A method and device for determining paternal kinship

Abstract

The application discloses a kind of paternal relationship determination method and device, belong to the field of forensic relationship determination, the method is: obtaining Y-STR genotype data to be determined, calculate its total step difference and difference site number;The difference value is compared with the corresponding threshold value to determine whether it belongs to the same paternal line;Wherein, the threshold value is based on reference population Y-STR database, by paternal lineage simulation method to generate simulation data, and is determined by using kernel density estimation method.Therefore, by implementing the application, the accuracy of Y-STR paternal relationship determination can be improved.

Description

Technical Field

[0001] This invention relates to the field of forensic kinship determination, and more particularly to a method, apparatus, equipment and medium for determining paternal kinship. Background Technology

[0002] In the field of paternal kinship determination, Y-STRs (Y-chromosome Short Tandem Repeats) are short tandem repeat sequences located on the male Y chromosome. They are a class of highly polymorphic genetic markers, and due to their strictly paternal inheritance characteristics, they hold irreplaceable value in kinship identification. This technology can be used to infer an individual's paternal geographical origin, identify victims of disasters or large-scale events, and assist in family tracing and genealogical research.

[0003] Current technologies primarily compare the number of differential steps or differential loci between two Y-STR genotypes and make judgments based on fixed thresholds or experience. The fundamental flaw of this method lies in the lack of scientific and adaptive discrimination criteria, leading to insufficient accuracy in the results. Since Y-STR mutations are random events, and different detection systems cover varying numbers and types of loci, using fixed thresholds cannot accurately assess the true probability of kinship corresponding to differential values ​​under different genetic distances and data conditions, thus easily causing misjudgments. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and medium for determining paternal kinship, which can improve the accuracy of Y-STR paternal kinship determination.

[0005] In a first aspect, embodiments of the present invention provide a method for determining paternal kinship, including: Obtain the first Y-STR genotype data and the second Y-STR genotype data to be determined; The Y-STR genotype difference calculation algorithm is used to calculate the first total step difference and the first difference site number between the first Y-STR genotype data and the second Y-STR genotype data; The first total step difference is compared with the total step difference threshold to obtain the first comparison result, and the kinship is determined based on the first comparison result; Alternatively, the first number of differential loci can be compared with a threshold for the number of differential loci to obtain a second comparison result, and the kinship can be determined based on the second comparison result; wherein, the total step difference threshold and the number of differential loci threshold are determined based on a preset reference population Y-STR database, using a paternal lineage simulation method and a kernel density estimation method.

[0006] This application's embodiments transform paternal relationship determination into a quantifiable and comparable objective indicator by acquiring the Y-STR genotype data pairs to be determined and calculating their first total step difference and first differential locus number. This overcomes the subjectivity of traditional experience-based judgments and lays a quantitative foundation for accurate determination. Secondly, by introducing total step difference thresholds and differential locus number thresholds determined based on a reference population Y-STR database and employing paternal pedigree simulation and kernel density estimation methods, the determination criteria no longer rely on fixed values ​​or subjective experience. Instead, they are based on scientific calculations of the real population's genetic background and simulated genetic processes. This allows for dynamic adaptation to determination scenarios under different combinations of paternal relationships and locus combinations, significantly reducing the risk of misjudgment due to unscientific thresholds. Finally, by comparing the quantified difference with the corresponding threshold based on the total step difference or differential locus number, the determination process is standardized and automated, improving the overall accuracy and reliability of Y-STR paternal relationship determination.

[0007] As a preferred example of the first aspect, the total step difference threshold and the difference locus number threshold are determined based on a preset reference population Y-STR database using a paternal lineage simulation method and a kernel density estimation method, including: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs, and the exhaustive pairing method is used to obtain several Y-STR genotype unrelated pairs from the preset reference population Y-STR database. Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm and the kernel density estimation method are used sequentially to calculate the total step difference threshold and the difference site number threshold.

[0008] This application utilizes a paternal lineage simulation method to generate a large number of Y-STR genotype pairs, simulating the randomness and diversity of mutation accumulation in real genetic processes. This provides a parental data foundation that conforms to genetic laws for threshold determination, overcoming the shortcomings of traditional methods that rely on limited samples. Secondly, irrelevant pairs are extracted from a reference database to establish the differential background distribution of unrelated individuals. Then, a Y-STR genotype difference calculation algorithm is used to quantify the kinship between the two types of sample pairs into two comparable indicators: the total step difference and the number of differential loci. Finally, through a kernel density estimation method, the intersection of the two distribution curves is scientifically determined as a dynamic threshold, enabling the judgment criteria to adapt to population genetic characteristics and data conditions, thereby systematically improving the accuracy of Y-STR paternal kinship determination.

