Global ancestry estimation method and system based on principal component analysis

Abstract

The application provides a global ancestor estimation method and system based on principal component analysis, which comprises the following steps: based on the principal component analysis method, according to single nucleotide mutation data, projecting the principal components of the to-be-tested offspring samples and the principal components of the ancestral samples into the same two-dimensional plane, and dividing the projected two-dimensional plane into multiple corresponding population regions; fitting the population region of each ancestral sample to obtain an ancestral population fitting region, and obtaining the region density of each ancestral population fitting region; extending each ancestral population fitting region outward at the same proportion, stopping the outward extension when any ancestral population fitting region contains a to-be-tested offspring sample, and obtaining the ancestral population proportion of the current to-be-tested offspring sample according to the region area after the extension and the region density. The application directly calculates the proportion of the corresponding ancestor in the offspring individual or population through the principal component analysis result, and has high accuracy.

Description

Technical Field

[0001] This invention relates to the field of bioinformatics, and more particularly to a global ancestry estimation method and system based on principal component analysis. Background Technology

[0002] Animal ancestry tracing can effectively predict the magnitude and direction of phenotypic variation in their hybrid offspring. Global ancestry estimation helps to detect factors that have a significant impact on breeds during animal evolution and breeding, and is of great significance for hybridization breeding.

[0003] By performing global ancestry estimation of animal species and calculating the proportion of ancestors, we can more accurately trace the origins of species, understand the evolutionary relationships between different varieties of the same animal species and the evolutionary history of the corresponding animals, thus providing conditions for exploring the origin of the corresponding animal species. However, the efficiency of current global ancestry estimation is still relatively low, and its accuracy needs to be further improved.

[0004] Therefore, there is an urgent need for a global ancestor estimation method and system based on principal component analysis to solve the above problems. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a global ancestor estimation method and system based on principal component analysis.

[0006] This invention provides a global ancestor estimation method based on principal component analysis, comprising:

[0007] Based on principal component analysis, the principal components of the offspring samples and the ancestral samples are projected onto the same two-dimensional plane according to single nucleotide mutation data. The projected two-dimensional plane is then divided into regions to obtain multiple corresponding population regions.

[0008] The population region of each ancestor sample is fitted to obtain the ancestor population fitted region, and the region density of each ancestor population fitted region is obtained.

[0009] The fitting region of each ancestral population is extended outward in the same proportion. When any ancestral population fitting region contains a sample of the offspring to be tested, the outward extension is stopped, and the proportion of the ancestral population of the currently contained offspring sample is obtained based on the area of ​​the extended region and the density of the region.

[0010] According to the present invention, a global ancestry estimation method based on principal component analysis is provided. This method projects the principal components of the offspring sample and the ancestral sample onto the same two-dimensional plane based on single nucleotide mutation data, and then divides the projected two-dimensional plane into regions to obtain multiple corresponding population regions, including:

[0011] The first feature vector is obtained based on the single nucleotide mutation data of the offspring sample to be tested, and the second feature vector is obtained based on the single nucleotide mutation data of the ancestral sample.

[0012] Based on the first feature vector and the second feature vector, the offspring sample to be tested and the ancestor sample are projected onto the same two-dimensional plane;

[0013] Each sample on the projected two-dimensional plane is labeled, and the population region is divided according to the labeling results.

[0014] According to the global ancestor estimation method based on principal component analysis provided by the present invention, the population region of each ancestor sample is fitted to obtain the ancestor population fitted region, and the region density of each ancestor population fitted region is obtained, including:

[0015] The least squares ellipse fitting method is used to fit the population region of each ancestor sample into an ellipse region, and the ellipse region is extended outward until it covers all ancestor samples in the current population region, thus obtaining the ancestor population fitting region.

[0016] Obtain the number of ancestral sample points within the fitting region of each ancestral group, and calculate the elliptical area of ​​the fitting region of the ancestral group according to the elliptical area formula.

[0017] Based on the number of ancestral sample points and the area of ​​the ellipse, the region density of the fitted region for each ancestral population is obtained.

