Genetic information processing system, genetic information processing method, and recording medium

Abstract

A genetic information processing system (10) is provided with: a first acquisition means (110) for acquiring distribution information of a microsatellite in a gene after PCR; a second acquisition means (120) for acquiring a first ratio (a) indicating the amplification factor of the microsatellite for each PCR cycle, a second ratio (b, c) indicating the ratio of stutters occurring from the microsatellite for each PCR cycle, and the PCR cycle count (n); and a calculation means (130) for calculating the distribution of the microsatellite in the gene prior to PCR on the basis of the distribution information of the microsatellite in the gene after PCR, the first ratio, the second ratio, and the PCR cycle count.

Description

[Technical field]

[0001] The present disclosure relates to the technical fields of a genetic information processing system, a genetic information processing method, and a recording medium for executing processing related to genetic information. [Background technology]

[0002] As this type of system, those that handle information on stutters occurring in PCR (Polymerase Chain Reaction) are known. For example, Patent Document 1 describes estimating the relative height of stutters that appear after PCR amplification. Patent Document 2 discloses a technique for peak determination regardless of whether a peak obtained by PCR is a true peak or a noise peak. Patent Document 3 discloses calculating a percent stutter and calculating an average percent stutter by summarizing the values ​​of any sample. Patent Document 4 discloses optimizing model parameters including peak position, peak height, and stutter rate. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2006-163720 A [Patent Document 2] JP 2006-079334 A [Patent Document 3] Special Publication No. 2004-533241 [Patent Document 4] Special Publication No. 2004-516455 Summary of the Invention [Problem to be solved by the invention]

[0004] This disclosure has been made in consideration of, for example, the above-mentioned cited documents, and aims to provide a genetic information processing system, a genetic information processing method, and a recording medium capable of appropriately executing genetic processing. [Means for solving the problem]

[0005] One aspect of the genetic information processing system disclosed herein comprises a first acquisition means for acquiring distribution information of microsatellites in the gene after PCR, a second acquisition means for acquiring a first ratio indicating the amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating the ratio of stutters occurring from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR, and a calculation means for calculating the distribution of the microsatellites in the gene before the PCR based on the distribution information of the microsatellites in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR.

[0006] One aspect of the genetic information processing method disclosed herein obtains distribution information of microsatellites in a gene after PCR, obtains a first ratio indicating the amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating the ratio of stutters occurring from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR, and calculates the distribution of the microsatellites in the gene before the PCR based on the distribution information of the microsatellites in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR.

[0007] One embodiment of the recording medium of this disclosure has recorded thereon a computer program that causes a computer to obtain distribution information of microsatellites in a gene after PCR, obtain a first ratio indicating the amplification rate of the microsatellites per cycle of the PCR, a second ratio indicating the ratio of stutters occurring from the microsatellites per cycle of the PCR, and the number of cycles of the PCR, and calculate the distribution of the microsatellites in the gene before the PCR based on the distribution information of the microsatellites in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a hardware configuration of a genetic information processing system according to a first embodiment. [Diagram 2] FIG. 1 is a block diagram showing the functional configuration of a genetic information processing system according to a first embodiment. [Diagram 3] 1 is a graph showing an example of stuttering that occurs in PCR. [Figure 4] 3 is a flowchart showing the flow of operations of the genetic information processing system according to the first embodiment. [Diagram 5] FIG. 11 is a block diagram showing the functional configuration of a genetic information processing system according to a second embodiment. [Figure 6] 1 is a graph showing an example of −1 stutter. [Figure 7] FIG. 1 is a conceptual diagram showing a method for estimating the amount of stutter amplicon. [Figure 8] 13 is a flowchart showing the flow of operations of the genetic information processing system according to the second embodiment. [Figure 9] 1 is a graph showing an example of −2 stutter and +2 stutter. [Figure 10] FIG. 13 is a block diagram showing the functional configuration of a genetic information processing system according to a fourth embodiment. [Figure 11]13 is a flowchart showing the flow of operations of the genetic information processing system according to the fourth embodiment. [Figure 12] FIG. 13 is a conceptual diagram showing an example in which both the rate at which negative stutter occurs and the rate at which positive stutter occurs are taken into consideration. [Figure 13] FIG. 13 is a block diagram showing the functional configuration of a genetic information processing system according to a sixth embodiment. [Figure 14] 1 is a determinant showing an example of an amplification matrix that models amplification by PCR. [Figure 15] 13 is a flowchart showing the flow of operations of the genetic information processing system according to the sixth embodiment. [Figure 16] FIG. 13 is a block diagram showing the functional configuration of a genetic information processing system according to a seventh embodiment. [Figure 17] 20 is a flowchart showing the flow of operations of the genetic information processing system according to the seventh embodiment. [Figure 18] 23 is a graph showing the estimated amount and actual amount of genetic information calculated in the genetic information processing system according to the eighth embodiment. [Figure 19] 1 is a graph showing the relationship between the number of repetitions and the −1 stutter ratio. [Figure 20] 13 is a graph showing a method for estimating the rate at which stutter occurs by data fitting. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, embodiments of a genetic information processing system, a genetic information processing method, a computer program, and a recording medium will be described with reference to the drawings.

[0010] First Embodiment A genetic information processing system according to a first embodiment will be described with reference to FIGS. 1 to 4. FIG.

[0011] (Hardware configuration) First, the hardware configuration of a genetic information processing system 10 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the hardware configuration of the genetic information processing system according to the first embodiment.

[0012] 1, the genetic information processing system 10 according to the first embodiment includes a processor 11, a RAM (Random Access Memory) 12, a ROM (Read Only Memory) 13, and a storage device 14. The genetic information processing system 10 may further include an input device 15 and an output device 16. The processor 11, the RAM 12, the ROM 13, the storage device 14, the input device 15, the output device 16, and the camera 20 are connected via a data bus 17.