[0009] As a preferred example of the first aspect, the step of calculating the total number of steps difference threshold and the number of difference sites threshold by sequentially using a Y-STR genotype difference calculation algorithm and a kernel density estimation method based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair includes: Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm is used to calculate the second total step difference of each Y-STR genotype related pair, the third total step difference of each Y-STR genotype unrelated pair, the number of second differential loci of each Y-STR genotype related pair, and the number of third differential loci of each Y-STR genotype unrelated pair. Based on the second total step difference of each Y-STR genotype kinship pair and the third total step difference of each Y-STR genotype unrelated pair, the total step difference threshold is estimated using a kernel density estimation method. Furthermore, based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the number of differential loci is estimated using a kernel density estimation method to obtain the number of differential loci threshold.

[0010] This application employs a Y-STR genotype difference calculation algorithm to quantify abstract genetic relationships into two sets of objective and comparable numerical indicators: "difference in the total number of second / third steps" and "number of second / third differential loci." This provides a precise data foundation for scientific judgment and overcomes the ambiguity of traditional experience-based comparisons. Secondly, kernel density estimation is applied to the quantified difference data. Its function is to accurately depict the true probability distribution of the difference values ​​between "related pairs" and "unrelated pairs" based on large-scale simulated data, and to dynamically determine the optimal discrimination threshold by finding the intersection of the two distribution curves. This method allows the threshold to adapt to the genetic background and data conditions of a specific population, fundamentally solving the misjudgment problem caused by the poor adaptability of fixed thresholds, thereby significantly improving the accuracy of judgment.

[0011] As a preferred example of the first aspect, the step of performing a first preset number of genetic simulations using a paternal lineage simulation method based on a preset reference population Y-STR database to generate a first preset number of Y-STR genotype pairs includes: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs; In each simulation, a Y-STR genotype is randomly selected from the preset reference population Y-STR database as the ancestral haplotype. Based on the ancestral haplotype, combined with the preset mutation rate and preset number of simulation generations, genetic simulation is performed to obtain the first lineage and the second lineage. Then, the Y-STR genotype kinship pair corresponding to the current simulation is determined based on the first lineage and the second lineage. All Y-STR genotype pairs are combined into the first preset number of Y-STR genotype pairs.

[0012] This application's embodiments ensure the representativeness of the genetic background of the simulated data by randomly selecting ancestral haplotypes from a real population database; by setting a controllable mutation rate and simulated generation number, it can accurately simulate the accumulation process of genetic variation at different kinship distances; and by simulating independent inheritance of two lineages, it can systematically generate paired samples with clear kinship correspondence. These steps work synergistically to ultimately generate large-scale, high-quality simulated kinship pair data, providing a training foundation for subsequent calculations that conforms to real genetic laws. This overcomes the shortcomings of traditional methods that rely on limited samples and fixed thresholds, improving the accuracy of the judgment system from the data source.

[0013] As a preferred example of the first aspect, the step of estimating the total step difference threshold using a kernel density estimation method based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair includes: Based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the first probability density function corresponding to the second total step difference and the second probability density function corresponding to the third total step difference. The intersection of the first probability density function and the second probability density function is determined as the total step difference threshold.

[0014] The kernel density estimation method in this application can accurately fit the true probability distribution of the difference values ​​between "related pairs" and "irrelevant pairs" non-parametrically based on large-scale differential data generated by simulation. This avoids the limitations of traditional threshold determination methods on the prior assumptions of the distribution pattern, thus reflecting the inherent statistical regularity of the data more accurately. Secondly, by determining the intersection of the two probability density functions as the discrimination threshold, its mathematical essence is to find the optimal point that theoretically balances the two error rates (false positives and false negatives). This method overcomes the shortcomings of fixed thresholds or empirical thresholds that cannot be adaptively adjusted according to population genetic characteristics, detection systems, and kinship distance. This innovative approach significantly improves the scientificity and accuracy of Y-STR paternal kinship determination from the judgment criteria themselves.

[0015] As a preferred example of the first aspect, the step of estimating the threshold number of differentially expressed loci using a kernel density estimation method based on the number of second differentially expressed loci in each Y-STR genotype-related pair and the number of third differentially expressed loci in each Y-STR genotype-independent pair includes: Based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the third probability density function corresponding to the number of second differential loci and the fourth probability density function corresponding to the number of third differential loci. The intersection of the third probability density function and the fourth probability density function is determined as the threshold for the number of differential sites.

[0016] As a preferred example of the first aspect, the calculation of the first total step difference and the first number of differentially expressed sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm includes: Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each single copy site are determined, and based on the data of each single copy site, the single copy site difference calculation method is used to calculate the first total step difference. Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each multicopy site are determined, and the number of the first differential sites is calculated using the multicopy site difference calculation method based on the data of each multicopy site.

[0017] This application employs direct difference calculation for single-copy sites, providing a fundamental and reliable accumulation unit for the total step difference. For multi-copy sites, the difference is calculated using the minimum step pairing principle, effectively solving the inherent technical problem of overestimation of difference values ​​due to the inability to distinguish allele origins. This divide-and-conquer strategy allows the genetic differences of different types of sites to be quantified using the optimal algorithm, ensuring the objectivity and accuracy of the first total step difference and the first difference digit result. This provides accurate and reliable quantitative input for subsequent threshold-based determinations, improving the accuracy of the overall determination system from the data calculation source.

