CN101838686A - Genetic relationship identification device and method - Google Patents

Abstract

The embodiment of the invention discloses a kinship identification device and method. The kinship identification device includes: a data reading module, a database table, a data analysis module and a result query module; the data reading module is used to read data that needs to be analyzed for kinship; the database table is used to save the The data read by the data reading module; the data analysis module is used to calculate the parentage index of the kinship between the two bodies according to the data preserved in the database table, and save the calculation result in the database table; the result The query module is used to query the calculation results stored in the database table by the data analysis module. Through the present invention, the problem of complicated manual calculation in the prior art can be solved, and the reliability and accuracy of data can be greatly improved.

Description

Apparatus and method for kinship identification

technical field

The invention relates to DNA testing technology, in particular to a device and method for identifying genetic relationship.

Background technique

Individual identification plays a pivotal role in forensic testing. In daily inspection cases, it is one of the important tasks of forensic inspection to judge the genetic relationship between individuals based on the DNA test results based on Mendelian genetic laws. However, in some cases, there may be situations where the parties’ parents have died or their parents cannot participate in the test for some reason. In this case, the parties will request the identification of the relationship between siblings; When conducting investigation and comparison of a large number of suspects and on-site evidence, when the direct identification of single-parent genetic relationship is excluded, it is necessary to use DNA testing to further analyze and infer the genetic relationship between their siblings for further investigation and comparison. At present, the forensic field usually uses the ITO method as the theoretical basis to identify the genetic relationship between siblings by typing the autosomal (STR) loci. In the prior art, calculations are generally performed manually for each locus using formulas one by one. However, the manual calculation is complicated, time-consuming and laborious, and the reliability and accuracy of the data cannot be guaranteed.

Contents of the invention

In view of this, an embodiment of the present invention proposes a device and method for identifying kinship to solve the problems in the prior art that manual calculations are complicated and the reliability and accuracy of the data cannot be guaranteed.

Embodiments of the present invention provide a kind of kinship identification device, including a data reading module, a database table, a data analysis module and a result query module;

The data reading module is used to read data that needs to be analyzed for kinship;

The database table is used to save the data read by the data reading module;

The data analysis module is used to calculate the parentage index of the kinship relationship between two individuals according to the data stored in the database table, and save the calculation result in the database table;

The result query module is used to query the calculation results stored in the database table by the data analysis module.

Embodiments of the present invention also propose a method for identification of kinship, including

Read the data that needs to be analyzed for kinship;

Calculate the parentage index of the kinship between the two bodies according to the data;

Query calculation results. .

It can be seen from the above technical solutions that the kinship identification device and method provided by the embodiments of the present invention can calculate the chance of kinship between two individuals, making complicated kinship calculation into simple data processing, and greatly improving the reliability of data precision and precision.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Apparently, the drawings in the following description are only some embodiments of the present invention, and those skilled in the art can obtain other drawings according to these drawings without creative efforts.

Fig. 1 is a kinship identification device according to an embodiment of the present invention;

Fig. 2 is a kinship identification method according to an embodiment of the present invention.

Detailed ways

In order to express the purpose, technical solutions and advantages of the present invention more clearly, the following will clearly and completely describe the technical solutions of the embodiments of the present invention in conjunction with the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. The present invention can also be embodied in different forms and is therefore not limited to the embodiments described here. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

Fig. 1 is a kinship identification device according to an embodiment of the present invention. As shown in FIG. 1 , the kinship identification device 10 includes: a data reading module 11 , a database table 12 , a data analysis module 13 and a result query module 14 .

The data reading module 11 is used to read data that needs to be analyzed for kinship. The data can be the data read automatically by the data reading module 11 from the DAT format file of the genetic analyzer, or the data read by the data reading module 11 manually input by the user through the input interface. Wherein, the file in DAT format is formed by the result obtained by the genetic analyzer through the detection of the sample to be analyzed.

The database table 12 is used to save the data read by the data reading module 11 . The data reading module 11 can further be used to modify and delete the data stored in the database table 12 , and can also add newly read data to the database table 12 .