[0013] The processor 11 reads a computer program. For example, the processor 11 is configured to read a computer program stored in at least one of the RAM 12, the ROM 13, and the storage device 14. Alternatively, the processor 11 may read a computer program stored in a computer-readable storage medium using a storage medium reading device (not shown). The processor 11 may acquire (i.e., read) a computer program from a device (not shown) disposed outside the gene information processing system 10 via a network interface. The processor 11 controls the RAM 12, the storage device 14, the input device 15, and the output device 16 by executing the computer program that the processor 11 reads. In particular, in this embodiment, when the processor 11 executes the computer program that the processor 11 reads, a functional block for executing processing related to gene information is realized in the processor 11. In addition, the processor 11 may be one of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an FPGA (field-programmable gate array), a DSP (Demand-Side Platform), and an ASIC (Application Specific Integrated Circuit), or may be a plurality of devices in parallel.

[0014] The RAM 12 temporarily stores a computer program executed by the processor 11. The RAM 12 temporarily stores data that is temporarily used by the processor 11 when the processor 11 is executing the computer program. The RAM 12 may be, for example, a D-RAM (Dynamic RAM).

[0015] The ROM 13 stores computer programs executed by the processor 11. The ROM 13 may also store other fixed data. The ROM 13 may be, for example, a programmable ROM (P-ROM).

[0016] The storage device 14 stores data to be stored long-term by the genetic information processing system 10. The storage device 14 may operate as a temporary storage device for the processor 11. The storage device 14 may include, for example, at least one of a hard disk device, a magneto-optical disk device, an SSD (Solid State Drive), and a disk array device.

[0017] The input device 15 is a device that receives input instructions from a user of the genetic information processing system 10. The input device 15 may include, for example, at least one of a keyboard, a mouse, and a touch panel.

[0018] The output device 16 is a device that outputs to the outside information related to the genetic information processing system 10. For example, the output device 16 may be a display device (for example, a display) that can display information related to the genetic information processing system 10.

[0019] (Functional configuration) Next, the functional configuration of the genetic information processing system 10 according to the first embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the functional configuration of the genetic information processing system according to the first embodiment.

[0020] 2, the genetic information processing system 10 according to the first embodiment includes, as processing blocks for realizing its functions, a first acquisition unit 110, a second acquisition unit 120, and a calculation unit 130. Each of the first acquisition unit 110, the second acquisition unit 120, and the calculation unit 130 may be realized, for example, in the above-mentioned processor 11 (see FIG. 1).

[0021] The first acquisition unit 110 is configured to be able to acquire distribution information of microsatellites in genes after PCR. The first acquisition unit 110 may acquire the distribution information of microsatellites, for example, as a result of an experiment conducted in advance (i.e., an amplification process using PCR). The distribution information of microsatellites may be distribution information of microsatellites in one organism (i.e., a single organism), or may be distribution information of microsatellites in multiple organisms (e.g., distribution information obtained from a mixed sample). Note that even if originating from a single organism, there may be two types of microsatellites at one gene locus (more precisely, one or two types). The distribution information of microsatellites may be distribution information of two types of microsatellites originating from such a single organism.

[0022] The second acquisition unit 120 is configured to be able to acquire a first ratio indicating the amplification rate of the microsatellite for each cycle of PCR, a second ratio indicating the ratio of stutters generated from the microsatellite for each cycle of PCR, and the number of cycles of PCR. The second acquisition unit 120 may acquire at least one of the first ratio, the second ratio, and the number of cycles of PCR as a known value input by, for example, a user. Alternatively, the second acquisition unit 120 may estimate and acquire at least one of the first ratio, the second ratio, and the number of cycles of PCR from other parameters. Note that a method for estimating each parameter will be described in detail in another embodiment described later.

[0023] The calculation unit 130 is configured to be capable of calculating the distribution of microsatellites in the gene before PCR based on the distribution information of microsatellites in the gene after PCR acquired by the first acquisition unit 110, and the first ratio, the second ratio, and the number of PCR cycles acquired by the second acquisition unit 120. That is, the calculation unit 130 is configured to be capable of calculating the original (i.e., before amplification) distribution of microsatellites in the gene that was the subject of PCR. A specific calculation method by the calculation unit 130 will be described in detail in another embodiment described later.

[0024] (Stutter) Next, stuttering that occurs in PCR will be specifically described with reference to Figure 3. Figure 3 is a graph showing an example of stuttering that occurs in PCR.

[0025] As shown in Fig. 3, when genetic information is amplified by PCR, a noise called stutter is detected in addition to the real genetic information (hereinafter referred to as "true allele" as appropriate). The peak of the stutter is detected at a position with a smaller or larger number of repeat units than the peak position of the true allele. The genetic information processing system 10 according to this embodiment calculates the distribution of microsatellites in the gene before PCR by obtaining the rate at which this stutter occurs as a second rate. In other words, even if stutter occurs during PCR amplification, it is possible to obtain distribution information before amplification corresponding to the true allele.

[0026] (Operation flow) Next, the flow of operations of the genetic information processing system 10 according to the first embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing the flow of operations of the genetic information processing system according to the first embodiment.

[0027] As shown in FIG. 4, when the genetic information processing system 10 according to the first embodiment operates, first, the first acquisition unit 110 acquires distribution information of microsatellites in genes after PCR (step S101).

[0028] Next, the second acquisition unit 120 acquires the first ratio (step S102), acquires the second ratio (step S103), and acquires the number of PCR cycles (step S104). Note that the order in which the first ratio, the second ratio, and the number of PCR cycles are acquired is not limited to the above order, and they may be acquired one after the other, or simultaneously.

