Genotyping method, device and storage medium for short tandem repeat sequences and their flanks

Abstract

The application discloses a short tandem repeat sequence and a genotyping method, device and storage medium thereof. The genotyping method comprises the following steps: aligning a sequence to be analyzed with a reference genome to obtain STR site information of the sequence to be analyzed; correcting mutations by using a sequence correction method; then, judging the STR genotyping of the sequence to be analyzed by arranging support allele sequences from large to small, calculating the proportion of alleles, and the like; and the reference genome comprises a plurality of known STR core repeat regions and upstream and downstream flanking sequences thereof, and a "plus-minus one" buffer library for simulating increase or decrease of one repeat unit of the known STR core repeat region. The application uses a specially constructed STR sequence library as the reference genome, expands the alignment range, calculates more accurately, improves the genotyping accuracy, removes amplification and sequencing error data through sequence correction, improves the effective depth of genotyping, and makes the genotyping result more reliable.

Description

Technical Field

[0001] This application relates to the field of short tandem repeat sequence and flanking gene detection technology, and in particular to a genotyping method, apparatus and storage medium for short tandem repeat sequences and their flanking genes. Background Technology

[0002] Short tandem repeats (STRs) are typically repetitive DNA sequences consisting of 1 to 6 base units in the genome. Due to the high variability and abundance of the number of core repeat units among individuals, STR loci exhibit genetic polymorphism. As the most widely used genetic marker in forensic genetics, they are currently primarily detected using capillary electrophoresis (CE). In DNA genotyping applications of STRs, a fluorescent dye is linked to a polymerase chain reaction (PCR) primer, and the amplified product is incorporated into the target DNA. The amplified STR alleles appear as bands on the gel or as peaks in the electrophoretic pattern.

[0003] However, traditional CE platforms have the following limitations: (1) the number of samples and STR loci that can be detected simultaneously is limited; (2) the CE platform can only identify the length of STR alleles, but cannot identify their sequence polymorphism.

[0004] Thanks to the significant advancements in sequencing speed, throughput, and read length achieved by massively parallel sequencing (MPS) technology, simultaneous analysis and further sequence interpretation of large-scale samples have become possible, leading to the development of STR genotyping methods based on massively parallel sequencing, namely MPS-STR.

[0005] MPS-STR sequencing data analysis mainly includes four steps: data preprocessing, reference genome comparison, allele detection, and genotyping.

[0006] The "data preprocessing" step is used for preparatory work before analysis. In addition to filtering low-quality data, some methods also sort the raw data, mark duplicates, and unify the sequence direction to reduce redundant analysis and speed up the analysis process.

[0007] The "reference genome comparison" step, based on the preprocessed raw data, clusters the sequences to be analyzed by comparing them with known target genome sequences, distributing the raw data into different STR genetic markers, and distinguishing between "flanking regions" and "repetitive regions" of the sequences to be analyzed based on known STR characteristics. "Flanking regions" are generally complex base combinations, possessing uniqueness and serving as identifiers for different STRs. "Repetitive regions" are DNA repeat sequences consisting of 1 to 6 base units, i.e., STRs, with the same number of repetitions as the STR allelic typing on the CE platform.

[0008] The "allele detection" step involves statistically analyzing the information from the aforementioned "repetitive regions" to obtain the DNA repetitive sequences and the number of sequences supported by the corresponding alleles in the STR. The number of repetitions for different repetitive units is then calculated to generate the identification results.

[0009] Existing technologies differ significantly in their alignment methods used in the "reference genome comparison" step. For example, the patent "A Method for Detecting and Generating the Repeat Count of Short Tandem Repeat Sequences" (patent number 202110669050.9) mentions aligning the sequence to be analyzed with an STR reference sequence library. The sequence to be analyzed is composed of a left flanking sequence, a right flanking sequence, and the original sequence. The STR reference sequence library is composed of the left and right flanking sequences assembled sequentially. Then, the repetitive regions in the sequence to be analyzed are anchored using a dynamic threshold setting. Based on the length of the repetitive region sequence anchored to each read, the repeat count of the STR sites aligned to each read is calculated. In contrast, the commonly used STR genotyping software, StraitRazor (https: / / github.com / Ahhgust / STRaitRazor), uses the flanking sequences as anchor points. After matching the flanking sequences to the original sequence, the original sequence is cut, retaining only the core repetitive region. Then, the sequence of this repetitive region is compared with the repetitive region sequences of known alleles to calculate the repeat count of the repetitive unit. Both methods effectively distinguish alleles at STR loci and correlate the number of supported sequences with the peak values ​​of the CE platform, providing data support for subsequent genotyping. However, the sequencing sequence anchoring method focuses on repetitive regions, making it difficult to detect mutations in flanking regions, thus limiting the sequence polymorphism of STRs.

[0010] In the "genotyping" stage, after obtaining the alleles and their supporting sequence numbers (reads) in different STRs through the above steps, further genotyping of the STRs is required. Patent 202110669050.9 proposes that when two alleles are adjacent, the effect of the previously found peaks is removed. This patent calculates genotyping by setting three fixed parameters: left threshold gradient, right threshold gradient, and initial gradient. However, this method is not applicable to samples produced by different sequencing platforms or kits.

[0011] In summary, existing STR genotyping methods based on massively parallel sequencing have the following shortcomings: (1) Insufficient utilization of STR genotyping polymorphisms. Existing technologies only consider allelic genotyping of repetitive regions, which is consistent with the genotyping of the previous CE platform. They lack detection schemes for possible single nucleotide polymorphisms (SNPs) or insertion / deletion (InDels) variations in the flanking regions of STRs; (2) Low data utilization. MPS data generated by the multiplex amplification principle has inherent mechanical errors. Existing methods will filter out a large number of invalid data by simply filtering with conventional quality values ​​or sorting to remove duplicates; (3) Low accuracy of genotyping algorithms, or high accuracy only in specific data but with a narrow scope of application. The accuracy is generally low when facing more different samples; (4) Poor readability of genotyping results. MPS data displays excessively long original sequences, which is not user-friendly for analysts to read and for database recording. Summary of the Invention

[0012] The purpose of this application is to provide a novel method, apparatus, and storage medium for genotyping short tandem repeat sequences and their flanking segments.

[0013] To achieve the above objectives, this application adopts the following technical solution:

[0014] The first aspect of this application discloses a genotyping method for short tandem repeat sequences and their flanking sequences, comprising: aligning the sequence to be analyzed with a reference genome to obtain STR site information of the sequence to be analyzed; correcting mutations in the sequence to be analyzed using a sequence correction method to remove noise sequences caused by amplification or sequencing errors; obtaining the allele sequence, allele length genotyping, and flanking mutation genotyping of the corrected sequence to be analyzed; and determining the STR genotyping of the sequence to be analyzed by arranging the support allele sequence numbers from largest to smallest and calculating the allele ratio; wherein, the reference genome is an STR sequence library, the STR sequence library includes several known STR core repeat region sequences and their upstream and downstream flanking sequences, as well as a buffer library capacity of "plus or minus one"; the buffer library capacity of "plus or minus one" includes sequences that simulate adding one repeat unit to the core repeat region sequence of a known STR, and sequences that simulate removing one repeat unit from the core repeat region sequence of a known STR.

