Mixed DNA sample donor proportion analysis method based on STR typing and residual matrix analysis

Abstract

The invention discloses a mixed DNA sample donor proportion analysis method based on STR typing and residual matrix analysis, which comprises the following steps: firstly, calculating the minimum donor number in a sample through a maximum allele counting method, further fitting the genotype distribution of the sample through an optimization algorithm, comparing the difference between the predicted peak height and the actually measured peak height, and determining the donor proportion of the sample according to the difference between the predicted peak height and the actually measured peak height. Therefore, the proportion of each donor in the mixed DNA sample is accurately estimated. Experimental results show that when the method is used for processing a multi-allele mixed DNA sample, estimation errors existing in a traditional method can be effectively reduced, and particularly, high accuracy is shown in complex sample analysis. By establishing a linear model and combining an optimization algorithm, the method not only provides high-precision technical support for DNA analysis in forensic science, but also provides a feasible solution for quantitative analysis of mixed DNA samples in other fields.

Description

Technical Field

[0001] The present invention relates to the field of biological detection technology, and in particular to a mixed DNA sample donor ratio analysis method based on STR typing and residual matrix analysis. Background Art

[0002] Mixed DNA samples are samples mixed from multiple donors, and are common in forensic identification and genetic analysis. The analysis of existing mixed DNA samples relies on the experience of DNA analysts and their understanding of DNA data. Usually, the analysis is performed on markers such as STR (short tandem repeats), and the contribution of different donors is judged based on the possible patterns of each marker in the mixed DNA sample (such as the number of repeats, size differences, etc.). Specifically, through methods such as cluster maps and genetic marker analysis maps (such as spectra or electrophoresis maps), technicians can manually analyze the intensity and frequency of each marker in the sample and preliminarily split the DNA of different individuals. For experienced technicians, intuitively judging the signal intensity, heterozygosity and homology of a position can help them make judgments without the assistance of advanced software. This manual method is usually used for relatively simple mixed DNA sample analysis, but when faced with multi-source complex samples, manual splitting is often inefficient, and the results are easily affected by personal experience and subjective judgment. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention aims to provide a mixed DNA sample donor ratio analysis method based on STR typing and residual matrix analysis.

[0004] In order to achieve the above object, the present invention adopts the following technical solution:

[0005] The mixed DNA sample donor ratio analysis method based on STR typing and residual matrix analysis includes the following steps:

[0006] S1. Determine the number of donors: After obtaining the mixed DNA sample, perform PCR amplification and capillary electrophoresis in sequence to obtain the size and fluorescence intensity information of each DNA fragment, and then further generate a map and perform genotype analysis to obtain the allele and peak height information of each site; the maximum value of the number of alleles at each site is taken as the maximum allele number, and the maximum allele number is determined according to the maximum allele number;

[0007] S2. Calculate the peak height ratio: for each locus, calculate the ratio of the peak height of each allele in the locus to the total peak height of all alleles in the locus, so as to obtain the peak height ratio of each allele at the locus;

[0008] S3. Generate residual matrix:

[0009] The mixing ratio of donor 1 is defined as a variable Mx, and the initial value, end value and step length of the variable Mx are defined, thereby obtaining all values ​​of the variable Mx;

[0010] At a locus, a corresponding allele mixing ratio matrix is ​​generated for each value of the variable Mx. Each row in the allele mixing ratio matrix corresponds to a possible genotype combination of two donors at the locus, and each column represents the allele mixing ratio calculated for each allele at the locus according to the mixing ratio Mx of donor 1.

[0011] At a locus, the following calculations are performed on the allele mixing ratio matrix corresponding to each value of the variable Mx and the corresponding matrix columns are generated:

[0012] First, the updated value of each column in the i-th row of the allele mixing ratio matrix is ​​calculated as follows:

[0013] updated_m(i)=(column_m[i]-x) 2

[0014] Where i∈[1,2,…,N], N represents the total number of rows of the allele mixing ratio matrix, column_m[i] represents the value of the i-th row and m-th column in the allele mixing ratio matrix, and x represents the peak height ratio of the allele corresponding to the m-th column at the corresponding site;