[0018] As a preferred example of the first aspect, determining kinship based on the first comparison result includes: If the first comparison result is that the difference in the first total number of steps is less than or equal to the threshold of the difference in the total number of steps, then it is determined that the first Y-STR genotype data and the second Y-STR genotype data belong to the same paternal lineage; otherwise, it is determined that the first Y-STR genotype data and the second Y-STR genotype data do not belong to the same paternal lineage.

[0019] As a preferred example of the first aspect, determining kinship based on the second comparison result includes: If the second comparison result is that the number of the first differential loci is less than or equal to the threshold of the number of differential loci, then the first Y-STR genotype data and the second Y-STR genotype data are determined to belong to the same paternal lineage; otherwise, the first Y-STR genotype data and the second Y-STR genotype data are determined not to belong to the same paternal lineage.

[0020] In a second aspect, the present invention provides a method and apparatus for determining paternal kinship, comprising: a data acquisition module, a first determination module, a second determination module, and a third determination module; The data acquisition module is used to acquire the first Y-STR genotype data and the second Y-STR genotype data to be determined; The first judgment module is used to calculate the first total step difference and the first number of difference sites between the first Y-STR genotype data and the second Y-STR genotype data using a Y-STR genotype difference calculation algorithm; The second judgment module is used to compare the first total step difference with the total step difference threshold to obtain a first comparison result, and determine the kinship based on the first comparison result; The third judgment module is used to compare the first number of differential loci with the threshold number of differential loci to obtain a second comparison result, and to determine the kinship based on the second comparison result; wherein, the total step difference threshold and the differential loci number threshold are determined by using a paternal lineage simulation method and a kernel density estimation method based on a preset reference population Y-STR database.

[0021] As a preferred example of the second aspect, the total step difference threshold and the difference locus number threshold are determined based on a preset reference population Y-STR database using a paternal lineage simulation method and a kernel density estimation method, including: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs, and the exhaustive pairing method is used to obtain several Y-STR genotype unrelated pairs from the preset reference population Y-STR database. Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm and the kernel density estimation method are used sequentially to calculate the total step difference threshold and the difference site number threshold.

[0022] As a preferred example of the second aspect, the step of calculating the total number of steps difference threshold and the number of difference sites threshold by sequentially using a Y-STR genotype difference calculation algorithm and a kernel density estimation method based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair includes: Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm is used to calculate the second total step difference of each Y-STR genotype related pair, the third total step difference of each Y-STR genotype unrelated pair, the number of second differential loci of each Y-STR genotype related pair, and the number of third differential loci of each Y-STR genotype unrelated pair. Based on the second total step difference of each Y-STR genotype kinship pair and the third total step difference of each Y-STR genotype unrelated pair, the total step difference threshold is estimated using a kernel density estimation method. Furthermore, based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the number of differential loci is estimated using a kernel density estimation method to obtain the number of differential loci threshold.

[0023] As a preferred example of the second aspect, the step of performing a first preset number of genetic simulations using a paternal lineage simulation method based on a preset reference population Y-STR database to generate a first preset number of Y-STR genotype pairs includes: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs; In each simulation, a Y-STR genotype is randomly selected from the preset reference population Y-STR database as the ancestral haplotype. Based on the ancestral haplotype, combined with the preset mutation rate and preset number of simulation generations, genetic simulation is performed to obtain the first lineage and the second lineage. Then, the Y-STR genotype kinship pair corresponding to the current simulation is determined based on the first lineage and the second lineage. All Y-STR genotype pairs are combined into the first preset number of Y-STR genotype pairs.

[0024] As a preferred example of the second aspect, the step of estimating the total step difference threshold using a kernel density estimation method based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair includes: Based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the first probability density function corresponding to the second total step difference and the second probability density function corresponding to the third total step difference. The intersection of the first probability density function and the second probability density function is determined as the total step difference threshold.

[0025] As a preferred example of the second aspect, the step of estimating the threshold number of differentially expressed loci using a kernel density estimation method based on the number of second differentially expressed loci in each Y-STR genotype-related pair and the number of third differentially expressed loci in each Y-STR genotype-unrelated pair includes: Based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the third probability density function corresponding to the number of second differential loci and the fourth probability density function corresponding to the number of third differential loci. The intersection of the third probability density function and the fourth probability density function is determined as the threshold for the number of differential sites.

[0026] As a preferred example of the second aspect, the calculation of the first total step difference and the first number of differentially expressed sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm includes: Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each single copy site are determined, and based on the data of each single copy site, the single copy site difference calculation method is used to calculate the first total step difference. Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each multicopy site are determined, and the number of the first differential sites is calculated using the multicopy site difference calculation method based on the data of each multicopy site.