[0015] It should be noted that the genotyping method of this application uses an STR sequence library containing the core repeat region sequence and its upstream and downstream flanking sequences as the reference genome. Compared with existing alignment methods that only anchor a small range of 10-30 bp flanking sequences, the method of this application expands the comparable range and minimizes the occurrence of alignment failures due to flanking sequence variations. In addition, the buffer library capacity of "adding or subtracting one" makes the calculation of complex repeat structures or non-counting units of STR sites more accurate, rather than simply calculating the length of the core region for genotyping. Therefore, the method of this application is more accurate than previous genotyping methods that only focus on the repeat region structure.

[0016] In one implementation of this application, the buffer capacity of "adding or subtracting one" specifically includes, when the known allele range of a STR locus is between m and n, constructing the sequence of core repeat region m-1 and the sequence of core repeat region n+1 based on the simulation of adding or subtracting one repeat unit in the core repeat region of the STR.

[0017] In one implementation of this application, the flanking sequence is specifically defined as the sequence of 200bp upstream and downstream of the same STR locus as the flanking sequence of that STR locus.

[0018] In one implementation of this application, the STR site information includes the sequence number of STR sites, alignment position, base matching status, allele length genotyping, and flanking mutation genotyping.

[0019] In one implementation of this application, the sequence to be analyzed is compared with a reference genome to obtain the STR site information of the sequence to be analyzed. Specifically, this includes comparing all STR alleles in the STR sequence library with the sequence to be analyzed one by one. If the sequence to be analyzed is compared with multiple alleles, the one with the highest alignment quality value is selected as the best alignment. The STR site and STR site information of the sequence to be analyzed are determined based on the best alignment.

[0020] In one implementation of this application, the STR site and STR site information of the sequence to be analyzed are determined based on the best alignment. Specifically, the best alignment is STR site A, whose core repeat region has a total length of L bases, repeat unit length is m bases, and there are n bases in uncounted units. Based on the alignment results, variation analysis of the core repeat region and flanking sequences is performed in the following three cases:

[0021] a. If the sequence to be analyzed is completely consistent with the STR sequence library, then the allele length of the sequence to be analyzed is consistent with the record in the STR sequence library, and there are no flanking mutations, so the allele length typing of the sequence to be analyzed can be obtained directly;

[0022] b. When the core repeat sequence of the sequence to be analyzed differs from the STR sequence library, the starting position of the core repeat region of the sequence to be analyzed is determined by re-alignment. Let the starting and ending coordinates of the core repeat region of the best aligned STR site A be p1 and p2, respectively, and let the insertion or deletion position that causes the change in the length of the core repeat region be p3. The number of inserted or deleted bases is denoted as w, where w is positive for insertion and negative for deletion. Depending on the position of the insertion or deletion relative to the core repeat region, the total length L of the core repeat region of the sequence to be analyzed is denoted as:

[0023]

[0024] Calculate the allele length genotype 'a' of the sequence to be analyzed using the following formula.

[0025]

[0026] Where L is the total length of the core repeat region of the sequence to be analyzed, m is the length of the repeat unit of the best aligned STR site A, and n is the length of the uncounted unit of the best aligned STR site A. If there is no uncounted unit, then the value of n is 0.

[0027] c. When the flanking sequence regions of the sequence to be analyzed differ from the STR sequence library, the distance and direction of the flanking mutation relative to the core repeat region are determined by re-alignment. A flanking mutation occurring upstream of the core repeat region is recorded as negative ("-"), and a flanking mutation occurring downstream of the repeat region is recorded as positive ("+"). Let the start and end coordinates of the core repeat region be p1 and p2. When multiple flanking mutations exist in the same direction, they are sorted according to their variation coordinates from the 5' end to the 3' end and recorded as p3, p4, ..., p2. n The number of bases involved in the mutation is denoted as q3, q4, ..., q n When the mutation type is a single-base mutation or deletion, q = 0, meaning it does not affect the relative position of flanking mutations. When the mutation type is an insertion, the number of inserted bases closer to the core repeat region is subtracted to match the insertion position; that is, the calculation is performed from the inside out. Taking the upstream of the core repeat region as an example, the insertion variation closest to the core repeat region is p. n Their relative distance is denoted as P. n The calculation formula is P n =p n -p1;

[0028] Then the relative position P of the upstream variation n-1 = Original relative position - Total number of inserted bases closer to the repeating region, i.e., P n-1 =p n-1 -p1-q n ;

[0029] By analogy, the relative positions of the flanking mutations are calculated and the base changes are recorded to obtain the flanking mutation genotype.

[0030] In one implementation of this application, a sequence correction method is used to correct mutations in the sequence to be analyzed. Specifically, this includes clustering sequences from the same DNA template before sequence correction, ensuring that the sequences to be corrected meet the following requirements: a) all sequences to be corrected align to the same STR sequence library reference sequence; b) the sequences to be corrected completely cover the core repetitive region. Then, by comparing with the STR sequence library, all mutation information is statistically analyzed. For a single locus to be corrected, the frequency of all detected mutations is counted, i.e., M1, M2, ..., M... i Based on the total number N of sequences to be corrected that are compared to the reference sequences in the same STR sequence library, the proportion of each mutation, RM=M, is calculated. i / N; When the proportion of mutations RM is greater than the preset threshold A, the mutation is counted as a reliable mutation; otherwise, it is considered a sequencing error and removed.

[0031] It should be noted that the threshold A in this application is a threshold set based on the proportion of major alleles and minor alleles at heterozygous loci, which theoretically each account for 50%, and in combination with actual sequencing data.

[0032] In one implementation of this application, the STR genotype of the sequence to be analyzed is determined by arranging the number of allele sequences from largest to smallest and calculating the allele ratio. Specifically, this includes defining the allele with the largest number of supporting sequences at each locus as the baseline peak, and defining the specific STR genotype based on the allele coverage ratio (ACR), i.e., the depth ratio of the minor alleles relative to the baseline peak, where 0 < ACR ≤ 1.

[0033] It should be noted that the ACR in this application refers to the definition in the 2024 edition of the "Basic Standards for Quality of Next-Generation Sequencing Reagents": when the locus type is heterozygous, the ratio of the lower value to the higher value of the two alleles. The minor allele in this application is the lower value in the aforementioned definition.