[0015] Then the value of the i-th row in the matrix column, i.e. the residual sum of squares RSS, is calculated as follows:

[0016] RSS[i]=updated_1(i)+updated_2(i)+,…,+updated_M(i)

[0017] M represents the total number of columns of the allele mixing ratio matrix;

[0018] Finally, the matrix columns corresponding to all values ​​of the variable Mx at a site are combined to obtain the residual matrix of the site; each row in the residual matrix corresponds to a genotype combination, each column corresponds to a value of the mixing ratio variable Mx, and each element represents the residual sum of squares under the corresponding genotype combination and mixing ratio;

[0019] S4, according to the residual matrix corresponding to each site obtained in step S3, draw a mixing ratio-logarithmic residual relationship diagram corresponding to each site, each curve in the mixing ratio-logarithmic residual relationship diagram represents a genotype combination, the abscissa is the mixing ratio, and the ordinate is the logarithmic residual calculated according to the residual square sum;

[0020] S5. After obtaining the admixture ratio-logarithmic residual relationship graph corresponding to all sites, the genotype combination and admixture ratio corresponding to the lowest point in the admixture ratio-logarithmic residual relationship graph are the most likely genotype combination and admixture ratio of the corresponding site;

[0021] S6. Calculate the average value of the mixing ratio corresponding to the most likely genotype combination of all sites, and perform genotype splitting to obtain the final analysis result.

[0022] Furthermore, in step S3, the initial value of the variable Mx is 0, the end value is 1, and the step length is 0.01.

[0023] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0024] The present invention also provides a computer device, comprising a processor and a memory, wherein the memory is used to store a computer program; and when the processor is used to execute the computer program, the above method is implemented.

[0025] The beneficial effect of the present invention is that the present invention combines the maximum allele counting method and the residual sum of squares (RSS) optimization fitting technology, which can accurately determine the contribution ratio of each donor in the mixed DNA sample. First, the minimum number of donors in the sample is calculated by the maximum allele counting method, and the genotype distribution of the sample is further fitted by the optimization algorithm, and the difference between the predicted peak height and the actual measured peak height is compared, so as to accurately estimate the proportion of each donor in the mixed DNA sample. The experimental results show that the present invention can effectively reduce the estimation error existing in the traditional method when processing multi-allelic mixed DNA samples, especially showing higher accuracy in complex sample analysis. By establishing a linear model and combining an optimization algorithm, the present invention not only provides high-precision technical support for DNA analysis in forensic science, but also provides a practical solution for the quantitative analysis of mixed DNA samples in other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is the STR typing spectrum of sample 16.4 in Example 1 of the present invention;

[0027] Figure 2 is a graph showing the relationship between the CSF1PO mixing ratio and the residual in Example 1 of the present invention;

[0028] Figure 3 is a graph showing the relationship between the D3S1358 mixing ratio and the residual in Example 1 of the present invention;

[0029] Figure 4 is a graph showing the relationship between the D18S51 mixing ratio and the residual in Example 1 of the present invention;

[0030] Figure 5 A graph showing the relationship between the D19S433 mixing ratio and the residual in Example 1 of the present invention;

[0031] Figure 6 is a graph showing the relationship between the FGA mixing ratio and the residual in Example 1 of the present invention;

[0032] Figure 7 is a graph showing the relationship between the TH01 mixing ratio and the residual in Example 1 of the present invention;

[0033] Figure 8 is the STR typing spectrum of sample 12.8 in Example 2 of the present invention;

[0034] Fig. 9 is a graph showing the relationship between the CSF1PO mixing ratio and the residual in Example 2 of the present invention;

[0035] Fig.10 is a graph showing the relationship between the D3S1358 mixing ratio and the residual in Example 2 of the present invention;

[0036] Fig.11 is a graph showing the relationship between the D18S51 mixing ratio and the residual in Example 2 of the present invention;

[0037] Fig.12 is a graph showing the relationship between the D19S433 mixing ratio and the residual in Example 2 of the present invention;

[0038] Fig.13 is a graph showing the relationship between the FGA mixing ratio and the residual in Example 2 of the present invention;

[0039] Fig.14 1 is a graph showing the relationship between the TH01 mixing ratio and the residual in Example 2 of the present invention. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with the accompanying drawings. It should be noted that this embodiment is based on the technical solution and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to this embodiment.