[0027] As a preferred example of the second aspect, determining kinship based on the first comparison result includes: If the first comparison result is that the difference in the first total number of steps is less than or equal to the threshold of the difference in the total number of steps, then it is determined that the first Y-STR genotype data and the second Y-STR genotype data belong to the same paternal lineage; otherwise, it is determined that the first Y-STR genotype data and the second Y-STR genotype data do not belong to the same paternal lineage.

[0028] As a preferred example of the second aspect, determining kinship based on the second comparison result includes: If the second comparison result is that the number of the first differential loci is less than or equal to the threshold of the number of differential loci, then the first Y-STR genotype data and the second Y-STR genotype data are determined to belong to the same paternal lineage; otherwise, the first Y-STR genotype data and the second Y-STR genotype data are determined not to belong to the same paternal lineage.

[0029] In summary, this application's embodiments, by acquiring the Y-STR genotype data pairs to be determined and calculating their first total step difference and first differential locus number, transform paternal relationship determination into a quantifiable and comparable objective indicator, overcoming the subjectivity of traditional experience-based judgment and laying a quantitative foundation for accurate determination. Secondly, by introducing total step difference thresholds and differential locus number thresholds determined based on a reference population Y-STR database and employing paternal lineage simulation and kernel density estimation methods, the determination criteria no longer rely on fixed values ​​or subjective experience, but are based on scientific calculations of the real population's genetic background and simulated genetic processes. This allows for dynamic adaptation to determination scenarios under different detection systems and different locus combinations, significantly reducing the risk of misjudgment due to unscientific thresholds. Finally, by comparing the quantified difference with the corresponding threshold based on the total step difference or differential locus number, the determination process is standardized and automated, improving the overall accuracy and reliability of Y-STR paternal relationship determination.

[0030] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the paternal kinship determination method of the present invention.

[0031] Another embodiment of the present invention also provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the paternal kinship determination method of the present invention. Attached Figure Description

[0032] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0033] Figure 1 This is a flowchart illustrating an embodiment of a method for determining paternal kinship provided by the present invention; Figure 2 A difference distribution diagram of actual and simulated family pedigrees, representing an embodiment of a paternal kinship determination method provided by the present invention; Figure 3 This is a module structure diagram of one embodiment of a paternal kinship determination device provided by the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0036] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0037] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0038] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0039] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0040] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0041] Example 1 See Figure 1 To improve the accuracy of Y-STR paternal kinship determination, an embodiment of the present invention provides a method for determining paternal kinship, comprising: S1. Obtain the first Y-STR genotype data and the second Y-STR genotype data to be determined; S2. Calculate the first total step difference and the first number of difference sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm; As a preferred embodiment, the step of calculating the first total step difference and the first number of differentially expressed sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm includes: Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each single copy site are determined, and based on the data of each single copy site, the single copy site difference calculation method is used to calculate the first total step difference. Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each multicopy site are determined, and the number of the first differential sites is calculated using the multicopy site difference calculation method based on the data of each multicopy site.

[0042] Specifically, the step of calculating the first total step difference and the first number of differential sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm can be implemented in the following preferred manner: ① For a single-copy site, each sample has only one allele value. The difference between two samples at this site is the absolute value of the difference in their allele values. For sample pair (A,B) at single-copy site i, the step difference Si is: Si = |Ai - Bi|. The sum of the step differences at all single-copy sites is the total step difference for the sample pair.

[0043] ② Multiple copy sites (such as DYS385ab, DYF387S1ab, etc.) have two allele values ​​in each sample. Direct comparison cannot determine which allele corresponds to which allele in another sample because PCR amplification and detection do not distinguish the origin of multiple copy alleles. This embodiment uses the minimum number of steps principle to calculate the differences in multiple copy sites, and the steps are as follows: (1) For a multicopy site, the alleles of sample A are (A1,A2) and the alleles of sample B are (B1,B2).

[0044] (2) Calculate the step difference between the two possible allele pairing methods: Pairing method 1: (A1 vs B1) and (A2 vs B2), total difference D1 = |A1 - B1| + |A2 - B2| Pairing method two: (A1 vs B2) and (A2 vs B1), total difference D2 = |A1 - B2| + |A2 - B1| (3) Take the minimum value between D1 and D2 as the final step difference for that site.

[0045] It should be noted that performing this calculation in a native loop within the R environment is inefficient. Therefore, we prioritize matrix calculations and then implement the algorithm in C++ using Rcpp, performing batch calculations on all sample pairs, which greatly improves computational efficiency and enables it to handle large-scale databases.

[0046] ③Total differences and site differences Total step difference: Sum the step differences Si of all sites (single copy and multiple copy).

[0047] Number of differential sites: Count the number of sites with a difference Si > 0 across all steps.

[0048] S3. Compare the first total step difference with the total step difference threshold to obtain a first comparison result, and determine the kinship based on the first comparison result; As a preferred embodiment, determining kinship based on the first comparison result includes: If the first comparison result is that the difference in the first total number of steps is less than or equal to the threshold of the difference in the total number of steps, then it is determined that the first Y-STR genotype data and the second Y-STR genotype data belong to the same paternal lineage; otherwise, it is determined that the first Y-STR genotype data and the second Y-STR genotype data do not belong to the same paternal lineage.