[0029] Next, the calculation unit 130 calculates the distribution of microsatellites in the gene before PCR based on the distribution information of microsatellites in the gene after PCR acquired by the first acquisition unit 110 and the first ratio, the second ratio, and the number of PCR cycles acquired by the second acquisition unit 120 (step S105). The calculation unit 130 may have a function of outputting the calculated distribution of microsatellites in the gene before PCR. The calculation unit 130 may display the calculated distribution of microsatellites on a display or the like, for example.

[0030] (Technical effect) Next, technical effects obtained by the genetic information processing system 10 according to the first embodiment will be described.

[0031] 1 to 4, in the genetic information processing system 10 according to the first embodiment, the distribution of microsatellites in genes before PCR is calculated based on distribution information of microsatellites in genes after PCR, the first ratio, the second ratio, and the number of PCR cycles. In this way, it is possible to appropriately calculate the distribution of microsatellites in genes before PCR, taking into account the presence of stutters that occur in PCR.

[0032] <Second embodiment> A genetic information processing system 10 according to the second embodiment will be described with reference to Fig. 5 to Fig. 8. The second embodiment differs from the first embodiment only in some operations, and may be the same as the first embodiment (see Fig. 1) in terms of, for example, hardware configuration, etc. For this reason, in the following, descriptions of parts that overlap with the first embodiment will be omitted as appropriate.

[0033] (Functional configuration) First, the functional configuration of the genetic information processing system 10 according to the second embodiment will be described with reference to Fig. 5. Fig. 5 is a block diagram showing the functional configuration of the genetic information processing system according to the second embodiment. In Fig. 5, the same components as those shown in Fig. 2 are denoted by the same reference numerals.

[0034] 5, the genetic information processing system 10 according to the second embodiment includes, as processing blocks for realizing its functions, a first acquisition unit 110, a second acquisition unit 120, and a calculation unit 130. In particular, the calculation unit 130 according to the second embodiment includes an amplicon amount estimation unit 131.

[0035] The amplicon amount estimation unit 131 is configured to be capable of estimating the amount of an amplicon of a stutter having one less repeat unit (hereinafter, appropriately referred to as a "-1 stutter") or a stutter having one more repeat unit (hereinafter, appropriately referred to as a "+1 stutter") using the first ratio, the second ratio, and the number of cycles of the PCR method. The calculation unit 130 according to the second embodiment is configured to be capable of calculating the distribution of microsatellites in the gene before PCR using the amplicon amount of the -1 stutter or +1 stutter estimated by the amplicon amount estimation unit 131.

[0036] (-1 stutter) Next, the -1 stutter, which is used by the amplicon amount estimating unit 131 to estimate the amplicon amount, will be specifically described with reference to Fig. 6. Fig. 6 is a graph showing an example of the -1 stutter.

[0037] As shown in FIG. 6, the peak of the -1 stutter is detected at a position where the number of repeat units is one less than the position of the peak of the true allele. The peak of the -1 stutter occurs more frequently than other stutters, and the peak size is also relatively large. Therefore, if the amplicon amount of the -1 stutter can be estimated, the distribution of the microsatellite of the true allele can be calculated with high accuracy. The specific method for estimating the amplicon amount of the -1 stutter will be described in detail below.

[0038] (Method of estimating amplicon amount) Next, a method for estimating the amount of amplicon in a stutter will be specifically described with reference to Figure 7. Figure 7 is a conceptual diagram showing a method for estimating the amount of amplicon in a stutter.

[0039] As shown in Figure 7, consider the case where "five repeats" of genetic information are amplified by PCR. For ease of explanation, consider the case where only -1 stutter occurs. Also, the amplification rate of microsatellites per cycle of PCR (i.e., the first rate) is "a", the rate of stutters occurring from microsatellites per cycle of PCR (i.e., the second rate) is "b", and the number of PCR cycles is "n".

[0040] As can be seen from Figure 7, when PCR was performed three times, the amount of amplicon in "five repeats" was a 3 The amount of amplicon in the −1 stutter (i.e., “four repeats”) is 3×a 2 × b. If PCR is repeated for n cycles, the amount of amplicon for "five cycles" is a n The amount of amplicon for a −1 stutter (i.e., “four repeats”) is nC1×a n-1 ×b (C is combination).

[0041] As described above, the amount of amplicon of -1 stutter can be estimated by using the first ratio a, the second ratio b, and the number of PCR cycles n. Although not described here, the amount of amplicon of +1 stutter (i.e., stutter detected at a position where the number of repeat units is one more than the position of the peak of the true allele) may be estimated. When estimating the amount of amplicon of +1 stutter, in addition to the above-mentioned first ratio a and second ratio b, the third ratio c at which a positive stutter occurs may be considered. The configuration using the third ratio c will be described in detail in another embodiment (the fifth embodiment) described later.

[0042] (Operation flow) Next, the flow of operations of the genetic information processing system 10 according to the second embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the flow of operations of the genetic information processing system according to the second embodiment. In Fig. 8, the same processes as those shown in Fig. 4 are denoted by the same reference numerals.

[0043] As shown in FIG. 8, when the genetic information processing system 10 according to the second embodiment operates, first, the first acquisition unit 110 acquires distribution information of microsatellites in genes after PCR (step S101).

[0044] Next, the second acquiring section 120 acquires the first ratio (step S102), acquires the second ratio (step S103), and acquires the number of PCR cycles (step S104).

[0045] Next, the amplicon amount estimation unit 131 estimates the amplicon amount of -1 stutter or the amplicon amount of +1 stutter using the first ratio, the second ratio, and the number of PCR cycles (step S201).Then, the calculation unit 130 calculates the distribution of microsatellites in the gene before PCR using the amplicon amount estimated by the amplicon amount estimation unit 131 (step S202).