[0041] This embodiment provides a mixed DNA sample donor ratio analysis method based on STR typing and residual matrix analysis, which is implemented based on the maximum allele counting method, heterozygote balance analysis, and residual square sum optimization fitting. It includes the following steps:

[0042] S1. Determine the number of donors.

[0043] After obtaining the mixed DNA sample, PCR amplification and capillary electrophoresis are performed in sequence to obtain the size and fluorescence intensity information of each DNA fragment, based on which a map is further generated and genotype analysis is performed to obtain the allele and peak height information of each site; the maximum value of the number of alleles at each site is taken as the maximum number of alleles, and the minimum number of donors is calculated based on the maximum number of alleles, thereby determining how many donors are contained in the mixed DNA sample at least.

[0044] Take sample 16.4 as an example (standard products 9947A and 9948 are mixed in a ratio of 16:4). Figure 1 As shown, there are 3 alleles at CSF1PO, D3S1358, TH01, D19S433, D18S51, and FGA loci. It is known that one donor has 2 alleles at one locus, and the number of alleles at multiple loci is greater than 2, indicating that there is more than one donor. 3 divided by 2, rounded up is 2. Preliminary analysis shows that the number of donors in the mixed DNA sample is 2. However, the mixing ratio and the genotypes of the two donors at each locus cannot be determined.

[0045] The allele and peak height information at each site obtained based on sample 16.4 is shown in Table 1.

[0046] Table 1 Allele peak height information of samples

[0047]

[0048]

[0049] S2. Calculate the peak height ratio. For each locus, sort each allele in the locus from small to large according to the molecular weight, and calculate the proportion of the peak height of each allele in the total peak height of all alleles in the locus, so as to obtain the peak height ratio of each allele at the locus.

[0050] Taking CSF1PO in Table 1 as an example, allele 10, allele 11, and allele 12 are re-sorted from small to large according to molecular weight and named a, b, and c respectively. The proportion of the peak height of each allele in the total peak height is calculated, as shown in Table 2.

[0051] Table 2 Allele peak height information of samples

[0052]

[0053] S3. Generate a residual matrix.

[0054] The mixing ratio of donor 1 is defined as a variable Mx, whose initial value is 0, end value is 1, and step length is 0.01. That is: Mx∈[0.0,0.01,0.02,…,1.0]. At a locus, a corresponding allele mixing ratio matrix is ​​generated for each value of the variable Mx. Each row in the allele mixing ratio matrix corresponds to the possible genotype combination of the two donors at the locus, and each column represents the allele mixing ratio calculated for each allele at the locus according to the mixing ratio Mx of donor 1.

[0055] Continuing with CSF1PO in Table 1 as an example, the allele mixing ratio matrix is ​​shown in Table 3.

[0056] Table 3 Generate allele mixing ratio matrix

[0057]

[0058] At a locus, the following calculations are performed on the allele mixing ratio matrix corresponding to each value of the variable Mx and the corresponding matrix columns are generated:

[0059] First, the updated value of each column in the i-th row of the allele mixing ratio matrix is ​​calculated as follows:

[0060] updated_m(i)=(column_m[i]-x) 2

[0061] Wherein, i∈[1,2,…,N], N represents the total number of rows of the allele mixing ratio matrix, column_m[i] represents the value of the i-th row and the m-th column in the allele mixing ratio matrix, and x represents the peak height ratio of the allele corresponding to the m-th column at the corresponding site (calculated in step S2).

[0062] Then the value of the i-th row in the matrix column, i.e. the residual sum of squares RSS, is calculated as follows:

[0063] RSS[i]=updated_1(i)+updated_2(i)+,…,+updated_M(i)

[0064] M represents the total number of columns of the allele mixing ratio matrix;

[0065] Finally, the matrix columns corresponding to all values ​​of the variable Mx at a site are combined to obtain the residual matrix of the site; each row in the residual matrix corresponds to a genotype combination, each column corresponds to a value of the mixing ratio variable Mx, and each element represents the residual sum of squares under the corresponding genotype combination and mixing ratio.