[0034] In one implementation of this application, the method for defining specific STR genotypes includes setting a "Balance" threshold ratio as T1, a "Subtract One Stutter" threshold ratio as T2, and a "Noise" threshold ratio as T3; when ACR ≥ T1, the allele will be labeled "Pass"; when T1 ≥ ACR ≥ T2, the allele will be labeled "Imbanlance"; if T2 ≥ ACR ≥ T3, and the difference between the allele length genotype and the baseline peak is less than or equal to 1, the allele is labeled "Subtract One Stutter". Alleles greater than 1 are labeled "Imbanlance"; when ACR < T3, the allele is labeled "Noise" and does not participate in genotyping; based on the known locus ploidy, in the case of non-multiple copies, the ploidy of the autosomal locus is 2, and the ploidy of the male X chromosome locus is 1. The alleles with the ploidy number of the locus labeled "Pass" and "Imbalance" are output as the STR genotyping of the sequence to be analyzed; for mixed samples or special samples, when the number of alleles exceeding the ploidy number reaches the "Pass" threshold requirement, they are output as the STR genotyping of the sequence to be analyzed.

[0035] In one implementation of this application, the genotyping method further includes allele sequence folding; allele sequence folding includes replacing the repeating sequence of STR with [X]a, where X is the repeating unit sequence corresponding to the repeating sequence, and a is the number of repetitions of the repeating unit sequence.

[0036] The second aspect of this application discloses a genotyping device for short tandem repeat sequences and their flanking sequences, including a reference genome module, an alignment module, a correction module, and an STR genotyping module. The reference genome module is used to acquire or store a reference genome, which is an STR sequence library. The STR sequence library includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer capacity of "plus or minus one". The buffer capacity includes sequences that simulate adding one repeat unit to the core repeat region sequence of a known STR, and sequences that simulate removing one repeat unit from the core repeat region sequence of a known STR. The alignment module is used to align the sequence to be analyzed with the reference genome to obtain the STR site information of the sequence to be analyzed. The correction module is used to correct mutations in the sequence to be analyzed using sequence correction methods, removing noise sequences caused by amplification or sequencing errors. The STR genotyping module is used to obtain the allele sequence, allele length genotyping, and flanking mutation genotyping of the corrected sequence to be analyzed, and to determine the STR genotyping of the sequence to be analyzed by arranging the allele sequence numbers from largest to smallest and calculating the allele ratio.

[0037] It should be noted that the genotyping device for short tandem repeat sequences and their flanking parts in this application is actually implemented by each module separately as part of the genotyping method for short tandem repeat sequences and their flanking parts in this application. Therefore, the specific limitations of each module can be referenced in the genotyping method for short tandem repeat sequences and their flanking parts in this application. For example, specific STR site information, "addition and subtraction" buffer capacity, confirmation of optimal alignment, sequence correction, delineation of specific STR genotypes, allele sequence folding, etc., can all refer to the genotyping method for short tandem repeat sequences and their flanking parts in this application.

[0038] A third aspect of this application discloses a genotyping device for short tandem repeat sequences and their flanking parts, the device comprising a memory and a processor; the memory includes a program for storing programs; the processor includes a method for implementing the genotyping method for short tandem repeat sequences and their flanking parts of this application by executing the programs stored in the memory.

[0039] The fourth aspect of this application discloses a computer-readable storage medium storing a program that can be executed by a processor to implement the genotyping method for short tandem repeat sequences and their flanking parts as described in this application.

[0040] Due to the adoption of the above technical solutions, the beneficial effects of this application are as follows:

[0041] The genotyping method and apparatus for short tandem repeat sequences and their flanking sequences in this application creatively employs an STR sequence library containing the core repeat region sequence and its upstream and downstream flanking sequences as a reference genome, and adds a buffer capacity of "plus or minus one" to the STR sequence library, which not only expands the comparable range, but also makes the calculation more accurate, thereby improving the accuracy of short tandem repeat sequence genotyping; through sequence correction, amplification and sequencing errors in the data are removed, thereby improving the effective depth of short tandem repeat sequence genotyping and making the genotyping results more reliable. Attached Figure Description

[0042] Figure 1 This is a schematic diagram illustrating the construction of the STR sequence library in an embodiment of this application;

[0043] Figure 2 This is a schematic diagram illustrating the identification of core repeating regions and flanking sequence variations in an embodiment of this application;

[0044] Figure 3 This is a schematic diagram illustrating the sequence correction principle in an embodiment of this application;

[0045] Figure 4 This is a schematic diagram of the STR typing threshold design in an embodiment of this application. Detailed Implementation

[0046] The present application will now be described in further detail with reference to specific embodiments and accompanying drawings. In the following embodiments, many details are described to facilitate a better understanding of the present application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other devices, materials, or methods. In some cases, certain operations related to the present application are not shown or described in the specification to avoid obscuring the core parts of the application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; a complete understanding of the related operations can be obtained from the description in the specification and general technical knowledge in the art.

[0047] To address the shortcomings of existing short tandem repeat (STLL) genotyping methods, such as insufficient polymorphism utilization, low data utilization, low accuracy of genotyping algorithms, and poor readability of genotyping results, this application develops a novel genotyping method for STLL sequences and their flanking sequences. This method involves aligning the sequence to be analyzed with a reference genome to obtain the STR locus information of the sequence; using sequence correction methods to correct mutations in the sequence to be analyzed and remove noise sequences caused by amplification or sequencing errors; obtaining the corrected allele sequence, allele length genotyping, and flanking mutation genotyping of the sequence to be analyzed; and determining the STR genotyping of the sequence to be analyzed by arranging the allele sequence numbers from largest to smallest and calculating the allele ratio. The reference genome is an STR sequence library, which includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer capacity of "plus or minus one". The "plus or minus one" buffer capacity includes sequences that simulate adding one repeat unit to the core repeat region sequence of a known STR, and sequences that simulate removing one repeat unit from the core repeat region sequence of a known STR.

[0048] In this application, the sequence to be analyzed refers to sequencing result data that has undergone routine preprocessing such as sequencing adapter sequence removal and low-base quality filtering. Specific sequencing data quality inspection and filtering refer to existing technologies and are not specifically limited here.

[0049] The genotyping method for short tandem repeat sequences and their flanking segments described in this application is mainly divided into five parts: STR sequence library, alignment, correction, STR genotyping, and allele sequence folding. The STR sequence library is a reference genome sequence library specifically developed and constructed to address the technical problem to be solved in this application. It can be understood that once the STR sequence library is constructed, it can be used directly without repeated construction each time, unless it needs to be expanded, such as by adding new known STR locus information. Furthermore, allele sequence folding is a further solution proposed in this application to address the problem of poor readability of genotyping results. If the sole purpose is to improve genotyping accuracy, allele sequence folding can be omitted.