[0018] According to the global ancestry estimation method based on principal component analysis provided by the present invention, the method of extending the fitting region of each ancestral population outward by the same proportion, and stopping the outward extension when any ancestral population fitting region contains a sample of the offspring to be tested, includes:

[0019] Using the asymptotic method, the fitted region of each ancestral population is extended outward in the same proportion, while keeping the eccentricity of each ancestral population fitted region unchanged, until the extended ancestral population fitted region contains the offspring sample to be tested. Then the current extension process is stopped, and the area of ​​the extended ancestral population fitted region is calculated.

[0020] According to the global ancestry estimation method based on principal component analysis provided by the present invention, after extending the fitting region of each ancestral population outward at the same proportion, stopping the outward extension when any ancestral population fitting region contains a sample of the offspring to be tested, and obtaining the proportion of the ancestral population of the currently included sample of the offspring to be tested based on the area of ​​the extended region and the density of the region, the method further includes:

[0021] Step S1: After obtaining the proportion of ancestral populations of the offspring samples to be tested included in the previous extension process, continue to extend the fitting region of each ancestral population outwards in the same proportion.

[0022] Step S2: When any ancestral population fitting region contains a test descendant sample, stop extending outward, and obtain the current extension factor of the ancestral population fitting region based on the area of ​​the region after the current extension process and the region density of the ancestral population fitting region, and obtain the ancestral population proportion of the test descendant sample included in the ancestral population fitting region during the current extension process based on the extension factor.

[0023] Step S3: Repeat steps S1 to S2 until the ancestral population proportions of all the offspring samples to be tested are obtained.

[0024] According to the global ancestor estimation method based on principal component analysis provided by the present invention, the step of obtaining the current extension factor of the ancestral population fitting region based on the region area after the current extension process and the region density of the ancestral population fitting region includes:

[0025] Based on the area Sl of the region after the current extension process and the region density N / S of the ancestral population fitting region, the current extension factor ni of the ancestral population fitting region is obtained through the extension factor formula, which is:

[0026]

[0027] Where N represents the number of sample points contained in the ancestral population fitting region before extension, and S represents the area of ​​the ancestral population fitting region before extension.

[0028] According to the global ancestry estimation method based on principal component analysis provided by the present invention, the step of obtaining the proportion of the ancestral population of the test offspring samples included in the ancestral population fitting region during the current extension process, based on the extension factor, includes:

[0029] The ancestral population proportion p of the offspring sample to be tested is calculated based on the extension factor and the ancestral population proportion formula, wherein the ancestral population proportion formula is:

[0030]

[0031] Where k represents k offspring samples to be tested.

[0032] This invention also provides a global ancestry estimation system based on principal component analysis, comprising:

[0033] The principal component projection region construction module is used to project the principal components of the offspring sample and the ancestral sample onto the same two-dimensional plane based on the principal component analysis method and single nucleotide mutation data, and to divide the projected two-dimensional plane into regions to obtain multiple corresponding population regions.

[0034] The ancestor population fitting module is used to fit the population region of each ancestor sample to obtain the ancestor population fitting region and obtain the region density of each ancestor population fitting region.

[0035] The ancestral population proportion acquisition module is used to extend the fitting region of each ancestral population outward at the same proportion. When any ancestral population fitting region contains a sample of the offspring to be tested, the outward extension is stopped, and the ancestral population proportion of the currently contained offspring sample is obtained based on the area of ​​the extended region and the density of the region.

[0036] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the global ancestor estimation method based on principal component analysis as described above.

[0037] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the global ancestor estimation method based on principal component analysis as described above.

[0038] The global ancestry estimation method and system based on principal component analysis provided by this invention can directly calculate the ancestral proportion of the target ancestral group in the offspring individuals or populations under test through principal component analysis results, and has high accuracy. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating the global ancestor estimation method based on principal components provided by this invention;

[0041] Figure 2 A schematic diagram of population region fitting using simulation data provided by this invention;

[0042] Figure 3A schematic diagram illustrating the correlation between the proportion of theoretical ancestral group 2 in the simulation data provided by this invention and the proportion of observed ancestral group 2 calculated according to PCA;

[0043] Figure 4 A schematic diagram of the population fitting region of real data animal species a and three other similar animal species b, c and d provided for this invention.