[0046] (Technical effect) Next, the technical effects obtained by the genetic information processing system 10 according to the second embodiment will be described.

[0047] 5 to 8, in the genetic information processing system 10 according to the second embodiment, the amount of amplicon of -1 stutter or +1 stutter is estimated, and the distribution of microsatellites in the gene before PCR is calculated using the estimated amount of amplicon. In this way, it is possible to appropriately calculate the distribution of microsatellites in the gene before PCR, taking into account the presence of -1 stutter or +1 stutter that occurs in PCR.

[0048] <Third embodiment> A genetic information processing system 10 according to the third embodiment will be described with reference to Fig. 9. The third embodiment differs from the second embodiment described above only in the type of stutters it handles, and the system configuration and overall operation flow may be the same as those of the second embodiment. For this reason, in the following, explanations of parts that overlap with parts already described will be omitted as appropriate.

[0049] (Configuration of amplicon amount estimation unit) In the genetic information processing system 10 according to the third embodiment, the amplicon amount estimation unit 131 estimates the amount of an amplicon of a stutter having two fewer repeat units (hereinafter, appropriately referred to as a "-2 stutter") or a stutter having two fewer repeat units (hereinafter, appropriately referred to as a "+2 stutter"). The amplicon amount estimation unit 131 typically estimates the amount of an amplicon of a -2 stutter or +2 stutter together with the amount of an amplicon of a -1 stutter or +1 stutter already described in the second embodiment. However, the amplicon amount estimation unit 131 may estimate only the amount of an amplicon of a -2 stutter or +2 stutter without estimating the amount of an amplicon of a -1 stutter or +1 stutter.

[0050] (-2 stutter and +2 stutter) Next, the −2 stutter and +2 stutter for which the amplicon amount estimation unit 131 according to the third embodiment estimates the amplicon amount will be specifically described with reference to Fig. 9. Fig. 9 is a graph showing an example of the −2 stutter and +2 stutter.

[0051] As shown in FIG. 9, the peak of the -2 stutter is detected at a position where the number of repeat units is two less than the position of the peak of the true allele. On the other hand, the peak of the +2 stutter is detected at a position where the number of repeat units is two more than the position of the peak of the true allele. The -2 stutter occurs when the phenomenon of the -1 stutter occurs twice. Similarly, the +2 stutter occurs when the phenomenon of the +1 stutter occurs twice. Therefore, the occurrence rate of the -2 stutter and the +2 stutter is smaller than that of the -1 stutter and the +1 stutter, and the size of the peak is relatively small. However, if the amount of the amplicon of the -2 stutter and the +2 stutter can be estimated, the distribution of the microsatellite of the true allele can be calculated more accurately. The specific method for estimating the amount of the amplicon of the -2 stutter and the +2 stutter will be described in detail below.

[0052] (Method of estimating amplicon amount) Next, a method for estimating the amount of amplicon of a stutter will be specifically described with reference to the already-mentioned Fig. 7. Note that various conditions are assumed to be the same as those described in the second embodiment.

[0053] In FIG. 7, as already explained, when PCR is performed for three cycles, the amount of amplicon in "five repeats" is a 3 The amount of amplicon in the −1 stutter (i.e., “four repeats”) is 3×a 2 In this case, the amount of amplicon in a −2 stutter (i.e., a “triple repeat”) is 3×a×b 2 It becomes.

[0054] And when PCR is repeated n cycles, the amount of amplicon in "five cycles" is a n and the amount of amplicon for a -1 stutter (i.e., "4 repeats") is nC1 x a n-1 In this case, the amount of amplicon for a -2 stutter (i.e., "triple repeat") is nC2 x a n-2 ×b 2-1 stutter ratio SR -1 can be expressed as (amount of amplicon for "four repeats") / (amount of amplicon for "five repeats"), so using the above values, SR -1 =(nC1×a n-1 ×b) / (a n ) = nC1 × b / a = n × b / a. Similarly, the -2 stutter ratio SR -2 can be expressed as (amount of amplicon for "three repeats") / (amount of amplicon for "five repeats"), so using the above values, SR -2 =(nC2×a n-2 ×b 2 ) / (a n )=nC2×b 2 / a 2 = 1 / 2 × n × (n-1) × b 2 / a 2 ≒1 / 2×(n×b / a) 2 =1 / 2×(SR -1 ) 2 It can be expressed as:

[0055] As described above, the amount of amplicon of -2 stutter can be estimated by using the first ratio a, the second ratio b, and the number of PCR cycles n. Although the explanation here is omitted, the amount of amplicon of +2 stutter can also be estimated by a similar method. In the above example, the explanation was given on the premise that -2 stutter occurs when the phenomenon of -1 stutter occurs twice, but the possibility of -2 stutter occurring in one PCR process may be considered. In this case, in addition to the above first ratio a and second ratio b, the rate at which -2 stutter occurs may be used. This value may be approximated, for example, by a quadratic expression of "x repetitions". Similarly, the possibility of -3 stutter occurring in one PCR process may be considered. In this case, the rate at which -3 stutter occurs may be used. This value may be approximated, for example, by a cubic expression (or an expression of cubic or higher order) of "x repetitions".

[0056] (Technical effect) Next, the technical effects obtained by the genetic information processing system 10 according to the third embodiment will be described.

[0057] 9, in the genetic information processing system 10 according to the third embodiment, the amount of amplicon of -2 stutter or +2 stutter is estimated, and the distribution of microsatellites in the gene before PCR is calculated using the estimated amount of amplicon. In this way, it is possible to appropriately calculate the distribution of microsatellites in the gene before PCR, taking into account the presence of -2 stutter or +2 stutter that occurs in PCR.