The data analysis module 13 is used to calculate the parentage index of the genetic relationship between two individuals according to the data stored in the database table 12 . In this embodiment, the relative relationship refers to sibling relationship. Specifically, the data analysis module 13 calculates the sibling relationship index PI _FS between any two individuals in the database table 12 by applying the ITO algorithm according to the calculation principle of EssenMoller for the PCR-STR typing results, and according to the formula W _FS =PI _FS /( PI _FS +1) calculates the probability of sibling relationship, counts the number of genes shared between two individuals, that is, the number of identical alleles possessed by two comparison individuals, and analyzes that the alleles of the same locus are completely different in each two comparison individuals , semi-identical and identical situations, and save the analysis results to the database table.

In addition, in order to improve the accuracy of the analysis results, this embodiment adopts the idea of "full ratio", that is, the data analysis module 13 correlates each data newly added by the data reading module 11 with all the data in the database table 12 Calculate and save the calculation result to the database table.

The result query module 14 is used to query the calculation results stored in the database table 12 by the data analysis module 13 . Specifically, the result query module 14 can query data such as relative chance of paternity (RCP) and parental relationship index (PI) between any two samples in the database table; , PI and other data to filter, for example, you can query the calculation results of RCP>0.999 in the database table.

In this embodiment, the data analysis module 13 can also be further used to calculate the prediction error rate under different boundary values, that is, start calculation from the boundary value that produces the minimum prediction error rate, and calculate the error rate under different _WFS boundary values, until the error rate exceeds 1%.

According to the above-mentioned kinship identification device, an embodiment of the present invention also proposes a kinship identification method, as shown in FIG. 2 . The genetic relationship identification method comprises the following steps:

Step 21: Read the data that needs to be analyzed for kinship. The data may be data automatically read from a file in DAT format of the genetic analyzer, or data manually input by a user through an input interface. Wherein, the file in DAT format is formed by the result obtained by the genetic analyzer through the detection of the sample to be analyzed. The read data is stored in a pre-set database table.

In this embodiment, the data saved in the database table can also be modified and deleted, and the newly read data can also be added to the database table.

Step 22: Calculate the parentage index of the genetic relationship between two individuals according to the data saved in the database table. In this embodiment, the relative relationship refers to sibling relationship. Specifically, this step includes: according to the PCR-STR typing results, according to the EssenMoller calculation principle, apply the ITO algorithm, calculate the sibling relationship index PI _FS between any two individuals in the database table 12, and calculate according to the formula W _FS =PI _FS /(PI _FS +1) Calculate the probability of sibling relationship, count the number of genes shared between two individuals, that is, the number of identical alleles in the two comparison individuals, and analyze the alleles of the same locus in each two comparison individuals are completely different, half The same and all the same, and save the analysis results to the database table.

In addition, in order to improve the accuracy of the analysis results, this embodiment can also perform correlation calculations on each newly added data and all data in the database table, and save the calculation results in the database table.

Step 23: Query the calculation result. Specifically, you can query the data such as RCP and PI between any two samples in the database table; you can also filter the data such as RCP and PI that meet a certain threshold condition, for example, you can query the data of RCP>0.999 in the database table Calculation results.

In the following, 151 pairs of sibling individuals and 31224 pairs of unrelated individual autosomal (STR) loci are typed and detected by the Identifiler system commonly used in daily case detection, and the PI value and _WFS are calculated by using the device and method described in the embodiments of the present invention as an example The present invention is further described.

In this specific embodiment, sibling individuals whose _WFS calculated by the data analysis module 13 is greater than 99.999% account for 39.07%, and unrelated individuals whose _WFS is greater than 99.999% account for 0%. The two sets of data have significant differences, so it can be inferred that there is a sibling relationship between the two bodies. When the _WFS calculated by the data analysis module 13 is less than 1%, it can be inferred that there is no sibling relationship between the two bodies. When the _WFS calculated by the data analysis module 13 is within the range of 1% to 99.999%, sibling individuals and unrelated individuals partially overlap. In this specific embodiment, sibling individuals account for 60.93%, unrelated individuals account for 21.3%, and both have certain differences. For the identification of sibling relationship within this range of _WFS , it is possible to increase the detection of STR loci, and then add Y-STR and mtDNA detection in combination with the actual case, so that _WFS will no longer overlap or provide more valuable information. To infer whether there is a sibling relationship between the two bodies.