[0049] S4. Alternatively, the first number of differential loci can be compared with the threshold number of differential loci to obtain a second comparison result, and the kinship can be determined based on the second comparison result; wherein, the total step difference threshold and the differential loci number threshold are determined based on a preset reference population Y-STR database, using a paternal lineage simulation method and a kernel density estimation method.

[0050] In a preferred embodiment, determining kinship based on the second comparison result includes: If the second comparison result is that the number of the first differential loci is less than or equal to the threshold of the number of differential loci, then the first Y-STR genotype data and the second Y-STR genotype data are determined to belong to the same paternal lineage; otherwise, the first Y-STR genotype data and the second Y-STR genotype data are determined not to belong to the same paternal lineage.

[0051] In a preferred embodiment, the total step difference threshold and the difference locus number threshold are determined based on a preset reference population Y-STR database using a paternal lineage simulation method and a kernel density estimation method, including: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs, and the exhaustive pairing method is used to obtain several Y-STR genotype unrelated pairs from the preset reference population Y-STR database. Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm and the kernel density estimation method are used sequentially to calculate the total step difference threshold and the difference site number threshold.

[0052] As a preferred embodiment, the step of calculating the total number of steps difference threshold and the number of difference sites threshold by sequentially using a Y-STR genotype difference calculation algorithm and a kernel density estimation method based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair includes: Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm is used to calculate the second total step difference of each Y-STR genotype related pair, the third total step difference of each Y-STR genotype unrelated pair, the number of second differential loci of each Y-STR genotype related pair, and the number of third differential loci of each Y-STR genotype unrelated pair. Based on the second total step difference of each Y-STR genotype kinship pair and the third total step difference of each Y-STR genotype unrelated pair, the total step difference threshold is estimated using a kernel density estimation method. Furthermore, based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the number of differential loci is estimated using a kernel density estimation method to obtain the number of differential loci threshold.

[0053] As a preferred embodiment, the step of performing a first preset number of genetic simulations using a paternal lineage simulation method based on a preset reference population Y-STR database to generate a first preset number of Y-STR genotype pairs includes: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs; In each simulation, a Y-STR genotype is randomly selected from the preset reference population Y-STR database as the ancestral haplotype. Based on the ancestral haplotype, combined with the preset mutation rate and preset number of simulation generations, genetic simulation is performed to obtain the first lineage and the second lineage. Then, the Y-STR genotype kinship pair corresponding to the current simulation is determined based on the first lineage and the second lineage. All Y-STR genotype pairs are combined into the first preset number of Y-STR genotype pairs.

[0054] Specifically, the genetic simulation can be implemented in the following preferred manner: The reference database was divided into two datasets: single-copy and multiple-copy. One dataset was randomly selected as the ancestral haplotype. Starting from this ancestor, the inheritance of two lineages was independently simulated. Simulating Y-STR mutations was the core of this process. In each generation, for each Y-STR locus, the following operations were performed: ① A mutation occurs once with a preset probability μ (mutation rate); ② If a mutation occurs, it will increase (+1) or decrease (-1) in one step with equal probability (μ / 2 for each). Let the current allele value be G, and the allele value G' after one generation be: G' = G + step The values ​​of step are shown in Table 1: Table 1. Values ​​of step ③ This process is achieved by generating a random number U(0,1) that follows a uniform distribution and comparing it with μ.

[0055] ④ To improve computational efficiency, n generations of simulation are performed on N individuals with m labels. Step can be represented as an m×N matrix of n values ​​(0, +1, -1). The offspring morphology is obtained by summing the matrices.

[0056] As a preferred embodiment, the step of estimating the total step difference threshold using a kernel density estimation method based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair includes: Based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the first probability density function corresponding to the second total step difference and the second probability density function corresponding to the third total step difference. The intersection of the first probability density function and the second probability density function is determined as the total step difference threshold.

[0057] In a preferred embodiment, the step of estimating the threshold number of differentially expressed loci using a kernel density estimation method based on the number of second differentially expressed loci in each Y-STR genotype-related pair and the number of third differentially expressed loci in each Y-STR genotype-independent pair includes: Based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the third probability density function corresponding to the number of second differential loci and the fourth probability density function corresponding to the number of third differential loci. The intersection of the third probability density function and the fourth probability density function is determined as the threshold for the number of differential sites.