[0058] In the embodiments described above, examples have been given of estimating the amplicon amounts of -1 stutter, +1 stutter, -2 stutter, and +2 stutter. However, it is also possible to estimate the amplicon amounts of stutters with three or more fewer or more repeat units (e.g., -3 stutter, +3 stutter, etc.) and calculate the distribution of microsatellites in the gene before PCR.

[0059] <Fourth embodiment> A genetic information processing system 10 according to the fourth embodiment will be described with reference to Fig. 10 and Fig. 11. The fourth embodiment differs from the first to third embodiments in only some of the configurations and operations, and other parts may be the same as the first to third embodiments. Therefore, in the following, explanations of parts that overlap with parts already described will be omitted as appropriate.

[0060] (Functional configuration) First, the functional configuration of the genetic information processing system 10 according to the fourth embodiment will be described with reference to Fig. 10. Fig. 10 is a block diagram showing the functional configuration of the genetic information processing system according to the fourth embodiment. In Fig. 10, the same components as those shown in Fig. 2 are denoted by the same reference numerals.

[0061] 10, the genetic information processing system 10 according to the fourth embodiment is configured to include, as processing blocks for realizing its functions, a first acquisition section 110, a second acquisition section 120, and a calculation section 130. In particular, the calculation section 130 according to the fourth embodiment includes a stutter ratio estimation section 132.

[0062] The stutter ratio estimation unit 132 is configured to be able to estimate a stutter ratio, which is the ratio of the amount of stutter amplicons to the amount of microsatellite amplicons amplified by PCR, using the first ratio, the second ratio, and the number of cycles of the PCR method. The stutter that is the subject of the stutter ratio may be a negative stutter with a small number of repeat units (e.g., -1 stutter or -2 stutter), or a positive stutter with a large number of repeat units (e.g., +1 stutter or +2 stutter). The calculation unit 130 according to the fourth embodiment is configured to be able to calculate the distribution of microsatellites in genes before PCR, using the stutter ratio estimated by the stutter ratio estimation unit 132.

[0063] (How to calculate the stutter ratio) The stutter ratio can be calculated using the amount of amplicon of each stutter as described above. For example, the stutter ratio r1 of the −1 stutter in the example shown in FIG. 7 can be calculated as the amount of amplicon of 4 repetitions (i.e., −1 stutter) divided by the amount of amplicon of 5 repetitions. Specifically, the stutter ratio r1 of the −1 stutter is calculated by (nC1×a n-1 ×b)÷a n =nC1 × (b / a). Similarly, the stutter ratio r2 of the -2 stutter can be calculated as "the amount of the amplicon with three repetitions (i.e., the -2 stutter)" ÷ "the amount of the amplicon with five repetitions". Specifically, the stutter ratio r2 of the -2 stutter is (nC2 × a n-2 ×b 2 )÷a n =nC2×(b / a) 2 It becomes.

[0064] Although only the stutter ratio r1 of the -1 stutter and the stutter ratio r2 of the -2 stutter have been described here, other stutter ratios can also be calculated in a similar manner.

[0065] (Operation flow) Next, the flow of operations of the genetic information processing system 10 according to the fourth embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the flow of operations of the genetic information processing system according to the fourth embodiment. In Fig. 11, the same processes as those shown in Fig. 4 are denoted by the same reference numerals.

[0066] As shown in FIG. 11, when the genetic information processing system 10 according to the fourth embodiment operates, first, the first acquisition unit 110 acquires distribution information of microsatellites in genes after PCR (step S101).

[0067] Next, the second acquiring section 120 acquires the first ratio (step S102), acquires the second ratio (step S103), and acquires the number of PCR cycles (step S104).

[0068] Next, the stutter ratio estimation unit 132 estimates a stutter ratio using the first ratio, the second ratio, and the number of PCR cycles (step S401). Then, the calculation unit 130 calculates the distribution of microsatellites in the gene before PCR using the stutter ratio estimated by the stutter ratio estimation unit 132 (step S402).

[0069] (Technical effect) Next, the technical effects obtained by the genetic information processing system 10 according to the fourth embodiment will be described.

[0070] 10 and 11, in the genetic information processing system 10 according to the fourth embodiment, a stutter ratio, which is the ratio of the amount of stutter amplicons, is estimated, and the distribution of microsatellites in the gene before PCR is calculated using the estimated stutter ratio. In this way, it is possible to appropriately calculate the distribution of microsatellites in the gene before PCR, taking into account the presence of stutters that occur in PCR.

[0071] <Fifth embodiment> A genetic information processing system 10 according to the fifth embodiment will be described with reference to Fig. 12. The fifth embodiment differs from the first to fourth embodiments described above only in some of the parameters included in the second ratio, and other parts may be the same as the first to fourth embodiments. Therefore, in the following, explanations of parts that overlap with parts already described will be omitted as appropriate.

[0072] (Occurrence rate of multiple types of stutter) First, the second ratio handled by the genetic information processing system 10 according to the fifth embodiment will be described with reference to Fig. 12. Fig. 12 is a conceptual diagram showing an example in which both the ratio at which a negative stutter occurs and the ratio at which a positive stutter occurs are taken into consideration.

[0073] As shown in FIG. 12, the genetic information processing system 10 according to the fifth embodiment takes into consideration both the rate b of occurrence of negative stutters with a small number of repeat units and the rate c of occurrence of positive stutters with a large number of repeat units.