In this embodiment, the data analysis module 13 analyzes the results of the analysis of the alleles of the same locus of each two comparison individuals being completely different, semi-identical and completely identical, as shown in Table 1.

Since there is a certain relationship between the allele matching between individuals and whether they have a sibling relationship, that is, when the number of identical or completely different alleles of two individuals reaches a certain threshold, it can be prompted as a sibling individual or an unrelated individual. In this embodiment, the calculation is started from the boundary value that produces the minimum prediction error rate, and the error rates under different boundary values are calculated until the error rate exceeds 1%. Then, when the 15 STR loci of the Identifiler system are detected, when the number of the two individuals is more than or equal to 5, or the number of differences is less than or equal to 1, it is indicated as a sibling individual; when the number of differences between the two individuals is greater than or equal to 6, Or when the number of identical individuals is less than or equal to 1, it is indicated as an unrelated individual. As shown in Table 2, this cutoff value can be used to predict whether there is a sibling relationship.

Using the kinship identification device and method provided in this embodiment, the chance of kinship between two individuals can be calculated, such as determining whether the two individuals are siblings. The device and the method turn the complicated compatriot relationship calculation into simple data processing, and greatly improve the reliability and accuracy of the data.

It should be understood that the above descriptions are only some embodiments of the present invention, and the present invention is not limited thereto. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art through modification, equivalent, and substitution without creative work, all belong to the protection scope of the present invention.

Claims (12)

1. A kinship identification device, characterized in that, comprises a data reading module, a database table, a data analysis module and a result query module; The data reading module is used to read data that needs to be analyzed for kinship; The database table is used to save the data read by the data reading module; The data analysis module is used to calculate the parentage index of the kinship relationship between two individuals according to the data stored in the database table, and save the calculation result in the database table; The result query module is used to query the calculation results stored in the database table by the data analysis module. 2. kinship identification device according to claim 1, is characterized in that, described data reading module is used for automatically reading data from the file of DAT format of genetic analyzer, or is used for reading user through input interface Data entered manually. 3. The kinship identification device according to claim 1 or 2, characterized in that, the data reading module is further used to modify and delete the data stored in the database table, and can also read the newly The data is added to the database table. 4. The kinship identification device according to claim 1, characterized in that the data analysis module is used to calculate the sibling relationship index PI _FS between any two bodies in the database table, and according to the formula W _FS =PI _FS / (PI _FS +1) calculates sibling relationship probability. 5. The kinship identification device according to claim 4, wherein the data analysis module is further used to count the number of the same alleles that two individuals have, and analyze the same locus alleles of every two individuals Genes are completely different, half identical and completely identical, and the analysis results are saved in the database table. 6. kinship identification device according to claim 4, is characterized in that, described data analysis module is further used for starting to calculate by the _WFS boundary value that produces minimum prediction error rate, calculates the error rate under different _WFS boundary value , until the error rate exceeds 1%. 7. kinship identification device according to claim 1, is characterized in that, described result query module is used for the paternity relative chance (RCP) and paternity relationship index (PI) between any two samples in the database table etc.; or filter the RCP and PI data that meet the preset threshold conditions. 8. A method for identification of kinship, characterized in that, comprising Read the data that needs to be analyzed for kinship; Calculate the parentage index of the kinship between the two bodies according to the data; Query calculation results. 9. The kinship identification method according to claim 8, characterized in that said reading the data that needs to be analyzed for kinship comprises: automatically reading the data in the file of the DAT format of the genetic analyzer, or reading the data of the user Data entered manually through the input interface. 10. The kinship identification method according to claim 8, characterized in that, said calculating the parentage index of the kinship between two bodies according to said data comprises: calculating the sibling relationship index PI _FS between any two bodies, and according to the formula W _FS =PI _FS /(PI _FS +1) calculates the probability of sibling relationship. 11. kinship identification method according to claim 10, is characterized in that, further comprises: Count the number of identical alleles in two individuals, and analyze the situation of completely different, semi-identical and completely identical alleles of the same locus in each two individuals, and save the analysis results. 12. The kinship identification method according to claim 8, characterized in that, said query calculation result comprises: querying relative chance of paternity (RCP) and parental relationship index (PI) between any two samples, Or filter RCP and PI data that meet preset threshold conditions.

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