[0050] The five parts of the genotyping method in this application are described in detail below:

[0051] (1) STR sequence library

[0052] Unlike existing technologies that only compare the flanking sequences of STRs to the STR loci in MPS data, this application constructs a complete STR sequence library before performing reference genome alignment. In one implementation of this application, a total of 218 STR core repeat sequences and their upstream and downstream flanking sequences are included. Considering the need for flanking variation detection, the positions of all STR loci in the GRCh38 version of the reference genome have been determined in advance. The 200bp sequences upstream and downstream of the same STR locus in the reference genome are extracted as the flanking sequences of the STR, and then spliced ​​with the STR core region sequences with known allele ranges to obtain an STR sequence library covering all common alleles.

[0053] Accordingly, considering the common stuttering phenomenon in STR amplification (in the strand slip mismatch model, a region of the primer-template complex mismatches during primer extension, forming a polymerase slip product with a length difference of several bases compared to the target allele), a "plus or minus one" buffer capacity was designed when constructing the sequence library. That is, when the known allele range for a STR site is between m and n, the addition or subtraction of one repeat unit is simulated based on the STR's repeat structure (assuming it's a [GATA] repeat), constructing [GATA]m-1 and [GATA]n+1 sequences, such as... Figure 1 As shown. This avoids alignment misalignment caused by a large difference in length between the sequence to be analyzed and the sequence library during the alignment process.

[0054] By simulating a large allele sequence library by splicing the core repeat sequence and its upstream and downstream flanking sequences, the comparison range is expanded compared to the existing alignment method that only anchors a small range of flanking sequences (10-30bp). This can minimize the possibility of alignment failure due to special variations in the flanking sequences. In addition, the presence of simulated allele core sequences makes the calculation of complex repeat structures or non-counting units at certain STR sites more accurate, rather than simply calculating the length of the core region for genotyping.

[0055] (2) Comparison

[0056] By aligning the aforementioned STR sequence library with the sequence to be analyzed using a reference genome, the number of sequences aligned to the STR locus, the alignment position, and the base matching can be obtained. However, due to the high similarity between alleles at the same STR locus in the sequence library, common alignment software has the problem of randomly selecting alignments when processing similar reference genomes, and cannot traverse all STR sequences in the sequence library. This application modifies the -N parameter of the sequence alignment software minimap2 (https: / / github.com / lh3 / minimap2) to make it greater than the maximum number of alleles for any STR in the sequence library. All STR alleles in the sequence library are aligned with the sequence to be analyzed one by one. When the sequence to be analyzed is aligned to multiple alleles, the one with the highest alignment quality value is selected as the best alignment.

[0057] After determining the STR site corresponding to the sequence to be analyzed based on the best alignment, it is necessary to identify its core repeats and flanking variations. Assuming the best alignment in the sequence library is STR site A, the total length of the core repeat region is L bases, and its characteristic repeat units are predefined as repeats of m bases in length, with uncounted units containing n bases. For example... Figure 2 As shown, the allelic genotype of the sequence to be analyzed is determined by an improved sequence re-alignment method. Based on the alignment results, three cases can be identified:

[0058] a. When the sequence to be analyzed is completely consistent with the sequence library, the allele length of the sequence to be analyzed is consistent with the sequence library record, and there are no flanking mutations, so the allele length typing can be obtained directly;

[0059] b. When the core repeating region of the sequence to be analyzed differs from that in the sequence library, such as Figure 2As shown, the starting position of the repeat region of the sequence to be analyzed is determined by re-alignment. Assuming the starting and ending coordinates of the core repeat region of the optimally aligned STR site A are p1 and p2 respectively, and the insertion or deletion position that causes a change in the length of the core repeat region is set as p3, the number of inserted or deleted bases is denoted as w (insertion is positive, deletion is negative). Based on the different positions of the insertion / deletion relative to the core repeat region, the total length L of the repeat region of the sequence to be analyzed can be denoted as:

[0060]

[0061] Further calculations yielded the allele length genotype a for the sequence to be analyzed:

[0062]

[0063] Where L is the total length of the repeating region of the sequence to be analyzed, m is the length of the characteristic repeating unit of the best-aligned STR, and n is the length of the uncounted unit of the best-aligned STR (this value is equal to 0 when there are no uncounted units).

[0064] c. When the flanking regions of the sequence to be analyzed differ from those in the sequence library, such as Figure 2 As shown, the distance and direction of flanking mutations relative to the core repeating region are determined by re-alignment. Flanking mutations occurring upstream of the repeating region are denoted as negative "-", and those occurring downstream are denoted as positive "+". Similarly, assuming the start and end coordinates of the core repeating region are p1 and p2, when multiple flanking mutations exist in the same direction, they are sorted according to their mutation coordinates from the 5' end to the 3' end, and denoted as p3, p4, ..., p2. n The number of bases involved in the mutation is denoted as q3, q4, ..., q n When the mutation type is a single-base mutation (s) or deletion (d), the relative position of the flanking mutation is not affected (assuming q = 0). However, when the mutation type is an insertion (i), the number of inserted bases closer to the repeating region is subtracted to match the insertion position. That is, the calculation is performed from the inside out. Taking the upstream of the repeating region as an example, the insertion mutation closest to the repeating region is , and its relative distance can be denoted as: P n =p n -p1

[0065] Then the relative position of the upstream variant = original relative position - total number of inserted bases closer to the repeating region: i.e., P n-1 =p n-1 -p1-q n ;

[0066] By calculating the relative position of the flanking mutation and recording the base changes, the flanking mutation genotype can be obtained. For example, +3sT indicates that the base is replaced with T 3 bp downstream of the repeating region.

[0067] (3) Correction

[0068] After obtaining allelic genotyping of the sequence to be analyzed through reference genome alignment, it can be found that, in addition to the two normal alleles in diploids (not considering multiple copies), the analysis results may show more sequences similar to the major alleles. These are noise sequences caused by amplification or sequencing errors, which occupy a large proportion of information, especially in some poor-quality samples, and interfere with subsequent STR genotyping. This application greatly reduces this interference and improves the effective depth of MPS data through sequence correction methods.

[0069] Before sequence correction, sequences that may originate from the same DNA template need to be clustered, and the following basic requirements must be met:

[0070] a. All sequences to be corrected are aligned to the same reference sequence in the sequence library;

[0071] b. The sequence to be corrected must completely cover the core repeat region.

[0072] All mutation information was statistically analyzed by aligning with the reference sequence library (using the same statistical method as in "Reference Genome Alignment"). For a single locus to be corrected, the frequency of all detected mutations (M1, M2, ..., M...) was calculated. i Using the total number of sequences N to be corrected that are aligned to the same sequence library reference sequence as a benchmark, the proportion of each mutation RM = M is calculated. i / N. When the proportion of mutations (RM) is greater than the preset threshold (A), the mutation is considered a reliable mutation; otherwise, it is considered a sequencing error and removed. Figure 3 As shown.