[0044] Figure 5 A pie chart illustrating the proportion of animal species a in the other three ancestral populations b, c, and d, based on real data provided for this invention.

[0045] Figure 6 A schematic diagram of the structure of the global ancestor estimation system based on principal component analysis provided by the present invention;

[0046] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0048] Figure 1 This is a flowchart illustrating the global ancestry estimation method based on principal components provided by the present invention, as shown below. Figure 1 As shown, this invention provides a global ancestry estimation method based on principal component analysis, comprising:

[0049] Step 101: Based on the principal component analysis method, according to the single nucleotide mutation data, the principal components of the offspring samples to be tested and the principal components of the ancestral samples are projected onto the same two-dimensional plane, and the projected two-dimensional plane is divided into regions to obtain multiple corresponding population regions.

[0050] In this invention, Principal Component Analysis (PCA) is used to project the offspring and ancestral samples onto a two-dimensional plane, and the offspring and ancestral samples are divided according to sample type; simultaneously, different ancestral samples are also divided accordingly. Specifically, based on sample labels (including offspring sample labels and different ancestral labels), and according to the degree of focus, each group is marked and displayed on the projected two-dimensional plane, and divided into groups with corresponding labels.

[0051] Step 102: Fit the population region of each ancestor sample to obtain the ancestor population fitting region, and obtain the region density of each ancestor population fitting region.

[0052] In this invention, the direct least squares method is used to obtain the fitted elliptical region corresponding to the ancestral population sample points based on the distribution of sample points within the ancestral population. Then, according to the ellipse equation, the ancestral sample point farthest from the fitted elliptical region is calculated. The fitted elliptical region is extended outwards until it covers the farthest ancestral sample point, ensuring that the newly obtained fitted ellipse covers the vast majority of sample points in the ancestral population. Further, based on the fitted ellipse equation, the relative distance between the ancestral sample points and their respective elliptical regions is calculated, the number N of non-ellipse external points is calculated, and the ellipse area S is calculated using the ellipse area formula. N / S represents the region density of the divided ancestral population fitted region.

[0053] Step 103: Extend the fitting region of each ancestral population outward in the same proportion. When any ancestral population fitting region contains a sample of the offspring to be tested, stop extending outward and obtain the ancestral population proportion of the currently contained offspring sample of the offspring to be tested based on the area of ​​the extended region and the density of the region.

[0054] In this invention, the ancestral population fitting region is extended outward proportionally until one of the ancestral population fitting regions contains the corresponding offspring sample points outside that region. Then, based on the area of ​​the extended region and the regional density of the ancestral population fitting region obtained in the above embodiment, the proportion of each ancestral population in each offspring sample in the offspring population to be tested is calculated.

[0055] The global ancestry estimation method based on principal component analysis provided by this invention directly calculates the ancestral proportion of the corresponding target ancestral group in the offspring individuals or populations under test through principal component analysis results, and has high accuracy.

[0056] Based on the above embodiments, the principal component analysis method, according to single nucleotide mutation data, projects the principal components of the offspring sample and the ancestral sample onto the same two-dimensional plane, and divides the projected two-dimensional plane into regions to obtain multiple corresponding population regions, including:

[0057] The first feature vector is obtained based on the single nucleotide mutation data of the offspring sample to be tested, and the second feature vector is obtained based on the single nucleotide mutation data of the ancestral sample.

[0058] Based on the first feature vector and the second feature vector, the offspring sample to be tested and the ancestor sample are projected onto the same two-dimensional plane;

[0059] Each sample on the projected two-dimensional plane is labeled, and the population region is divided according to the labeling results.

[0060] In this invention, the SmartPCA software is used to obtain the feature vectors corresponding to each sample based on the VCF file containing the single nucleotide mutations (SNVs) of the above samples, that is, to obtain the feature vectors and feature value data after dimensionality reduction based on the PCA method; then, the first principal component and the second principal component are selected to project the sample points of all populations onto a two-dimensional plane for graphical display.

[0061] Based on the above embodiments, the population region of each ancestor sample is fitted to obtain the ancestor population fitted region, and the region density of each ancestor population fitted region is obtained, including:

[0062] The least squares ellipse fitting method is used to fit the population region of each ancestor sample into an ellipse region, and the ellipse region is extended outward until it covers all ancestor samples in the current population region, thus obtaining the ancestor population fitting region.