[0074] In the example of FIG. 12, if PCR is performed for 10 cycles, the amount of amplicon for "5 repeats" is a 10 +a 8 bc+1260a 6 b 2 c 2 +4200a 4 b 3 c 3 +3150a 2 b 4 c4 +252b 5 c 5 The amount of amplicon in the "four repeats (i.e., -1 stutter)" is 10a 9 b+360a 7 b 2 c+2520a 5 b 3 c 2 +4200a 3 b 4 c 3 +1260ab 5 c 4 The amount of amplicon in the "triple repeat (i.e., -2 stutter)" is 45a. 8 b 2 +840a 6 b 3 c+3150a 4 b 4 c 2 +2520a 2 b 5 c 3 +210b 6 c 4 It becomes.

[0075] Although examples of -1 stutter and -2 stutter are given here, other stutter ratios can also be calculated in a similar manner.

[0076] (Technical effect) Next, the technical effects obtained by the genetic information processing system 10 according to the fifth embodiment will be described.

[0077] 12, the genetic information processing system 10 according to the fifth embodiment uses both the rate at which negative stuttering occurs and the rate at which positive stuttering with many repeat units occurs. In this way, it is possible to appropriately calculate the distribution of microsatellites in genes before PCR, taking into account the presence of both negative stuttering and positive stuttering that occurs in PCR.

[0078] Sixth embodiment A genetic information processing system 10 according to the sixth embodiment will be described with reference to Fig. 13 to Fig. 16. The sixth embodiment differs from the first to fifth embodiments in only some of the configurations and operations, and other parts may be the same as the first to fifth embodiments. Therefore, in the following, explanations of parts that overlap with parts already described will be omitted as appropriate.

[0079] (Functional configuration) First, the functional configuration of the genetic information processing system 10 according to the sixth embodiment will be described with reference to Fig. 13. Fig. 13 is a block diagram showing the functional configuration of the genetic information processing system according to the sixth embodiment. In Fig. 13, the same components as those shown in Fig. 2 are denoted by the same reference numerals.

[0080] 13, the genetic information processing system 10 according to the sixth embodiment includes a first acquisition unit 110, a second acquisition unit 120, and a calculation unit 130 as processing blocks for realizing the functions of the system. In particular, the calculation unit 130 according to the sixth embodiment includes an amplification matrix calculation unit 133.

[0081] The amplification matrix calculation unit 133 is configured to be capable of calculating an amplification matrix that is a matrix that models amplification by PCR. The amplification matrix calculation unit 133 calculates an amplification matrix that includes a first ratio, a second ratio, and the number of PCR cycles as components. The calculation unit 130 according to the sixth embodiment is configured to be capable of calculating the distribution of microsatellites in genes before PCR using the amplification matrix estimated by the amplification matrix calculation unit 133.

[0082] (Amplification matrix) Next, the amplification matrix calculated by the above-mentioned amplification matrix calculation section 133 will be specifically described with reference to Fig. 14. Fig. 14 is a determinant showing an example of an amplification matrix that models amplification by PCR.

[0083] As shown in FIG. 14, the amplification matrix is ​​a matrix including the PCR amplification rate a (i.e., the first rate), the negative stutter occurrence rate b and the positive stutter occurrence rate c (i.e., the second rate), and the number of PCR cycles n as components, as explained in FIG. 7 and FIG. 12. By using such an amplification matrix, the distribution information of the microsatellite after n cycles of PCR can be expressed as the distribution information of the microsatellite before PCR multiplied by the amplification matrix. Therefore, by using the amplification matrix, the distribution of the microsatellite before PCR can be easily calculated from the distribution information of the microsatellite after PCR. Note that when the rate at which -2 stutters occur in one PCR process is taken into consideration, the value is entered in the column to the right of b. Similarly, when the rate at which +2 stutters occur in one PCR process is taken into consideration, the value is entered in the column to the left of c.

[0084] (Operation flow) Next, the flow of operations of the genetic information processing system 10 according to the sixth embodiment will be described with reference to Fig. 15. Fig. 15 is a flowchart showing the flow of operations of the genetic information processing system according to the sixth embodiment. In Fig. 15, the same processes as those shown in Fig. 4 are denoted by the same reference numerals.

[0085] As shown in FIG. 15, when the genetic information processing system 10 according to the sixth embodiment operates, first, the first acquisition unit 110 acquires distribution information of microsatellites in genes after PCR (step S101).

[0086] Next, the second acquiring section 120 acquires the first ratio (step S102), acquires the second ratio (step S103), and acquires the number of PCR cycles (step S104).

[0087] Next, the amplification matrix calculation unit 133 calculates an amplification matrix using the first ratio, the second ratio, and the number of PCR cycles (step S601). Then, the calculation unit 130 calculates the distribution of microsatellites in the gene before PCR using the amplification matrix calculated by the amplification matrix calculation unit 133 (step S602).

[0088] (Technical effect) Next, the technical effects obtained by the genetic information processing system 10 according to the sixth embodiment will be described.

[0089] 11, in the genetic information processing system 10 according to the sixth embodiment, an amplification matrix that models amplification by PCR is calculated, and the distribution of microsatellites in the gene before PCR is calculated using the calculated amplification matrix. In this way, by using an amplification matrix whose components are the first ratio, the second ratio, and the number of PCR cycles, it is possible to appropriately calculate the distribution of microsatellites in the gene before PCR.

[0090] Seventh embodiment A genetic information processing system 10 according to the seventh embodiment will be described with reference to Fig. 16 and Fig. 17. The seventh embodiment differs from the first to sixth embodiments in some configurations and operations, and other parts may be the same as the first to sixth embodiments. Therefore, in the following, explanations of parts that overlap with parts already explained will be omitted as appropriate.

[0091] (Functional configuration) First, the functional configuration of the genetic information processing system 10 according to the seventh embodiment will be described with reference to Fig. 16. Fig. 16 is a block diagram showing the functional configuration of the genetic information processing system according to the seventh embodiment. In Fig. 16, the same components as those shown in Fig. 2 are denoted by the same reference numerals.