[0073] (4) STR typing

[0074] After completing the genome alignment and sequence correction steps described above, all alleles detected at all loci have been identified, including specific sequences, length genotypes, and flanking mutations. STR genotyping can be determined by arranging the supporting allele sequences from largest to smallest and calculating the allele ratio. Specifically, the method involves defining the allele with the largest number of supporting sequences at each locus as the baseline peak, and determining the specific STR genotype based on the allele coverage ratio (ACR), i.e., the ratio of the depth of the minor alleles relative to the baseline peak (0 < ACR ≤ 1).

[0075] The threshold ratios for "Balance" (T1), "Stutter (T2)," and "Noise" (T3) are set. When ACR ≥ T1, the allele will be labeled "Pass." When T1 ≥ ACR ≥ T2, the allele will be labeled "Imbanlance." If T2 ≥ ACR ≥ T3, and the difference between the allele length genotype and the baseline peak is less than or equal to 1, the allele is labeled "Stutter (T1); if the difference is greater than 1, it is labeled "Imbanlance." When ACR < T3, the allele is labeled "Noise" and does not participate in genotyping. Figure 4 As shown.

[0076] Based on the known locus ploidy (in the case of non-multiple copies, the ploidy of autosomal loci is 2, and the ploidy of male X chromosome loci is 1), the alleles of the locus ploidy number marked with "Pass" and "Imbalance" are output as STR genotypes; for mixed samples or special samples, alleles exceeding the ploidy number must reach the "Pass" threshold before they can be output.

[0077] (5) Allele sequence folding

[0078] To improve the readability of STR typing, this application provides a sequence folding method that can fold DNA sequences ranging from tens to hundreds of bases in length into easily readable degenerate sequences based on the repeat unit structure. The repeat unit structure X and the non-counting unit structure Y of the STR locus are predefined. Regular matching is used to determine the frequency {a,b,c,...} of structure X, and the position and sequence of structure Y relative to structure X, allowing the sequences to be grouped into [X]aY[X]b.

[0079] Taking locus D7S3048 as an example, it contains three repeating units: TATC, TACC, and CACC, as well as one non-counting unit: ctttctccataat. Therefore, its repeating region DNA sequence TATCCTTTCTCCATAATTATCTATCTATCTATCTATCTATCTATCTATCTATCTAC CTACCTACCTACCTACCTACCTACCCACCCACCCACC can be grouped into [TATC]1ctttctccataat[TATC]9[TACC]7[CACC]3. That is, [X]a replaces the repeating sequence in the STR, where X is the repeating unit sequence corresponding to the repeating sequence, and a is the number of repetitions of the repeating unit sequence.

[0080] Those skilled in the art will understand that all or part of the functions of the above methods can be implemented in hardware or by computer programs. When all or part of the functions of the above methods are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in storage media such as a server, another computer, disk, optical disk, flash drive, or portable hard drive, and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions of the above methods can be achieved.

[0081] Therefore, based on the genotyping method of short tandem repeat sequences and their flanking parts in this application, this application proposes a genotyping device for short tandem repeat sequences and their flanking parts, including a reference genome module, an alignment module, a correction module, and an STR genotyping module.

[0082] The system includes the following modules: a reference genome module for acquiring or storing a reference genome, which is an STR sequence library. The STR sequence library includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer capacity of "plus or minus one". The "plus or minus one" buffer capacity includes sequences that simulate adding one repeat unit to the core repeat region sequences of known STRs, and sequences that simulate removing one repeat unit from the core repeat region sequences of known STRs. An alignment module is used to align the sequence to be analyzed with the reference genome to obtain the STR locus information of the sequence to be analyzed. A correction module is used to correct mutations in the sequence to be analyzed using sequence correction methods, removing noise sequences caused by amplification or sequencing errors. An STR genotyping module is used to obtain the allele sequence, allele length genotyping, and flanking mutation genotyping of the corrected sequence to be analyzed. It determines the STR genotyping of the sequence to be analyzed by arranging the allele sequence numbers from largest to smallest and calculating the allele ratio.

[0083] Another implementation of this application provides a genotyping device for short tandem repeat sequences and their flanking sequences. The device includes a memory and a processor. The memory includes a program for storing data. The processor includes a program for executing the program stored in the memory to perform the following methods: aligning the sequence to be analyzed with a reference genome to obtain STR site information of the sequence; correcting mutations in the sequence to be analyzed using a sequence correction method to remove noise sequences caused by amplification or sequencing errors; obtaining the corrected allele sequence, allele length genotyping, and flanking mutation genotyping of the sequence to be analyzed; and determining the STR genotyping of the sequence to be analyzed by arranging allele sequence numbers from largest to smallest and calculating the allele ratio. The reference genome is an STR sequence library, which includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer capacity of "plus or minus one". The buffer capacity of "plus or minus one" includes sequences that simulate adding one repeat unit to the core repeat region sequence of a known STR, and sequences that simulate removing one repeat unit from the core repeat region sequence of a known STR. Furthermore, the method may also include allele sequence folding, i.e., replacing the repeating sequence of STR with [X]a, where X is the repeating unit sequence corresponding to the repeating sequence and a is the number of repetitions of the repeating unit sequence.

[0084] Another implementation of this application also provides a computer-readable storage medium, which includes a program executable by a processor to implement the following method: aligning the sequence to be analyzed with a reference genome to obtain STR site information of the sequence to be analyzed; correcting mutations in the sequence to be analyzed using a sequence correction method to remove noise sequences caused by amplification or sequencing errors; obtaining the allele sequence, allele length genotyping, and flanking mutation genotyping of the corrected sequence to be analyzed; and determining the STR genotyping of the sequence to be analyzed by arranging the allele sequence numbers from largest to smallest and calculating the allele ratio; wherein, the reference genome is an STR sequence library, which includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer library capacity of "plus or minus one"; the buffer library capacity of "plus or minus one" includes sequences that simulate adding one repeat unit to the core repeat region sequences of known STRs, and sequences that simulate removing one repeat unit from the core repeat region sequences of known STRs. Furthermore, the method may also include allele sequence folding, i.e., replacing the repeating sequence of STR with [X]a, where X is the repeating unit sequence corresponding to the repeating sequence and a is the number of repetitions of the repeating unit sequence.

[0085] In summary, this application develops a set of STR analysis methods and devices applicable to MPS data, enabling simultaneous genotyping of SNPs and InDels on STR core sequences and flanking sequences, thus expanding the polymorphism of STR loci. Specifically, it improves and provides a sequence correction scheme that accurately removes amplification and sequencing errors in MPS data, increasing the effective depth of STR genotyping; it also improves and provides an STR genotyping scheme that accurately excludes non-specific amplified sequences and STR stutter structures (which may cause genotyping errors), and supports users in customizing analysis thresholds based on data characteristics; and it improves and provides a sequence folding scheme that outputs the core repetitive sequences of STR loci in a more readable degenerate form.