[0058] Specifically, to fully explain the estimation process using the kernel density estimation method, the following scheme will be used as an example: ① Simulate 100,000 (or more) pairs of individuals from the same paternal lineage with different meiotic counts, and use the "Y-STR genotype difference calculation algorithm" to calculate the step difference and locus difference between individuals from the same paternal lineage and unrelated individuals respectively; ② Kernel density estimation is performed on the difference (step count or locus count) data of "related pairs" and "unrelated individual pairs" respectively, resulting in two continuous probability density functions f_rel(x) and f_unrel(x). Within the domain of the difference value x, the point where f_rel(x) = f_unrel(x) is found, i.e., the intersection of the two density curves. This intersection point is the theoretically optimal discrimination threshold t. For any pair of individuals, if the difference number is less than or equal to t, they are determined to be of the same paternal lineage; if it is greater than t, they are determined to be unrelated individuals. ③ The area under the f_rel(x) curve to the right of the optimal threshold represents the proportion of related individuals incorrectly identified as unrelated individuals (false negative rate). The area under the f_unrel(x) curve to the left of the optimal threshold represents the proportion of unrelated individuals incorrectly identified as related individuals (false positive rate). ④Due to the differences in the number of Y-STRs among individuals and the types of kinship included, there may be differences in threshold and efficacy. The above process can be adjusted as needed to simulate and obtain an ideal threshold, which will facilitate decision-making in actual identification.

[0059] Specifically, in order to verify the reliability of the method of this application, such as Figure 2 As shown, based on genetic data from 80 Y-STRs of a multi-generational male family in southern China, kinshipY was used to calculate the genetic distance between each pair of male individuals within the family and the differences in the number / absence of Y-STRs. Simultaneously, based on genetic data from 80 Y-STRs of 709 unrelated male individuals, kinshipY was used to simulate and generate 100,000 pairs of male kinship samples undergoing 1-27 meiotic divisions. The differences in the number / absence of these pairs are shown in the figure below. It can be observed that the distribution patterns of the two methods are highly consistent, demonstrating the reliability of this method.

[0060] In summary, this application's embodiments, by acquiring the Y-STR genotype data pairs to be determined and calculating their first total step difference and first differential locus number, transform paternal relationship determination into a quantifiable and comparable objective indicator, overcoming the subjectivity of traditional experience-based judgment and laying a quantitative foundation for accurate determination. Secondly, by introducing total step difference thresholds and differential locus number thresholds determined based on a reference population Y-STR database and employing paternal lineage simulation and kernel density estimation methods, the determination criteria no longer rely on fixed values ​​or subjective experience, but are based on scientific calculations of the real population's genetic background and simulated genetic processes. This allows for dynamic adaptation to determination scenarios under different detection systems and different locus combinations, significantly reducing the risk of misjudgment due to unscientific thresholds. Finally, by comparing the quantified difference with the corresponding threshold based on the total step difference or differential locus number, the determination process is standardized and automated, improving the overall accuracy and reliability of Y-STR paternal relationship determination.

[0061] Example 2 like Figure 3 As shown, based on the above method embodiments, corresponding device embodiments are provided; One embodiment of the present invention provides a paternal kinship determination device, comprising: a data acquisition module 31, a first determination module 32, a second determination module 33, and a third determination module 34; Data acquisition module 31 is used to acquire the first Y-STR genotype data and the second Y-STR genotype data to be determined; The first judgment module 32 is used to calculate the first total step difference and the first number of difference sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm; The second judgment module 33 is used to compare the first total step difference with the total step difference threshold to obtain a first comparison result, and determine the kinship based on the first comparison result; The third judgment module 34 is used to compare the first number of differential loci with the threshold number of differential loci to obtain a second comparison result, and to determine the kinship based on the second comparison result; wherein, the total step difference threshold and the differential loci number threshold are determined by using a paternal lineage simulation method and a kernel density estimation method based on a preset reference population Y-STR database.

[0062] In a preferred embodiment, the total step difference threshold and the difference locus number threshold are determined based on a preset reference population Y-STR database using a paternal lineage simulation method and a kernel density estimation method, including: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs, and the exhaustive pairing method is used to obtain several Y-STR genotype unrelated pairs from the preset reference population Y-STR database. Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm and the kernel density estimation method are used sequentially to calculate the total step difference threshold and the difference site number threshold.

[0063] As a preferred embodiment, the step of calculating the total number of steps difference threshold and the number of difference sites threshold by sequentially using a Y-STR genotype difference calculation algorithm and a kernel density estimation method based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair includes: Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm is used to calculate the second total step difference of each Y-STR genotype related pair, the third total step difference of each Y-STR genotype unrelated pair, the number of second differential loci of each Y-STR genotype related pair, and the number of third differential loci of each Y-STR genotype unrelated pair. Based on the second total step difference of each Y-STR genotype kinship pair and the third total step difference of each Y-STR genotype unrelated pair, the total step difference threshold is estimated using a kernel density estimation method. Furthermore, based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the number of differential loci is estimated using a kernel density estimation method to obtain the number of differential loci threshold.