[0092] 16, the genetic information processing system 10 according to the seventh embodiment includes, as processing blocks for realizing the functions thereof, a first acquisition unit 110, a second acquisition unit 120, and a calculation unit 130. In particular, the second acquisition unit 120 according to the seventh embodiment includes a parameter estimation unit 121.

[0093] The parameter estimation unit 121 is configured to be able to estimate at least one of the first ratio, the second ratio, and the number of PCR cycles from the distribution information of microsatellites in the gene after PCR. That is, the second acquisition unit 120 according to the seventh embodiment estimates and acquires at least one of the first ratio, the second ratio, and the number of PCR cycles in the parameter estimation unit 121. Note that, among the first ratio, the second ratio, and the number of PCR cycles, those other than those estimated by the parameter estimation unit 121 may be acquired by a method other than estimation (for example, input from a user, etc.).

[0094] (Operation flow) Next, the flow of operations of the genetic information processing system 10 according to the seventh embodiment will be described with reference to Fig. 17. Fig. 17 is a flowchart showing the flow of operations of the genetic information processing system according to the seventh embodiment. In Fig. 17, the same processes as those shown in Fig. 4 are denoted by the same reference numerals.

[0095] As shown in FIG. 17, when the genetic information processing system 10 according to the seventh embodiment operates, first, the first acquisition unit 110 acquires distribution information of microsatellites in genes after PCR (step S101).

[0096] Next, the parameter estimation unit 121 estimates at least one of the first ratio, the second ratio, and the number of PCR cycles from the distribution information of the microsatellite in the gene after CR (step S701). Then, the second acquisition unit 120 acquires the first ratio (step S102), acquires the second ratio (step S103), and acquires the number of PCR cycles (step S104). The second acquisition unit 120 acquires estimated values ​​for the parameters estimated by the parameter estimation unit 121.

[0097] Next, the calculation unit 130 calculates the distribution of microsatellites in the gene before PCR based on the distribution information of microsatellites in the gene after PCR acquired by the first acquisition unit 110 and the first ratio, the second ratio, and the number of PCR cycles acquired by the second acquisition unit 120 (step S105).

[0098] (Technical effect) Next, the technical effects obtained by the genetic information processing system 10 according to the seventh embodiment will be described.

[0099] 16 and 17, in the genetic information processing system 10 according to the seventh embodiment, at least one of the first ratio, the second ratio, and the number of PCR cycles is estimated from the distribution information of microsatellites in genes after PCR. In this way, it is possible to appropriately calculate the distribution of microsatellites in genes before PCR using the estimated parameters without directly acquiring the first ratio, the second ratio, and the number of PCR cycles.

[0100] Eighth embodiment A genetic information processing system 10 according to the eighth embodiment will be described with reference to Fig. 18 to Fig. 20. The eighth embodiment describes a specific method for estimating parameters in the seventh embodiment described above, and the system configuration and overall operation flow may be the same as those of the seventh embodiment. Therefore, in the following, descriptions of parts that overlap with those already described will be omitted as appropriate.

[0101] (Estimated using the hill-climbing method) First, a parameter estimation method using the hill-climbing method will be specifically described with reference to Fig. 18. Fig. 18 is a graph showing the estimated amount and actual amount of genetic information calculated in the genetic information processing system according to the eighth embodiment.

[0102] The parameter estimation unit 121 in the genetic information processing system 10 according to the eighth embodiment is configured to be able to estimate at least one of the first ratio, the second ratio, and the number of PCR cycles by using a hill-climbing method.

[0103] Assume that experimental results have been obtained by amplifying "five repeats" by PCR. In this case, in the right-hand side of the determinant shown in Figure 14, the part of "five repeats" before PCR has a certain value (e.g., 20), and the rest is zero.

[0104] Next, by appropriately determining the PCR amplification rate a (i.e., the first rate), the rate b of negative stuttering and the rate c of positive stuttering (i.e., the second rate), and the number of PCR cycles n, the values ​​of each component of the amplification matrix are also determined. Then, by using this amplification matrix and the above-mentioned values ​​before PCR, the values ​​after PCR (amplicon amount) can be estimated.

[0105] In the diagram shown in Figure 18, the estimated amount calculated as described above is shown by a solid line, and the actual amount is shown by a dashed line. Note that in Figure 18, both the estimated amount and the actual amount are normalized to 1.0. Therefore, it does not matter what the value of the "5 repeats" part before PCR is.

[0106] Here, in particular, the reason why there is an error between the estimated amount (solid line) and the actual amount (dashed line) in Figure 18 is because the PCR amplification rate a, the stutter occurrence rates b and c, and the PCR cycle number n, which are determined arbitrarily, deviate from the actual values. Therefore, by changing the arbitrarily determined values ​​of a, b, c, and n so that this error becomes smaller, the true values ​​of a, b, c, and n can be estimated.

[0107] For example, if a=1.800, increase it by 0.001 to a=1.801. Then, estimate in the same way using the changed a, and if the error is smaller, use the changed value (i.e., a=1.801), and if the error is larger, leave it as it is (i.e., a=1.800). After that, change one of the values ​​of a, b, c, and n again and perform the same calculation. By repeating such processing, it is possible to estimate the true values ​​of a, b, c, and n. Note that, although an example in which the values ​​of a, b, c, and n are changed one by one has been given here, the same processing may be repeated while changing all the values ​​of a, b, c, and n.

[0108] The initial values ​​of a, b, c, and n may be determined randomly, or may be selected from a predetermined range (for example, a realistically expected value). For example, a, which is the amplification rate of PCR, may be selected from the range of 1.0 to 2.0. The number of PCR cycles n may be selected as a value from 1 to 30. Note that while the number of PCR cycles n is actually an integer, it may be a real number that is not an integer, since it is a value indicating the number of effective PCRs.