[0086] Compared with existing short tandem repeat genotyping methods, this application has the following advantages:

[0087] (1) It achieves simultaneous typing of SNPs and InDels on the core and flanking sequences of STR, and is compatible with the length typing of CE. It is more accurate than the previous typing method that only focuses on the repeating region structure.

[0088] (2) By removing amplification and sequencing errors in MPS data, the typing method of this application improves the effective depth of STR genotyping and makes the typing results more reliable.

[0089] (3) The core repeat sequences of STR sites are output in a degenerate format, which improves the readability of the data.

[0090] The following specific experiments will further illustrate this application in detail. These experiments are merely illustrative and should not be construed as limiting the scope of this application.

[0091] Example

[0092] Based on the above genotyping methods and parameter settings, this example uses the standard 9948 cell line (male DNA) as a positive control and 10 real samples for testing. 9948 DNA was amplified by PCR using the Identifier DNA genotyping kit (Yanhuang 34) and the Yanhuang Y supplementary site genotyping kit (YS) from BGI Genomics Co., Ltd., and then subjected to capillary electrophoresis using an Applied Biosystems 3500XL genetic analyzer. Genotyping was performed using GeneMapper ID-X 1.5 genotyping software. The MPS data of the standard 9948 cell line and the real sample data were obtained from the multiplex amplification system of the FGID four-library integrated detection kit (core version) from BGI Genomics Co., Ltd., and FASTQ format data were obtained using the SE400 sequencing mode of the DNBSEQ-G99 platform (BGI Genomics Co., Ltd.).

[0093] After the data from the DNBSEQ-G99 platform was preprocessed, it was aligned to the reference sequence library, corrected for mutation information, and genotyped according to the aforementioned method. Finally, the accuracy of the STR genotype obtained by the 9948 DNA was evaluated by the CE platform, and the results before and after the mutation information correction and STR genotyping methods applied to this case were compared.

[0094] 1) Test results of standard products

[0095] Table 1 shows the results of comparing the traditional STR typing method and the STR typing method in this case, using the CE typing of the standard 9948 cell line as a positive control.

[0096] Table 1 Comparison of results from different analytical methods used for the 9948 standard cell line.

[0097]

[0098]

[0099]

[0100] Table 1 shows that the genotyping results obtained using this method are 100% consistent with the CE genotyping method, while the consistency rate of the traditional STR genotyping method is only 94.92%. Furthermore, comparing allele depth reveals that the MPS sequence correction in this method significantly improves the effective depth, with a median improvement rate of 32.01%. The improvement is even more pronounced for the two loci with the longest amplified fragments (DYS526b and DYS713), with effective depth improvements of 5129.63% and 9183.33%, respectively.

[0101] Inconsistent sites in traditional STR typing methods are mainly concentrated in Y-STRs with complex repeat units and long amplified fragments ("Yanhuang Y Supplementary Site Typing Box (YS)"). These loci are prone to uneven base distribution in MPS data, leading to excessively high sequencing error rates and the introduction of a large number of false positive sequences, such as the 17.4 and 18.1 alleles of the DYS587 locus in Table 1. The method in this example can effectively exclude false positive mutations introduced during the sequencing and amplification process.

[0102] 2) Actual sample test results

[0103] Table 2 presents the STR genotyping data of 10 randomly selected real samples. When the STR genotype contains multiple alleles, it is displayed in separate rows. As can be seen from the information in Table 2, in addition to the usual allele length genotyping and depth ratio information, this example assigns various labels to alleles based on a set threshold, such as "Stutter" referring to a stutter with one less allele, "Imbanlance" referring to an unbalanced allele, and provides a more readable core repeat structure.

[0104] For loci with flanking mutations, this example can accurately distinguish the correspondence between mutations and sequences. For example, the D13S317 locus in sample 5 can be divided into 8 and 10 [+1sT / +5sT], indicating that only allele 10 has a flanking mutation. For multi-copy loci (such as DYF371) and complex structural loci (such as DYS389I / II), this method can also clearly distinguish them by comparison with the reference sequence library.

[0105] Table 2 shows the analytical results of real samples using the method described in this example.

[0106]

[0107]

[0108] In practical applications, this example involves one or more computer programs whose code can be implemented using various object-oriented programming languages, such as Java, C++, Python, Perl, R, or other similar code that can reproduce the same effect.

[0109] Furthermore, similar construction logic can be used to replace this approach by increasing or decreasing the number of allele entries in the reference sequence library, or by modifying the flanking range covered by the sequence library. Additionally, thresholds can be added or modified during the STR genotyping process to assign more labels to alleles, improving the result presentation and making it more comprehensive. This example is primarily applied to downstream analysis of MPS data, suitable for individual identification fields such as public security database construction and physical evidence DNA analysis. It is also compatible with MPS data of different read lengths (this example uses the SE400 read length from the BGI platform sequencer), or other similar sequencing platforms (not limited to MPS sequencing), as long as the DNA fragment analysis can completely cover the STR loci.

[0110] The above description, in conjunction with specific embodiments, provides a further detailed explanation of this application and should not be construed as limiting the specific implementation of this application to these descriptions. Those skilled in the art to which this application pertains can make several simple deductions or substitutions without departing from the concept of this application.

Claims

1. A genotyping method for short tandem repeat sequences and their flanking parts, characterized in that: This includes aligning the sequence to be analyzed with a reference genome to obtain the STR locus information of the sequence to be analyzed; Sequence correction methods are used to correct mutations in the sequence to be analyzed and remove noisy sequences caused by amplification or sequencing errors. The corrected allele sequences, allele length genotypes, and flanking mutation genotypes of the sequence to be analyzed are obtained. The STR genotype of the sequence to be analyzed is determined by arranging the support allele sequence numbers from largest to smallest and calculating the allele ratio. The reference genome is an STR sequence library, which includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer library capacity of "plus or minus one". The "adding or subtracting one" buffer capacity includes a sequence that simulates adding one repeating unit based on the known core repeating region sequence of a STR, and a sequence that simulates removing one repeating unit based on the known core repeating region sequence of a STR.

2. The genotyping method according to claim 1, characterized in that: The "addition and subtraction of one" buffer capacity specifically includes, when the known allele range of a STR site is between m and n, constructing the sequence of core repeat region m-1 and the sequence of core repeat region n+1 based on the simulation of adding or subtracting one repeat unit in the core repeat region of the STR. Preferably, 200 bp sequences upstream and downstream of the same STR locus are extracted as flanking sequences of that STR locus.