[0063] Obtain the number of ancestral sample points within the fitting region of each ancestral group, and calculate the elliptical area of ​​the fitting region of the ancestral group according to the elliptical area formula.

[0064] Based on the number of ancestral sample points and the area of ​​the ellipse, the region density of the fitted region for each ancestral population is obtained.

[0065] In this invention, based on the sample points, an elliptical region of the ancestral population sample points is fitted using the Least Squares Fitting of Ellipses method. By proportionally extending the elliptical region, it is ensured that most sample points of the ancestral population can be covered. After counting the number N of ancestral sample points within the extended elliptical region, the area S of each elliptical region is calculated to obtain the region density N / S. The above method specifically includes:

[0066] Step 1: Use the Python module LsqEllipse, which is based on the direct least squares ellipse fitting method, to fit the elliptical region of the already divided population.

[0067] Step 2: Obtain the equation formula of the ellipse and the relevant parameters of the elliptical region, mainly including the major semi-axis a, the minor semi-axis b and the offset angle alpha (relative to the X-axis), and calculate the relative distance between the ancestral group sample points and the ellipse based on the properties of the ellipse equation.

[0068] Step 3: Based on the relative distance, calculate the ancestral sample point px that is farthest from the ellipse in the ancestral population. Then, keeping the ellipse offset angle alpha and eccentricity b / a constant, extend outwards until the ancestral sample point px is covered. Calculate the relative distance between all ancestral sample points and the extended ellipse again, comparing the relative distance to 1. If the relative distance is less than 1, the ancestral sample point is inside the ellipse; if it equals 1, it is on the ellipse boundary; and if it is greater than 1, it is outside the ellipse. Count the number N of sample points outside the ellipse, calculate the area S of the elliptical region as π*a*b, and obtain the region density as N / S.

[0069] Based on the above embodiments, the step of extending the fitting region of each ancestral population outward at the same proportion, and stopping the outward extension when any ancestral population fitting region contains a sample of the offspring to be tested, includes:

[0070] Using the asymptotic method, the fitted region of each ancestral population is extended outward in the same proportion, while keeping the eccentricity of each ancestral population fitted region unchanged, until the extended ancestral population fitted region contains the offspring sample to be tested. Then the current extension process is stopped, and the area of ​​the extended ancestral population fitted region is calculated.

[0071] In this invention, an asymptotic method is used to expand the elliptical region fitted by the ancestral population outward while maintaining its eccentricity, until the expanded elliptical region covers the offspring sample points to be tested. The area of ​​the expanded ellipse is then calculated, along with the expansion factor of the elliptical region. Specifically, in this invention, the elliptical eccentricity of the ancestral population fitted region is kept constant (i.e., the b / a ratio remains constant), and the ellipse is extended outward until the offspring sample points outside the original fitted ellipse are included within the elliptical region. Then, the area Sl of the extended ellipse is obtained, and the region density N / S of the corresponding ancestral population fitted region is calculated using the above embodiment. Based on the calculated expansion factor ni of the current ancestral population fitted region, the expansion factor nx of all ancestral population fitted regions corresponding to the currently covered offspring sample points is further obtained, thereby calculating the proportion p of the ancestral population corresponding to the offspring sample point.

[0072] Based on the above embodiments, after extending each ancestral population fitting region outward at the same proportion, stopping the outward extension when any ancestral population fitting region contains a test descendant sample, and obtaining the ancestral population proportion of the currently included test descendant sample based on the extended region area and the region density, the method further includes:

[0073] Step S1: After obtaining the proportion of ancestral populations of the offspring samples to be tested included in the previous extension process, continue to extend the fitting region of each ancestral population outwards in the same proportion.

[0074] Step S2: When any ancestral population fitting region contains a test descendant sample, stop extending outward, and obtain the current extension factor of the ancestral population fitting region based on the area of ​​the region after the current extension process and the region density of the ancestral population fitting region, and obtain the ancestral population proportion of the test descendant sample included in the ancestral population fitting region during the current extension process based on the extension factor.