[0064] As a preferred embodiment, the step of performing a first preset number of genetic simulations using a paternal lineage simulation method based on a preset reference population Y-STR database to generate a first preset number of Y-STR genotype pairs includes: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs; In each simulation, a Y-STR genotype is randomly selected from the preset reference population Y-STR database as the ancestral haplotype. Based on the ancestral haplotype, combined with the preset mutation rate and preset number of simulation generations, genetic simulation is performed to obtain the first lineage and the second lineage. Then, the Y-STR genotype kinship pair corresponding to the current simulation is determined based on the first lineage and the second lineage. All Y-STR genotype pairs are combined into the first preset number of Y-STR genotype pairs.

[0065] As a preferred embodiment, the step of estimating the total step difference threshold using a kernel density estimation method based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair includes: Based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the first probability density function corresponding to the second total step difference and the second probability density function corresponding to the third total step difference. The intersection of the first probability density function and the second probability density function is determined as the total step difference threshold.

[0066] In a preferred embodiment, the step of estimating the threshold number of differentially expressed loci using a kernel density estimation method based on the number of second differentially expressed loci in each Y-STR genotype-related pair and the number of third differentially expressed loci in each Y-STR genotype-independent pair includes: Based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the third probability density function corresponding to the number of second differential loci and the fourth probability density function corresponding to the number of third differential loci. The intersection of the third probability density function and the fourth probability density function is determined as the threshold for the number of differential sites.

[0067] As a preferred embodiment, the step of calculating the first total step difference and the first number of differentially expressed sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm includes: Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each single copy site are determined, and based on the data of each single copy site, the single copy site difference calculation method is used to calculate the first total step difference. Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each multicopy site are determined, and the number of the first differential sites is calculated using the multicopy site difference calculation method based on the data of each multicopy site.

[0068] As a preferred embodiment, determining kinship based on the first comparison result includes: If the first comparison result is that the difference in the first total number of steps is less than or equal to the threshold of the difference in the total number of steps, then it is determined that the first Y-STR genotype data and the second Y-STR genotype data belong to the same paternal lineage; otherwise, it is determined that the first Y-STR genotype data and the second Y-STR genotype data do not belong to the same paternal lineage.

[0069] In a preferred embodiment, determining kinship based on the second comparison result includes: If the second comparison result is that the number of the first differential loci is less than or equal to the threshold of the number of differential loci, then the first Y-STR genotype data and the second Y-STR genotype data are determined to belong to the same paternal lineage; otherwise, the first Y-STR genotype data and the second Y-STR genotype data are determined not to belong to the same paternal lineage.

[0070] In summary, this application's embodiments, by acquiring the Y-STR genotype data pairs to be determined and calculating their first total step difference and first differential locus number, transform paternal relationship determination into a quantifiable and comparable objective indicator, overcoming the subjectivity of traditional experience-based judgment and laying a quantitative foundation for accurate determination. Secondly, by introducing total step difference thresholds and differential locus number thresholds determined based on a reference population Y-STR database and employing paternal lineage simulation and kernel density estimation methods, the determination criteria no longer rely on fixed values ​​or subjective experience, but are based on scientific calculations of the real population's genetic background and simulated genetic processes. This allows for dynamic adaptation to determination scenarios under different detection systems and different locus combinations, significantly reducing the risk of misjudgment due to unscientific thresholds. Finally, by comparing the quantified difference with the corresponding threshold based on the total step difference or differential locus number, the determination process is standardized and automated, improving the overall accuracy and reliability of Y-STR paternal relationship determination.

[0071] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the paternal kinship determination method provided by any of the above-described method embodiments of the present invention.

[0072] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0073] Example 3 Based on the above embodiments of the paternal kinship determination method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the paternal kinship determination method of any embodiment of the present invention.

[0074] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0075] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0076] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0077] Example 4 Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the paternal kinship determination method described in any of the above-described method embodiments of the present invention.

[0078] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0079] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for determining paternal kinship, characterized in that, include: Obtain the first Y-STR genotype data and the second Y-STR genotype data to be determined; The Y-STR genotype difference calculation algorithm is used to calculate the first total step difference and the first difference site number between the first Y-STR genotype data and the second Y-STR genotype data; The first total step difference is compared with the total step difference threshold to obtain the first comparison result, and the kinship is determined based on the first comparison result; Alternatively, the first number of differential loci can be compared with a threshold for the number of differential loci to obtain a second comparison result, and the kinship can be determined based on the second comparison result; wherein, the total step difference threshold and the number of differential loci threshold are determined based on a preset reference population Y-STR database, using a paternal lineage simulation method and a kernel density estimation method.

2. The method for determining paternal kinship as described in claim 1, characterized in that, The total step difference threshold and the difference locus number threshold are determined based on a preset reference population Y-STR database using paternal lineage simulation and kernel density estimation methods, including: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs, and the exhaustive pairing method is used to obtain several Y-STR genotype unrelated pairs from the preset reference population Y-STR database. Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm and the kernel density estimation method are used sequentially to calculate the total step difference threshold and the difference site number threshold.