3. The genotyping method according to claim 1, characterized in that: The STR locus information includes the number of STR loci, alignment position, base matching status, allele length genotyping, and flanking mutation genotyping. Preferably, the step of aligning the sequence to be analyzed with a reference genome to obtain the STR site information of the sequence to be analyzed specifically includes aligning all STR alleles in the STR sequence library with the sequence to be analyzed one by one. If the sequence to be analyzed is aligned to multiple alleles, the one with the highest alignment quality value is selected as the best alignment, and the STR site and STR site information of the sequence to be analyzed are determined based on the best alignment. Preferably, the step of determining the STR site and STR site information of the sequence to be analyzed based on the best alignment specifically includes, assuming the best alignment is STR site A, its core repeat region has a total length of L bases, the repeat unit length is m bases, and there are n bases in uncounted units. Based on the alignment results, variation analysis of the core repeat region and flanking sequences is performed in the following three cases. a. If the sequence to be analyzed is completely consistent with the STR sequence library, then the allele length of the sequence to be analyzed is consistent with the record in the STR sequence library, and there are no flanking mutations, so the allele length typing of the sequence to be analyzed can be obtained directly; b. When the core repeat sequence of the sequence to be analyzed differs from the STR sequence library, the starting position of the core repeat region of the sequence to be analyzed is determined by re-alignment. Let the starting and ending coordinates of the core repeat region of the best aligned STR site A be p1 and p2, respectively, and let the insertion or deletion position that causes the change in the length of the core repeat region be p3. The number of inserted or deleted bases is denoted as w, where w is positive for insertion and negative for deletion. Depending on the position of the insertion or deletion relative to the core repeat region, the total length L of the core repeat region of the sequence to be analyzed is denoted as: Calculate the allele length genotype 'a' of the sequence to be analyzed using the following formula. Where L is the total length of the core repeat region of the sequence to be analyzed, m is the length of the repeat unit of the best aligned STR site A, and n is the length of the uncounted unit of the best aligned STR site A. If there is no uncounted unit, then the value of n is 0. c. When the flanking sequence regions of the sequence to be analyzed differ from those in the STR sequence library, the distance and direction of the flanking mutation relative to the core repeat region are determined by re-alignment. A flanking mutation occurring upstream of the core repeat region is recorded as negative ("-"), and a flanking mutation occurring downstream of the repeat region is recorded as positive ("+"). Let the start and end coordinates of the core repeat region be p1 and p2. When multiple flanking mutations exist in the same direction, they are sorted according to their variation coordinates from the 5' end to the 3' end, and recorded as p3, p4, ..., p2. n The number of bases involved in the mutation is denoted as q3, q4, ..., q n When the mutation type is a single-base mutation or deletion, q = 0, meaning it does not affect the relative position of flanking mutations. When the mutation type is an insertion, the number of inserted bases closer to the core repeat region is subtracted to match the insertion position; that is, the calculation is performed from the inside out. Taking the upstream of the core repeat region as an example, the insertion variation closest to the core repeat region is p. n Their relative distance is denoted as P. n The calculation formula is P n =p n -p1; Then the relative position P of the upstream variation n-1 = Original relative position - Total number of inserted bases closer to the repeating region, i.e., P n-1 =p n-1 -p1-q n ; By analogy, the relative positions of the flanking mutations are calculated and the base changes are recorded to obtain the flanking mutation genotype.

4. The genotyping method according to claim 1, characterized in that: The sequence correction method is used to correct mutations in the sequence to be analyzed. Specifically, before sequence correction, sequences from the same DNA template are clustered so that the sequences to be corrected meet the following requirements: a) all sequences to be corrected are aligned to the same STR sequence library reference sequence, and b) the sequences to be corrected completely cover the core repeat region. By comparing and analyzing STR sequence databases, all mutation information was statistically analyzed. For a single locus to be corrected, the frequency of all detected mutations was counted, i.e., M1, M2, ..., M... i Based on the total number N of sequences to be corrected that are compared to the reference sequences in the same STR sequence library, the proportion of each mutation, RM=M, is calculated. i / N; When the proportion of mutations RM is greater than the preset threshold A, the mutation is counted as a reliable mutation; otherwise, it is considered a sequencing error and removed.

5. The genotyping method according to claim 1, characterized in that: The method of determining the STR genotype of the sequence to be analyzed by arranging the number of supporting allele sequences from largest to smallest and calculating the allele ratio specifically includes defining the allele with the largest number of supporting sequences at each locus as the baseline peak, and defining the specific STR genotype based on the allele coverage ratio (ACR), i.e. the ratio of the depth of the minor allele to the baseline peak, where 0 < ACR ≤ 1. Preferably, the method for defining specific STR genotypes includes setting a "Balance" threshold ratio as T1, a "Stutter" threshold ratio as T2, and a "Noise" threshold ratio as T3; when ACR ≥ T1, the allele will be labeled "Pass"; when T1 ≥ ACR ≥ T2, the allele will be labeled "Imbanlance"; if T2 ≥ ACR ≥ T3, and the difference between the allele length genotype and the baseline peak is less than or equal to 1, the allele is labeled "Stutter"; if the difference is greater than 1, it is labeled "Imbanlance"; when ACR < T3, the allele is labeled "Noise" and does not participate in genotyping. Based on known locus ploidies, in the case of non-multiple copies, the ploidy of autosomal loci is 2, and the ploidy of male X chromosome loci is 1. The alleles of the ploidy numbers marked "Pass" and "Imbalance" are output as the STR genotyping of the sequence to be analyzed. For mixed samples or special samples, when the number of alleles exceeding the ploidy number reaches the "Pass" threshold, they are output as the STR genotyping of the sequence to be analyzed.

6. The genotyping method according to any one of claims 1-5, characterized in that: This also includes allele sequence folding; The allele sequence folding includes replacing the repeating sequence of STR with [X]a, where X is the repeating unit sequence corresponding to the repeating sequence and a is the number of repetitions of the repeating unit sequence.

7. A genotyping device for short tandem repeat sequences and their flanking parts, characterized in that: Includes a reference genome module, alignment module, correction module, and STR genotyping module; The reference genome module is used to acquire or store a reference genome, which is an STR sequence library. The STR sequence library includes core repeat region sequences of several known STRs and their upstream and downstream flanking sequences, as well as a buffer library capacity of "plus or minus one". The buffer library capacity of "plus or minus one" includes sequences that simulate adding one repeat unit to the core repeat region sequences of known STRs, and sequences that simulate removing one repeat unit from the core repeat region sequences of known STRs. The alignment module is used to align the sequence to be analyzed with a reference genome to obtain the STR locus information of the sequence to be analyzed. The correction module is used to correct mutations in the sequence to be analyzed using sequence correction methods, and to remove noisy sequences caused by amplification or sequencing errors. The STR genotyping module is used to obtain the allele sequence, allele length genotyping, and flanking mutation genotyping of the corrected sequence to be analyzed. It determines the STR genotyping of the sequence to be analyzed by supporting the arrangement of allele sequence numbers from largest to smallest and calculating the allele ratio.