[0075] Step S3: Repeat steps S1 to S2 until the ancestral population proportions of all the offspring samples to be tested are obtained.

[0076] Based on the above embodiments, obtaining the current extension factor of the ancestral population fitting region according to the area of ​​the region after the current extension process and the region density of the ancestral population fitting region includes:

[0077] Based on the area Sl of the region after the current extension process and the region density N / S of the ancestral population fitting region, the current extension factor ni of the ancestral population fitting region is obtained through the extension factor formula, which is:

[0078]

[0079] Where N represents the number of sample points contained in the ancestral population fitting region before extension, and S represents the area of ​​the ancestral population fitting region before extension.

[0080] Based on the above embodiments, obtaining the proportion of the ancestral population of the test offspring samples that include the ancestral population fitting region in the current extension process according to the extension factor includes:

[0081] The ancestral population proportion p of the offspring sample to be tested is calculated based on the extension factor and the ancestral population proportion formula, wherein the ancestral population proportion formula is:

[0082]

[0083] Where k represents k offspring samples to be tested.

[0084] In one embodiment, simulated data of the known ancestral population proportions are obtained using SliM software to test the accuracy of the global ancestry estimation method based on principal component analysis provided by this invention. Specifically, Figure 2 A schematic diagram illustrating population region fitting using the simulation data provided in this invention can be found here. Figure 2 As shown, using the SliM software and based on the corresponding parameters set in the configuration file, five sets of offspring samples (4, 5, 6, 7, and 8) with ancestral population proportions changing in a 10% gradient were obtained from two ancestral populations, 2 and 3. A total of seven sets of data are presented. Table 1 shows the five sets of hybrid offspring samples simulated by the SliM software in this embodiment of the invention.

[0085] Table 1

[0086] Group number Ancestor group 2 percentage Ancestor group 3% 4 0.1 0.9 5 0.2 0.8 6 0.3 0.7 7 0.4 0.6 8 0.5 0.5

[0087] In this invention, the output files of SliM include tree and VCF files. Based on the tree file, the theoretical ancestral population proportion of the simulated offspring samples can be calculated. Based on the VCF file, a MAF screening threshold of 0.05 is set to perform quality control on the mutations. Using SmartPCA software, principal components 1 and 2 are obtained from the VCF file. Principal components 1 and 2 are then projected onto a two-dimensional planar graph.

[0088] Furthermore, the Python module LsqEllipse, which uses an ellipse fitting method based on direct least squares, is used to fit elliptical regions to the ancestor sample points of each group. The equation of the ellipse is output, and based on the ellipse's deflection angle alpha relative to the X-axis, its semi-major axis a, and semi-minor axis b, the distance from the ancestor sample points outside the ellipse to the ellipse is calculated, thus obtaining the farthest ancestor sample point px. Then, using an asymptotic method, keeping alpha and b / a constant, the ellipse is gradually expanded, and the distance d from the expanded ellipse to the farthest ancestor sample point px is continuously calculated until d is less than 0.001. This expanded ellipse and its equation are then obtained, and it becomes the fitted ellipse for the corresponding ancestor group, covering the vast majority of ancestor group sample points.

[0089] Furthermore, based on the method described above, the elliptical regions of the two ancestral populations 2 and 3 and the five descendant populations 4, 5, 6, 7, and 8 generated by the SliM software are fitted. Then, for the simulated descendant hybrid populations 4, 5, 6, 7, and 8, the PCA method is used to calculate the proportion of each descendant sample corresponding to ancestral population 2 and ancestral population 3, respectively. The specific method is consistent with the above calculation of the farthest point fitting ellipse, based on the extension factor formula:

[0090]

[0091] Calculate the extension factor ni of the fitted ellipse for ancestral populations 2 and 3 corresponding to the descendant sample points, based on the ancestral population ratio formula:

[0092]

[0093] Calculate the proportion of descendant sample points corresponding to ancestral group 2 and ancestral group 3.

[0094] In addition, based on the tree file generated by SliM, the ancestral proportions of each descendant sample corresponding to ancestral group 2 and ancestral group 3 during the original simulation were calculated.

