain of SNPs linked together is obtained, we can look back to see how many reads can support the SNP chain, and then traverse all reads to obtain the number of reads support for each SNP chain, so as to determine the one or two SNP chains with the most support. For those that cannot accurately select two linkage relationships after various conditions are judged, they will be judged as suspected contaminated samples or mixed samples. The software will give a prompt and use the best matching chain to give a possible result.

[0054] Step S105, determining the HLA type result according to the candidate type range and the precise candidate type.

[0055] In the embodiment of the present application, the above candidate type range and precise candidate type are jointly analyzed, and when data anomalies are found, problem indications are output in a timely manner, such as Figure 5 The data output during the joint analysis process shown in the figure is abnormal. At this time, it has been determined that the A gene of the sample is heterozygous, and one of the types is A 02:07:01, another type and A 32:01:01 is the closest, but there is always one SNP that does not match the type, so the final output is: A 02:07:01+A 32:01NEW, and notes the site information that needs to be reviewed and noted. In addition, this application also provides corresponding new type results and prompt notes for the identified new type samples that are not in the HLA database, such as Figure 6 The HLA typing analysis results shown in the figure show that the A gene of sample TB06851 has a new gene mutation, which indicates that a review is needed. The mutation site is G -> C mutation at the 222nd base of exon 3, with a mutation frequency of 38%. In order to further verify the new type of sample, Figure 7 As shown, the HLA typing "gold standard" first-generation sequencing was used to verify sample TB06851. According to the first-generation results, the data were compared with the closest A 32:01:01, the G -> C mutation was indeed found in exon 3, indicating that this is indeed an A 32:01NEW new alleles.

[0056] The HLA type determination method provided in the embodiment of the present application is a method for analyzing the six HLA genotypes of human leukocytes, including HLA-I class genes HLA-A, HLA-B, HLA-C and HLA-II class genes HLA-DPB1, HLA-DQB1, HLA-DRB1, and the data analyzed is the sequencing data of NGS sequencing of the human HLA gene region. The present application can directly analyze the HLA type results for normal HLA second-generation sequencing data samples without manual participation, and will give corresponding prompt information for abnormal data such as HLA new type samples, suspected mixed samples, and data unqualified samples, prompting manual review to check the situation of the problem samples and make corresponding processing. Compared with other HLA type analysis methods, on the one hand, the present application can identify the insertion and deletion differences between similar types and include them in the analysis, and the typing is more accurate; on the other hand, the present application can identify new type samples that are not in the HLA database, and give corresponding new type results and prompt notes; on the other hand, the present application can identify complex sample situations such as mixed samples, contamination and triploids, and give prompts and notes.

[0057] Corresponding to the method of the above embodiment, Figure 8 A structural block diagram of an HLA type determination device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown. Figure 8 The exemplary HLA type determination device may be an execution subject of the HLA type determination method provided in the aforementioned embodiment.

[0058] Reference Figure 8 , the HLA type determination device comprises:

[0059] Gene classification module 810, used to compare and screen the HLA second-generation sequencing data sample after quality control with the gene features of the HLA type database, and perform gene classification on the screened data;

[0060] The candidate type range determination module 820 is used to determine the candidate type range of each gene based on the gene classification data and the HLA type database;

[0061] The difference site determination module 830 is used to compare the gene classification data with the preset gene sequence to determine the difference site; the preset gene sequence is different from the sequence of each genotype in the HLA type database, and the difference site with each genotype is different;

[0062] The precise candidate type determination module 840 is used to link the differential sites into chains and compare them with the differential site database to obtain precise candidate types; and the HLA typing result determination module 850 is used to determine the HLA typing result based on the candidate type range and the precise candidate type.

[0063] The accurate candidate type determination module 840 includes:

[0064] A linkage relationship determination unit, used to link the differential sites into chains and determine the linkage relationship between the differential sites;

[0065] A target linkage chain determination unit is used to connect two adjacent differential sites in sequence and continuously extend them according to the linkage relationship between the differential sites, so as to determine the differential site linkage relationship of the entire exon and the target linkage chain; and a selected candidate type determination unit is used to compare the target linkage chain with the differential site database to obtain an accurate candidate type.

[0066] The process of each module in the HLA type determination device provided in the embodiment of the present application realizing its own function can be specifically referred to the aforementioned Figure 1 The description of the illustrated embodiment will not be repeated here.

[0067] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0068] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0069] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0070] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0071] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish descriptions, and cannot be understood as indicating or suggesting relative importance. It should also be understood that although the terms "first", "second", etc. are used to describe various elements in some embodiments of the present application in the text, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, the first table can be named as the second table, and similarly, the second table can be named as the first table without departing from the scope of the various described embodiments. The first table and the second table are both tables, but they are not the same table.

[0072] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0073] The HLA type determination method provided in the embodiments of the present application can be applied to terminal devices such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc. The embodiments of the present application do not impose any restrictions on the specific types of terminal devices.

[0074] For example, the terminal device can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a TV set top box (STB), a customer premises equipment (CPE) and / or other devices for communicating on a wireless system and a next-generation communication system, such as a mobile terminal in a 5G network or a mobile terminal in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0075] As an example but not limitation, when the terminal device is a wearable device, the wearable device can also be a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not just hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include those that are fully functional, large in size, and can achieve complete or partial functions without relying on smartphones, such as smart watches or smart glasses, as well as those that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets and smart jewelry for vital sign monitoring.

[0076] Fig. 9Schematic diagram of the structure of a terminal device provided by an embodiment of the present application. Fig. 9 As shown, the terminal device 7 of this embodiment includes: at least one processor 70 ( Fig. 9 Only one is shown in the figure), a memory 71, wherein the memory 71 stores a computer program 72 that can be run on the processor 70. When the processor 70 executes the computer program 72, the steps in the above-mentioned HLA type determination method embodiments are implemented, such as Figure 1 Alternatively, when the processor 70 executes the computer program 72, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 8 Functions of modules 810 to 850 are shown.