[0066] Taking Table 3 as an example, for each allele mixing ratio matrix corresponding to the Mx value, the following calculations are performed:

[0067] Calculate the updated value of column_A[i]:

[0068] updated_A(i)=(column_A[i]-0.47) 2

[0069] Calculate the updated value of column_B[i]:

[0070] updated_B(i)=(column_B[i]-0.15) 2

[0071] Calculate the updated value of matrix column column_C[i]:

[0072] updated_C(i)=(column_C[i]-0.38) 2

[0073] Then calculate the residual sum of squares RSS:

[0074] RSS[i]=updated_A(i)+updated_B(i)+updated_C(i)

[0075] For example, for Mx=0, the residual sum of squares of 12 genotype combinations can be calculated according to Table 3, thereby obtaining the matrix columns shown in Table 4.

[0076] Table 4, residual sum of squares of each gene habit combination when Mx=0

[0077]

[0078] The same calculation is performed for other Mx values, and finally the residual matrix can be combined as shown in Table 5.

[0079] Table 5

[0080]

[0081] It should be noted that the step size of the actual variable Mx is 0.01, and the matrix column data of some Mx values ​​are omitted in Table 5.

[0082] S4, draw the mixing ratio-logarithmic residual graph. The residual values ​​are more, from 0 to 1, the step length is 0.01, one genotype has 100 residuals, a total of 12 genotypes, a total of 1200 residual data, for observation convenience, in the present embodiment, according to the residual matrix corresponding to each site obtained in step S3, the mixing ratio-logarithmic residual relationship diagram corresponding to each site is drawn, and each curve in the mixing ratio-logarithmic residual relationship diagram represents a genotype combination, the abscissa is the mixing ratio, and the ordinate is the logarithmic residual calculated according to the residual sum of squares (the ordinate is the logarithm of the residual sum of squares with 10 as the base), and taking the logarithm is to compress the data and increase the contrast effect.

[0083] S5. After obtaining the mixing ratio-logarithmic residual relationship diagram of each site, find the lowest point of the mixing ratio-logarithmic residual relationship diagram. The genotype combination and mixing ratio corresponding to the lowest point are the most likely genotype combination and mixing ratio of the corresponding site.

[0084] Figure 2 The following is the relationship between the mixing ratio and the logarithmic residual corresponding to CSF1PO: Figure 2 As shown, the lowest point corresponds to ab and ac, which are the most likely genotype combinations, and the corresponding mixing ratios are 0.27 (the mixing ratio value corresponding to the lowest point of the curve) and 0.73.

[0085] The mixing ratio-logarithmic residual relationship diagrams of the remaining sites D3S1358, D18S51, D19S433, FGA, and TH01 are shown as follows: Figure 3 , 4 , 5, 6, and 7 as shown.

[0086] like Figure 3 As shown, for locus D3S1358, cc, ab are the most likely genotype combinations, and the admixture ratios are 0.09 and 0.91.

[0087] like Figure 4 As shown, for the locus D18S51, bb, ac are the most likely genotype combinations, and the admixture ratios are 0.15 and 0.85.

[0088] like Figure 5 As shown, for locus D19S433, ab, bc are the most likely genotype combinations, and the mixing ratios are 0.27 and 0.73.

[0089] like Figure 6 As shown, for the locus FGA, bc, ab are the most likely genotype combinations, and the mixing ratios are 0.18 and 0.82.

[0090] like Figure 7As shown, for locus TH01, ac, bc are the most likely genotype combinations, and the admixture ratios are 0.19 and 0.81.

[0091] S6. Calculate the average value of the mixing ratio corresponding to the most likely genotype combination of all sites, and perform genotype splitting to obtain the final analysis result.

[0092] In this example, the mixing ratios of CSF1PO, D3S1358, TH01, D19S433, D18S51, and FGA were averaged, and the average mixing ratio of donor 1 was 0.19, and the average mixing ratio of donor 2 was 0.81. The genotype splitting results are shown in Table 6.

[0093] Table 6 Average admixture ratio and allele splitting

[0094]

[0095] S7. Verification.