[0095] Furthermore, based on the ancestral population proportions obtained from PCA and those calculated from the tree file, the Pearson correlation between the two proportions was calculated, yielding a Pearson correlation coefficient of 0.85 (p-value < 0.001). Figure 3 A schematic diagram illustrating the correlation between the proportion of theoretical ancestral group 2 in the simulation data provided by this invention and the proportion of observed ancestral group 2 calculated according to PCA can be referenced. Figure 3 As shown, it is feasible and accurate to directly calculate the proportion of the corresponding ancestral group in the offspring sample or offspring population based on PCA.

[0096] In another embodiment, the ancestral proportion calculation is performed on the population data of real animal species a and three other animal species b, c, and d (b, c, and d are the ancestral populations of animal species a). The specific steps for calculating the ancestral proportion of the offspring samples to be tested include:

[0097] Data from four population samples (a, b, c, and d) were obtained, and principal components were obtained by performing PCA analysis using SmartPCA software. Figure 4 A schematic diagram of the population fitting region for real data samples of animal species a and three other similar animal species b, c, and d provided for this invention, as shown in the figure. Figure 4 As shown, according to the global ancestry estimation method provided by this invention, the corresponding projected region ellipses of the four populations are first fitted. To facilitate the subsequent calculation of the proportion of the corresponding ancestral population, the expansion factor of the 16 samples in group a in the corresponding three populations b, c, and d ellipses is calculated, corresponding to the transformation value 1 / ni, as shown in Table 2:

[0098] Table 2

[0099] sample_id X1 X2 1 / ni(b) 1 / ni(c) 1 / ni(d) a_1 0.0874 0.023 6.16655E-05 1.0628E-06 8.989E-07 a_2 0.0826 0.0204 4.67075E-05 1.1557E-06 9.896E-07 a_3 0.0732 0.0206 2.59645E-05 1.4199E-06 1.2587E-06 a_4 0.0835 0.0207 4.91397E-05 1.1362E-06 9.707E-07 a_5 0.0799 0.0191 4.04109E-05 1.2144E-06 1.0482E-06 a_6 0.0843 0.0188 0.000053164 1.1066E-06 9.415E-07 a_7 0.0798 0.0178 0.000041045 1.2085E-06 1.0415E-06 a_8 0.0804 0.017 4.26977E-05 1.1878E-06 1.0211E-06 a_9 0.0797 0.0207 3.83043E-05 1.2307E-06 1.0642E-06 a_10 0.0854 0.0176 5.66498E-05 1.0754E-06 9.109E-07 a_11 0.0879 0.0228 6.41136E-05 1.0512E-06 8.877E-07 a_12 0.0843 0.0172 0.000053164 0.000001097 9.323E-07 a_13 0.0843 0.0175 5.36417E-05 0.000001099 9.337E-07 a_14 0.0798 0.0165 4.16943E-05 1.1998E-06 1.0332E-06 a_15 0.0874 0.0185 6.41136E-05 1.0382E-06 8.754E-07 a_16 0.079 0.0217 3.53142E-05 1.2561E-06 1.0904E-06

[0100] Then, the three ancestral groups are paired up, for example, d_b means that d and b are considered ancestors, and d_b_c means that all three ancestral groups are considered ancestors simultaneously, according to the ancestral group ratio formula. The ancestral population proportions of the 16 samples in group a are calculated, as shown in Table 3:

[0101] Table 3

[0102]

[0103]

[0104] Take the average of the ancestral proportions of the 16 samples in variety a after calculation. Figure 5 A pie chart illustrating the proportion of animal species a in the other three ancestral populations b, c, and d, provided for the present invention. Figure 5 As shown, among varieties a, variety b has the highest proportion of ancestors.

[0105] This embodiment establishes an ancestral population proportion detection method based on PCA analysis results. Data analysis is performed on simulated data with known ancestral proportions and real animal species data with unknown ancestral proportions to obtain relatively reliable ancestral proportion analysis results, verifying the correctness and accuracy of the method. Furthermore, using population data of real animal species a and three other similar animal species b, c, and d, the ancestral component proportion of species a in b, c, and d was identified, revealing a close relationship between a and b.