3. The method for determining paternal kinship as described in claim 2, characterized in that, The process involves calculating the total number of steps difference threshold and the number of difference sites threshold based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, sequentially using a Y-STR genotype difference calculation algorithm and a kernel density estimation method. Based on each Y-STR genotype related pair and each Y-STR genotype unrelated pair, the Y-STR genotype difference calculation algorithm is used to calculate the second total step difference of each Y-STR genotype related pair, the third total step difference of each Y-STR genotype unrelated pair, the number of second differential loci of each Y-STR genotype related pair, and the number of third differential loci of each Y-STR genotype unrelated pair. Based on the second total step difference of each Y-STR genotype kinship pair and the third total step difference of each Y-STR genotype unrelated pair, the total step difference threshold is estimated using a kernel density estimation method. Furthermore, based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the number of differential loci is estimated using a kernel density estimation method to obtain the number of differential loci threshold.

4. The method for determining paternal kinship as described in claim 2, characterized in that, The step of performing a first preset number of genetic simulations using a paternal lineage simulation method based on a preset reference population Y-STR database to generate a first preset number of Y-STR genotype pairs includes: Based on the preset reference population Y-STR database, the paternal lineage simulation method is used to perform a first preset number of genetic simulations to generate a first preset number of Y-STR genotype pairs; In each simulation, a Y-STR genotype is randomly selected from the preset reference population Y-STR database as the ancestral haplotype. Based on the ancestral haplotype, combined with the preset mutation rate and preset number of simulation generations, genetic simulation is performed to obtain the first lineage and the second lineage. Then, the Y-STR genotype kinship pair corresponding to the current simulation is determined based on the first lineage and the second lineage. All Y-STR genotype pairs are combined into the first preset number of Y-STR genotype pairs.

5. The method for determining paternal kinship as described in claim 3, characterized in that, The threshold for the total step difference is estimated using a kernel density estimation method based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair, including: Based on the second total step difference of each Y-STR genotype related pair and the third total step difference of each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the first probability density function corresponding to the second total step difference and the second probability density function corresponding to the third total step difference. The intersection of the first probability density function and the second probability density function is determined as the total step difference threshold.

6. The method for determining paternal kinship as described in claim 3, characterized in that, The threshold for the number of differentially expressed loci is estimated using a kernel density estimation method based on the number of second differentially expressed loci in each Y-STR genotype-related pair and the number of third differentially expressed loci in each Y-STR genotype-independent pair, including: Based on the number of second differential loci in each Y-STR genotype kinship pair and the number of third differential loci in each Y-STR genotype unrelated pair, the kernel density estimation method is used to estimate the third probability density function corresponding to the number of second differential loci and the fourth probability density function corresponding to the number of third differential loci. The intersection of the third probability density function and the fourth probability density function is determined as the threshold for the number of differential sites.

7. The method for determining paternal kinship as described in claim 1, characterized in that, The calculation of the first total step difference and the first number of differentially expressed sites between the first Y-STR genotype data and the second Y-STR genotype data using the Y-STR genotype difference calculation algorithm includes: Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each single copy site are determined, and based on the data of each single copy site, the single copy site difference calculation method is used to calculate the first total step difference. Based on the first Y-STR genotype data and the second Y-STR genotype data, the data of each multicopy site are determined, and the number of the first differential sites is calculated using the multicopy site difference calculation method based on the data of each multicopy site.

8. The method for determining paternal kinship as described in claim 1, characterized in that, The determination of kinship based on the first comparison result includes: If the first comparison result is that the difference in the first total number of steps is less than or equal to the threshold of the difference in the total number of steps, then it is determined that the first Y-STR genotype data and the second Y-STR genotype data belong to the same paternal lineage; otherwise, it is determined that the first Y-STR genotype data and the second Y-STR genotype data do not belong to the same paternal lineage.

9. The method for determining paternal kinship as described in claim 1, characterized in that, The determination of kinship based on the second comparison result includes: If the second comparison result is that the number of the first differential loci is less than or equal to the threshold of the number of differential loci, then the first Y-STR genotype data and the second Y-STR genotype data are determined to belong to the same paternal lineage; otherwise, the first Y-STR genotype data and the second Y-STR genotype data are determined not to belong to the same paternal lineage.

10. A method and apparatus for determining paternal kinship, characterized in that, include: The system comprises a data acquisition module, a first judgment module, a second judgment module, and a third judgment module. The data acquisition module is used to acquire the first Y-STR genotype data and the second Y-STR genotype data to be determined; The first judgment module is used to calculate the first total step difference and the first number of difference sites between the first Y-STR genotype data and the second Y-STR genotype data using a Y-STR genotype difference calculation algorithm; The second judgment module is used to compare the first total step difference with the total step difference threshold to obtain a first comparison result, and determine the kinship based on the first comparison result; The third judgment module is used to compare the first number of differential loci with the threshold number of differential loci to obtain a second comparison result, and to determine the kinship based on the second comparison result; wherein, the total step difference threshold and the differential loci number threshold are determined by using a paternal lineage simulation method and a kernel density estimation method based on a preset reference population Y-STR database.

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