[0096] The known typing of 9947A and 9948 is shown in Table 7:

[0097] Table 7 Genotypes of Standards

[0098]

[0099] As shown in Table 7, the correct typing at each locus and the splitting results shown in Table 6 are not accurate, but the result of calculating the mixing ratio using the average value is 0.19:0.81, while the actual mixing ratio is 0.2:0.8, with an error of about 6.5%, which is relatively accurate.

[0100] Example 2

[0101] This embodiment provides another application example of the method of embodiment 1 with another sample 12.8 (standard products 9947A and 9948 are mixed in a ratio of 12:8), including the following steps:

[0102] S1. Determine the number of donors. After obtaining the mixed DNA sample, perform PCR amplification and capillary electrophoresis in sequence to obtain the size and fluorescence intensity information of each DNA fragment, and then further generate a map and perform genotype analysis to obtain the allele and peak height information of each site; the maximum value of the number of alleles at each site is taken as the maximum number of alleles, and the minimum number of donors is calculated based on the maximum number of alleles, thereby determining how many donors are contained in the mixed DNA sample at least.

[0103] like Figure 8As shown, there are 3 alleles at CSF1PO, D3S1358, TH01, D19S433, D18S51, and FGA loci. It is known that one donor has 2 alleles at one locus, and the number of alleles at multiple loci is greater than 2, indicating that there is more than one donor. 3 divided by 2, rounded up is 2. Preliminary analysis shows that the number of donors in the mixed DNA sample is 2. However, the mixing ratio and the genotypes of the two donors at each locus cannot be determined.

[0104] The allele height at each site in the mixed DNA sample is derived. The specific information is shown in Table 8:

[0105] Table 8 Allele peak height information of samples

[0106]

[0107]

[0108] S2. Calculate the peak height ratio. Taking CSF1PO as an example, allele 10, allele 11, and allele 12 are re-sorted from small to large according to their molecular weight and named a, b, and c respectively. Calculate the proportion of the peak height of each allele in the total peak height. As shown in Table 9.

[0109] Table 9 Allele peak height information of samples

[0110]

[0111] S3, generating a residual matrix. The method used is the same as step S3 of embodiment 1. Taking CSF1PO as an example, the obtained residual matrix is ​​shown in Table 10.

[0112] Table 10 Residual table under different Mx

[0113]

[0114]

[0115] It should be noted that the step size of the actual variable Mx is 0.01, and the column data of some Mx values ​​are omitted in Table 10.

[0116] S4. Draw the relationship between the mixing ratio and the logarithmic residual.

[0117] The process of drawing the mixing ratio-logarithmic residual relationship diagram is the same as that in Example 1.

[0118] S5. Obtain the mixing ratio-logarithmic residual relationship diagram for all loci CSF1PO, D3S1358, TH01, D19S433, D18S51, and FGA, and find the lowest point of the mixing ratio-logarithmic residual relationship diagram. The genotype combination and mixing ratio corresponding to the lowest point are the most likely genotype combination and its mixing ratio for the corresponding locus.

[0119] In this embodiment, the mixing ratio-logarithmic residual relationship diagram of CSF1PO is as follows Fig. 9 As shown. Among them, the lowest point corresponds to aa, bc, which is the most likely genotype combination, and the corresponding mixing ratio is 0.46 and 0.54.

[0120] The mixing ratio-logarithmic residual relationship diagrams of D3S1358, D18S51, D19S433, FGA, and TH01 are shown in Figure 2. Fig.10 , 11 , 12, 13, and 14.

[0121] like Fig.10 As shown, bc and ab are the most likely genotype combinations, and the mixing ratios are 0.32 and 0.68.

[0122] like Fig.11 As shown, ab and ac are the most likely genotype combinations, and the mixing ratios are 0.46 and 0.54.

[0123] like Fig.12 As shown, ab and bc are the most likely genotype combinations, and the mixing ratios are 0.46 and 0.54.

[0124] like Fig.13 As shown, bc and ab are the most likely genotype combinations, and the mixing ratios are 0.37 and 0.63.

[0125] like Fig.14 As shown, ac and bc are the most likely genotype combinations, and the mixing ratios are 0.36 and 0.64.

[0126] S6. Calculate the average value of the mixing ratio corresponding to the most likely genotype combination of all sites, and perform genotype splitting to obtain the final analysis result. In this embodiment, the results are shown in Table 11.