[0106] Figure 6 This is a schematic diagram of the structure of the global ancestor estimation system based on principal component analysis provided by the present invention, as shown below. Figure 6 As shown, this invention provides a global ancestry estimation system based on principal component analysis, including a principal component projection region construction module 601, an ancestor population fitting module 602, and an ancestor population proportion acquisition module 603. The principal component projection region construction module 601, based on principal component analysis and single nucleotide mutation data, projects the principal components of the offspring sample to be tested and the principal components of the ancestral sample onto the same two-dimensional plane, and divides the projected two-dimensional plane into regions to obtain multiple corresponding population regions. The ancestor population fitting module 602 fits the population region of each ancestral sample to obtain an ancestral population fitting region and acquires the region density of each ancestral population fitting region. The ancestor population proportion acquisition module 603 extends each ancestral population fitting region outwards at the same proportion. When any ancestral population fitting region contains an offspring sample to be tested, the outward extension stops, and the ancestral population proportion of the currently contained offspring sample is obtained based on the extended region area and the region density.

[0107] The global ancestry estimation system based on principal component analysis provided by this invention can directly calculate the ancestral proportion of the target ancestral group in the offspring individuals or populations under test through principal component analysis results, and has high accuracy.

[0108] The system provided in this embodiment of the invention is used to execute the above-described method embodiments. For specific processes and details, please refer to the above embodiments, which will not be repeated here.

[0109] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 7As shown, the electronic device may include a processor 701, a communication interface 702, a memory 703, and a communication bus 704. The processor 701, communication interface 702, and memory 703 communicate with each other via the communication bus 704. The processor 701 can call logical instructions in the memory 703 to execute a global ancestor estimation method based on principal component analysis. This method includes: based on principal component analysis, projecting the principal components of the offspring sample to be tested and the principal components of the ancestral sample onto the same two-dimensional plane according to single nucleotide mutation data, and dividing the projected two-dimensional plane into regions to obtain multiple corresponding population regions; fitting the population region of each ancestral sample to obtain an ancestral population fitting region, and obtaining the region density of each ancestral population fitting region; extending each ancestral population fitting region outwards at the same proportion; stopping the outward extension when any ancestral population fitting region contains the offspring sample to be tested, and obtaining the ancestral population proportion of the currently contained offspring sample to be tested based on the extended region area and the region density.

[0110] Furthermore, the logical instructions in the aforementioned memory 703 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0111] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the global ancestor estimation method based on principal component analysis provided by the above methods, the method comprising: based on the principal component analysis method, according to single nucleotide mutation data, projecting the principal components of the offspring sample to be tested and the principal components of the ancestral sample onto the same two-dimensional plane, and dividing the projected two-dimensional plane into regions to obtain multiple corresponding population regions; fitting the population region of each ancestral sample to obtain an ancestral population fitting region, and obtaining the region density of each ancestral population fitting region; extending each ancestral population fitting region outward at the same proportion, stopping the outward extension when any ancestral population fitting region contains the offspring sample to be tested, and obtaining the ancestral population proportion of the currently contained offspring sample to be tested based on the extended region area and the region density.

[0112] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the global ancestor estimation method based on principal component analysis provided in the above embodiments. The method includes: based on principal component analysis, projecting the principal components of the offspring sample to be tested and the principal components of the ancestral sample onto the same two-dimensional plane according to single nucleotide mutation data, and dividing the projected two-dimensional plane into regions to obtain multiple corresponding population regions; fitting the population region of each ancestral sample to obtain an ancestral population fitting region, and obtaining the region density of each ancestral population fitting region; extending each ancestral population fitting region outward at the same proportion, stopping the outward extension when any ancestral population fitting region contains the offspring sample to be tested, and obtaining the ancestral population proportion of the currently contained offspring sample to be tested based on the extended region area and the region density.