[0077] The terminal device 7 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device may include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art will appreciate that Fig. 9 It is only an example of the terminal device 7 and does not constitute a limitation on the terminal device 7. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include an input sending device, a network access device, a bus, etc.

[0078] The processor 70 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0079] In some embodiments, the memory 71 may be an internal storage unit of the terminal device 7, such as a hard disk or memory of the terminal device 7. The memory 71 may also be an external storage device of the terminal device 7, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 7. Further, the memory 71 may include both an internal storage unit and an external storage device of the terminal device 7. The memory 71 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 71 may also be used to temporarily store data that has been sent or is to be sent.

[0080] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0081] An embodiment of the present application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor, wherein when the processor executes the computer program, the terminal device implements the steps in any of the above-mentioned method embodiments.

[0082] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0083] An embodiment of the present application provides a computer program product. When the computer program product runs on a terminal device, the terminal device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0084] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0085] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0086] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0087] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0088] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for determining HLA type, characterized in that: include: The HLA second-generation sequencing data samples after quality control are compared and screened with the gene features of the HLA type database, and the screened data are genetically classified; Based on the data after gene classification and the HLA type database, the coverage of all types of exons of the corresponding gene and the depth of each covered site are calculated to determine the candidate type range of each gene; Compare the gene classification data with the preset gene sequence to determine the difference sites; the preset gene sequence is different from the sequence of each genotype in the HLA type database, and the difference sites with each genotype are different; The differential sites were subjected to noise reduction; The differential sites are linked into chains and compared with the differential site database to obtain accurate candidate types; Determine the HLA type result according to the candidate type range and the precise candidate type; The step of determining the HLA type result according to the candidate type range and the precise candidate type includes: Conduct joint analysis on the candidate type range and precise candidate type, and output problem indication in time when data anomalies are found; For the identified new type samples that are not in the HLA database, the corresponding new type results and prompt notes are given.

2. The HLA type determination method according to claim 1, characterized in that: The step of comparing and screening the HLA second-generation sequencing data sample after quality control with the gene features of the HLA type database, and performing gene classification on the screened data includes: The HLA second-generation sequencing data samples after quality control processing are compared with the gene features in the HLA type database, the data that meets the gene features are screened out, and the genes are classified based on the preset matching similarity threshold.

3. The HLA type determination method according to claim 1, characterized in that: The step of linking the differential sites into chains and comparing them with the differential site database to obtain accurate candidate types includes: Link the differential sites into chains and determine the linkage relationship between the differential sites; According to the linkage relationship between the various differential sites, two adjacent differential sites are sequentially connected and continuously extended to determine the linkage relationship of the differential sites of the entire exon and the target linkage chain; The target linkage chain is compared with the differential site database to obtain accurate candidate types.

4. The HLA type determination method according to claim 3, characterized in that: The step of sequentially connecting two adjacent differential sites and continuously extending them according to the linkage relationship between the differential sites to determine the linkage relationship of the differential sites of the entire exon and the target linkage chain includes: According to the linkage relationship between the various differential sites, two adjacent differential sites are sequentially connected and continuously extended to determine the linkage relationship of the differential sites of the entire exon; Determine one or two pre-selected linkage chains with the most support according to the linkage relationship of the difference sites and the sequence support number information of each difference site; According to the differential sites on the preselected chain, the differential site sequences are clustered to divide the differential site sequences into two categories, and two target chain are constructed based on the comparison results of the differential site sequences.

5. An HLA type determination device, characterized in that: include: The gene classification module is used to compare and screen the HLA second-generation sequencing data samples after quality control with the gene characteristics of the HLA type database, and to perform gene classification on the screened data; A candidate type range determination module is used to determine the candidate type range of each gene based on the gene classification data and the HLA type database; A differential site determination module is used to compare the data after gene classification with a preset gene sequence to determine the differential site; the preset gene sequence is different from the sequence of each genotype in the HLA type database, and the differential site with each genotype is different; An accurate candidate type determination module is used to link the differential sites into chains and compare them with the differential site database to obtain accurate candidate types; and an HLA typing result determination module is used to determine the HLA typing result based on the candidate type range and the accurate candidate type; The step of determining the candidate type range of each gene based on the gene classification data and the HLA type database includes: Based on the data after gene classification and the HLA type database, the coverage of all types of exons of the corresponding gene and the depth of each covered site are calculated to determine the candidate type range of each gene; Before the step of linking the differential sites into chains and comparing them with the differential site database to obtain accurate candidate types, the step also includes: performing noise reduction processing on the differential sites; The step of determining the HLA type result according to the candidate type range and the precise candidate type includes: The candidate type range and the precise candidate type are jointly analyzed, and problem indications are output in a timely manner when data anomalies are found; for the identified new type samples that are not in the HLA database, corresponding new type results and prompt notes are given.

6. The HLA type determination device according to claim 5, characterized in that: The precise candidate type determination module comprises: A linkage relationship determination unit, used to link the differential sites into chains and determine the linkage relationship between the differential sites; A target linkage chain determination unit is used to connect two adjacent differential sites in sequence and continuously extend them according to the linkage relationship between the differential sites, so as to determine the differential site linkage relationship of the entire exon and the target linkage chain; and a selected candidate type determination unit is used to compare the target linkage chain with the differential site database to obtain an accurate candidate type.

7. A terminal device, characterized in that: The terminal device includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the steps of the HLA type determination method according to any one of claims 1 to 4 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the HLA type determination method according to any one of claims 1 to 4 are implemented.

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