8. The genotyping device according to claim 7, characterized in that: The "addition and subtraction" buffer capacity in the reference genome module specifically includes, when the known allele range of a STR site is between m and n, constructing the sequence of core repeat region m-1 and the sequence of core repeat region n+1 based on the simulation of adding or subtracting one repeat unit in the core repeat region of the STR. Preferably, 200 bp sequences upstream and downstream of the same STR locus are extracted as flanking sequences of that STR locus.

9. The genotyping device according to claim 7, characterized in that: In the alignment module, the STR site information includes the number of STR sites, alignment position, base matching status, allele length genotyping, and flanking mutation genotyping. Preferably, the sequence to be analyzed is compared with a reference genome to obtain the STR site information of the sequence to be analyzed. Specifically, this includes comparing all STR alleles in the STR sequence library with the sequence to be analyzed one by one. If the sequence to be analyzed is compared with multiple alleles, the one with the highest alignment quality value is selected as the best alignment. The STR site and STR site information of the sequence to be analyzed are determined based on the best alignment. Preferably, the step of determining the STR site and STR site information of the sequence to be analyzed based on the best alignment specifically includes, assuming the best alignment is STR site A, its core repeat region has a total length of L bases, the repeat unit length is m bases, and there are n bases in uncounted units. Based on the alignment results, variation analysis of the core repeat region and flanking sequences is performed in the following three cases. a. If the sequence to be analyzed is completely consistent with the STR sequence library, then the allele length of the sequence to be analyzed is consistent with the record in the STR sequence library, and there are no flanking mutations, so the allele length typing of the sequence to be analyzed can be obtained directly; b. When the core repeat sequence of the sequence to be analyzed differs from the STR sequence library, the starting position of the core repeat region of the sequence to be analyzed is determined by re-alignment. Let the starting and ending coordinates of the core repeat region of the best aligned STR site A be p1 and p2, respectively, and let the insertion or deletion position that causes the change in the length of the core repeat region be p3. The number of inserted or deleted bases is denoted as w, where w is positive for insertion and negative for deletion. Depending on the position of the insertion or deletion relative to the core repeat region, the total length L of the core repeat region of the sequence to be analyzed is denoted as: Calculate the allele length genotype 'a' of the sequence to be analyzed using the following formula. Where L is the total length of the core repeat region of the sequence to be analyzed, m is the length of the repeat unit of the best aligned STR site A, and n is the length of the uncounted unit of the best aligned STR site A. If there is no uncounted unit, then the value of n is 0. c. When the flanking sequence regions of the sequence to be analyzed differ from those in the STR sequence library, the distance and direction of the flanking mutation relative to the core repeat region are determined by re-alignment. A flanking mutation occurring upstream of the core repeat region is recorded as negative ("-"), and a flanking mutation occurring downstream of the repeat region is recorded as positive ("+"). Let the start and end coordinates of the core repeat region be p1 and p2. When multiple flanking mutations exist in the same direction, they are sorted according to their variation coordinates from the 5' end to the 3' end, and recorded as p3, p4, ..., p2. n The number of bases involved in the mutation is denoted as q3, q4, ..., q n When the mutation type is a single-base mutation or deletion, q = 0, meaning it does not affect the relative position of flanking mutations. When the mutation type is an insertion, the number of inserted bases closer to the core repeat region is subtracted to match the insertion position; that is, the calculation is performed from the inside out. Taking the upstream of the core repeat region as an example, the insertion variation closest to the core repeat region is p. n Their relative distance is denoted as P. n The calculation formula is P n =p n -p1; Then the relative position P of the upstream variation n-1 = Original relative position - Total number of inserted bases closer to the repeating region, i.e., P n-1 =p n-1 -p1-q n ; By analogy, the relative positions of the flanking mutations are calculated and the base changes are recorded to obtain the flanking mutation genotype.

10. The genotyping device according to claim 7, characterized in that: In the correction module, a sequence correction method is used to correct mutations in the sequence to be analyzed. Specifically, before sequence correction, sequences from the same DNA template are clustered so that the sequences to be corrected meet the following requirements: a) all sequences to be corrected are aligned to the same STR sequence library reference sequence, b) the sequences to be corrected completely cover the core repeat region. By comparing and analyzing STR sequence databases, all mutation information was statistically analyzed. For a single locus to be corrected, the frequency of all detected mutations was counted, i.e., M1, M2, ..., M... i Based on the total number N of sequences to be corrected that are compared to the reference sequences in the same STR sequence library, the proportion of each mutation, RM=M, is calculated. i / N; When the proportion of mutations RM is greater than the preset threshold A, the mutation is counted as a reliable mutation; otherwise, it is considered a sequencing error and removed.

11. The genotyping device according to claim 7, characterized in that: In the STR genotyping module, the STR genotyping of the sequence to be analyzed is determined by arranging the allele sequence numbers from largest to smallest and calculating the allele ratio. Specifically, it includes defining the allele with the largest number of supported sequences at each locus as the baseline peak, and defining the specific STR genotyping based on the allele coverage ratio (ACR), i.e., the ratio of the depth of the minor alleles to the baseline peak, where 0 < ACR ≤ 1. Preferably, the method for defining specific STR genotypes includes setting a "Balance" threshold ratio as T1, a "Stutter" threshold ratio as T2, and a "Noise" threshold ratio as T3; when ACR ≥ T1, the allele will be labeled "Pass"; when T1 ≥ ACR ≥ T2, the allele will be labeled "Imbanlance"; if T2 ≥ ACR ≥ T3, and the difference between the allele length genotype and the baseline peak is less than or equal to 1, the allele is labeled "Stutter"; if the difference is greater than 1, it is labeled "Imbanlance"; when ACR < T3, the allele is labeled "Noise" and does not participate in genotyping. Based on known locus ploidies, in the case of non-multiple copies, the ploidy of autosomal loci is 2, and the ploidy of male X chromosome loci is 1. The alleles of the ploidy numbers marked "Pass" and "Imbalance" are output as the STR genotyping of the sequence to be analyzed. For mixed samples or special samples, when the number of alleles exceeding the ploidy number reaches the "Pass" threshold, they are output as the STR genotyping of the sequence to be analyzed.

12. The genotyping device according to any one of claims 7-11, characterized in that: It also includes an allele sequence folding module; The allele sequence folding module includes replacing the repeating sequence of STR with [X]a, where X is the repeating unit sequence corresponding to the repeating sequence and a is the number of times the repeating unit sequence is repeated.

13. A genotyping device for short tandem repeat sequences and their flanking parts, characterized in that, The genotyping device includes: Memory, used to store programs; A processor for implementing the genotyping method for short tandem repeat sequences and their flanks as described in any one of claims 1-6 by executing a program stored in the memory.

14. A computer-readable storage medium, characterized in that: The method includes a program that can be executed by a processor to implement the genotyping method for short tandem repeat sequences and their flanking parts as described in any one of claims 1-6.

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