[0113] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0114] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A global ancestor estimation method based on principal component analysis, characterized in that, include: Based on principal component analysis, the principal components of the offspring samples and the ancestral samples are projected onto the same two-dimensional plane according to single nucleotide mutation data. The projected two-dimensional plane is then divided into regions to obtain multiple corresponding population regions. The least squares method is used to fit an ellipse to the population region of each ancestor sample to obtain the ancestor population fitting region, and the region density of each ancestor population fitting region is obtained. The fitting region for each ancestral population is extended outwards at the same proportion. When any ancestral population fitting region contains a sample of the offspring to be tested, the outward extension stops. Based on the area of ​​the extended region and the region density, the proportion of the ancestral population of the currently included offspring sample to be tested is obtained, including: Based on the area of ​​the region after the current extension process Sl Regional density of the region fitted to the ancestral population N / S The current extension factor of the ancestral population fitting region is obtained by using the extension factor formula. ni The formula for the extension ratio is: ； in, N This indicates the number of sample points contained in the ancestral population fitting region before extension. S This represents the area of ​​the ancestral population fitted region before extension; The ancestral population proportion of the offspring sample to be tested is calculated based on the extension factor and the ancestral population proportion formula. p The formula for the proportion of the ancestral population is: ； in, k express k One offspring sample to be tested.

2. The global ancestor estimation method based on principal component analysis according to claim 1, characterized in that, The principal component analysis-based method projects the principal components of the offspring samples and the ancestral samples onto the same two-dimensional plane based on single nucleotide mutation data. The projected two-dimensional plane is then divided into regions to obtain multiple corresponding population regions, including: The first feature vector is obtained based on the single nucleotide mutation data of the offspring sample to be tested, and the second feature vector is obtained based on the single nucleotide mutation data of the ancestral sample. Based on the first feature vector and the second feature vector, the offspring sample to be tested and the ancestor sample are projected onto the same two-dimensional plane; Each sample on the projected two-dimensional plane is labeled, and the population region is divided according to the labeling results.

3. The global ancestor estimation method based on principal component analysis according to claim 1, characterized in that, The process involves using the least squares method to fit an ellipse to the population region of each ancestor sample, obtaining the ancestor population fitted region, and acquiring the region density of each ancestor population fitted region, including: The least squares ellipse fitting method is used to fit the population region of each ancestor sample into an ellipse region, and the ellipse region is extended outward until it covers all ancestor samples in the current population region, thus obtaining the ancestor population fitting region. Obtain the number of ancestral sample points within the fitting region of each ancestral population, and calculate the elliptical area of ​​the fitting region of the ancestral population according to the elliptical area formula. Based on the number of ancestral sample points and the area of ​​the ellipse, the region density of the fitted region for each ancestral population is obtained.

4. The global ancestor estimation method based on principal component analysis according to claim 1, characterized in that, The step of extending the fitting region of each ancestral population outwards at the same proportion, and stopping the outward extension when any ancestral population fitting region contains a sample of the offspring to be tested, includes: Using the asymptotic method, the fitted region of each ancestral population is extended outward in the same proportion, while keeping the eccentricity of each ancestral population fitted region unchanged, until the extended ancestral population fitted region contains the offspring sample to be tested. Then the current extension process is stopped, and the area of ​​the extended ancestral population fitted region is calculated.

5. The global ancestor estimation method based on principal component analysis according to claim 1, characterized in that, After extending the fitting region of each ancestral population outwards at the same proportion, stopping the outward extension when any ancestral population fitting region contains a sample of the offspring to be tested, and obtaining the proportion of the ancestral population of the currently included offspring sample of the offspring to be tested based on the area of ​​the extended region and the region density, the method further includes: Step S1: After obtaining the proportion of ancestral populations of the offspring samples to be tested included in the previous extension process, continue to extend the fitting region of each ancestral population outwards in the same proportion. Step S2: When any ancestral population fitting region contains a test descendant sample, stop extending outward, and obtain the current extension factor of the ancestral population fitting region based on the area of ​​the region after the current extension process and the region density of the ancestral population fitting region, and obtain the ancestral population proportion of the test descendant sample included in the ancestral population fitting region during the current extension process based on the extension factor. Step S3: Repeat steps S1 to S2 until the ancestral population proportions of all the offspring samples to be tested are obtained.

6. A global ancestor estimation system based on principal component analysis, characterized in that, The system is used to implement the global ancestor estimation method based on principal component analysis as described in any one of claims 1 to 5.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the global ancestor estimation method based on principal component analysis as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the global ancestor estimation method based on principal component analysis as described in any one of claims 1 to 5.

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