[0127] Table 11 Average admixture ratio and allele splitting

[0128]

[0129] S7. Verification.

[0130] The known typing of 9947A and 9948 is shown in Table 12.

[0131] Table 12 Genotypes of Standards

[0132]

[0133]

[0134] As shown in Table 12, the correct typing at each locus and the splitting results shown in Table 11 are highly accurate, with only CSF1PO having an error. The result of calculating the mixing ratio using the average value is 0.41:0.59, while the actual mixing ratio is 0.4:0.6, with an error of approximately 2.1%, which is relatively accurate.

[0135] For those skilled in the art, various corresponding changes and modifications can be made according to the above technical solutions and concepts, and all of these changes and modifications should be included in the protection scope of the claims of the present invention.

Claims

1. A mixed DNA sample donor ratio analysis method based on STR typing and residual matrix analysis, characterized in that: The steps include: S1. Determine the number of donors: After obtaining the mixed DNA sample, perform PCR amplification and capillary electrophoresis in sequence to obtain the size and fluorescence intensity information of each DNA fragment, and then further generate a map and perform genotype analysis to obtain the allele and peak height information of each site; the maximum value of the number of alleles at each site is taken as the maximum allele number, and the maximum allele number is determined according to the maximum allele number; S2. Calculate the peak height ratio: for each locus, calculate the ratio of the peak height of each allele in the locus to the total peak height of all alleles in the locus, so as to obtain the peak height ratio of each allele at the locus; S3. Generate residual matrix: The mixing ratio of donor 1 is defined as a variable Mx, and the initial value, end value and step length of the variable Mx are defined, thereby obtaining all values ​​of the variable Mx; At a locus, a corresponding allele mixing ratio matrix is ​​generated for each value of the variable Mx. Each row in the allele mixing ratio matrix corresponds to a possible genotype combination of two donors at the locus, and each column represents the allele mixing ratio calculated for each allele at the locus according to the mixing ratio Mx of donor 1. At a locus, the following calculations are performed on the allele mixing ratio matrix corresponding to each value of the variable Mx and the corresponding matrix columns are generated: First, the updated value of each column in the i-th row of the allele mixing ratio matrix is ​​calculated as follows: updated_m(i)=(column_m[i]-x) 2 Where i∈[1,2,…,N], N represents the total number of rows of the allele mixing ratio matrix, column_m[i] represents the value of the i-th row and m-th column in the allele mixing ratio matrix, and x represents the peak height ratio of the allele corresponding to the m-th column at the corresponding site; Then the value of the i-th row in the matrix column, i.e. the residual sum of squares RSS, is calculated as follows: RSS[i]=updated_1(i)+updated_2(i)+,…,+updated_M(i) M represents the total number of columns of the allele mixing ratio matrix; Finally, the matrix columns corresponding to all values ​​of the variable Mx at a site are combined to obtain the residual matrix of the site; each row in the residual matrix corresponds to a genotype combination, each column corresponds to a value of the mixing ratio variable Mx, and each element represents the residual sum of squares under the corresponding genotype combination and mixing ratio; S4, according to the residual matrix corresponding to each site obtained in step S3, draw a mixing ratio-logarithmic residual relationship diagram corresponding to each site, each curve in the mixing ratio-logarithmic residual relationship diagram represents a genotype combination, the abscissa is the mixing ratio, and the ordinate is the logarithmic residual calculated according to the residual square sum; S5. After obtaining the admixture ratio-logarithmic residual relationship graph corresponding to all sites, the genotype combination and admixture ratio corresponding to the lowest point in the admixture ratio-logarithmic residual relationship graph are the most likely genotype combination and admixture ratio of the corresponding site; S6. Calculate the average value of the mixing ratio corresponding to the most likely genotype combination of all sites, and perform genotype splitting to obtain the final analysis result.

2. The method according to claim 1, characterized in that In step S3, the initial value of the variable Mx is 0, the end value is 1, and the step length is 0.

01.

3. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 2 is implemented.

4. A computer device, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store a computer program; when the processor is used to execute the computer program, the method described in any one of claims 1 to 2 is implemented.

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