[0109] (Estimation by data fitting) Next, a method for estimating parameters using data fitting will be specifically described with reference to Fig. 19 and Fig. 20. Fig. 19 is a graph showing the relationship between the number of repetitions and the -1 stutter ratio. Fig. 20 is a graph showing a method for estimating the rate at which stuttering occurs by data fitting.

[0110] The parameter estimation unit 121 in the gene information processing system 10 according to the eighth embodiment may be configured to estimate the rate at which stuttering occurs by data fitting in addition to or instead of the hill climbing method described above. In the following, an example of calculating the rate b at which minus stuttering occurs from the -1 stutter ratio will be described.

[0111] As shown in FIG. 19, it is known that the -1 stutter ratio hardly increases when the number of repetitions is relatively small, and increases when the number of repetitions is relatively large. If this relationship is expressed as an Excel function using a constant b0 and the number of repetitions x, it becomes, for example, ((x-3)>0?(b0*(x-3)):0). In this case, if the number of repetitions is 3 or less, b=0 (i.e., the -1 stutter ratio does not increase), and as the number of repetitions increases, b also increases (for example, for "10 repetitions," it becomes b0*7).

[0112] As a result of the above, the -1 stutter ratio can be expressed as an Excel function as {nC1*((x-3)>0?(b0*(x-3)):0)} / {a}. When this relationship is applied to a graph, a straight line is obtained as shown in Figure 20. In this case, "3" is the minimum number that generates a -1 stutter. If this minimum number is bn, the following relationship is obtained: b0*((x-bn)>0?(b0*(x-bn)):0)}. As a result, the rate b at which negative stutter occurs can be expressed by two parameters, b0 and bn. The values ​​of b0 and bn can be easily obtained from the experimental results shown in Figures 19 and 20. In other words, the rate b at which negative stutter occurs can be easily estimated from the experimental results.

[0113] The above example shows how to estimate the rate b of negative stuttering, but the rate c of positive stuttering can also be estimated using a similar method. The relational expression for c, expressed using a constant c0 and a minimum number cn, is, for example, c0*((x-cn)>0?(c0*(x-cn)):0).

[0114] (Technical effect) Next, technical effects obtained by the genetic information processing system 10 according to the eighth embodiment will be described.

[0115] 18 to 20, in the genetic information processing system 10 according to the eighth embodiment, at least one of the first ratio, the second ratio, and the number of PCR cycles is estimated using a hill climbing method or data fitting. In this way, it is possible to estimate the first ratio, the second ratio, and the number of PCR cycles with high accuracy and appropriately calculate the distribution of microsatellites in the genes before PCR.

[0116] <Additional Notes> The above-described embodiment may be further described as follows, but is not limited to the following.

[0117] (Appendix 1) The genetic information processing system described in Appendix 1 is a genetic information processing system characterized by comprising a first acquisition means for acquiring distribution information of microsatellites in a gene after PCR, a second acquisition means for acquiring a first ratio indicating an amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating a ratio of stutters occurring from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR, and a calculation means for calculating the distribution of the microsatellites in the gene before the PCR based on the distribution information of the microsatellites in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR.

[0118] (Appendix 2) The genetic information processing system described in Appendix 2 is the genetic information processing system described in Appendix 1, characterized in that the calculation means estimates the amount of a stutter amplicon having one less or one more repeat unit using the first ratio, the second ratio, and the number of PCR cycles.

[0119] (Appendix 3) The genetic information processing system described in Appendix 3 is the genetic information processing system described in Appendix 1 or 2, characterized in that the calculation means estimates the amount of a stutter amplicon having two fewer or two more repeat units using the first ratio, the second ratio, and the number of PCR cycles.

[0120] (Appendix 4) The genetic information processing system described in Appendix 4 is the genetic information processing system described in any one of Appendixes 1 to 3, characterized in that the calculation means estimates a stutter ratio, which is the ratio of the amount of the stutter amplicon to the amount of the microsatellite amplicon amplified by the PCR, using the first ratio, the second ratio, and the number of PCR cycles.

[0121] (Appendix 5) The genetic information processing system described in Appendix 5 is a genetic information processing system described in any one of Appendixes 1 to 4, characterized in that the second ratio includes both the ratio of negative stutters with few repeat units and the ratio of positive stutters with many repeat units.

[0122] (Appendix 6) The genetic information processing system described in Appendix 6 is the genetic information processing system described in any one of Appendixes 1 to 5, characterized in that the calculation means calculates the distribution of the microsatellites in the gene before the PCR using an amplification matrix that is a matrix that models the amplification by PCR and has the first ratio, the second ratio, and the number of PCR cycles as components.

[0123] (Appendix 7) The genetic information processing system described in Appendix 7 is the genetic information processing system described in any one of Appendixes 1 to 6, characterized in that the second acquisition means estimates and acquires at least one of the first ratio, the second ratio, and the number of cycles of the PCR from distribution information of the microsatellite in the gene after the PCR.

[0124] (Appendix 8) The genetic information processing system described in Appendix 8 is the genetic information processing system described in Appendix 7, characterized in that the second acquisition means estimates at least one of the first ratio, the second ratio, and the PCR cycle number by hill climbing or data fitting.

[0125] (Appendix 9) The genetic information processing method described in Appendix 9 is a genetic information processing method characterized by obtaining distribution information of microsatellites in a gene after PCR, obtaining a first ratio indicating an amplification rate of the microsatellites per cycle of PCR, a second ratio indicating a ratio of stutters occurring from the microsatellites per cycle of PCR, and the number of cycles of PCR, and calculating the distribution of the microsatellites in the gene before PCR based on the distribution information of the microsatellites in the gene after PCR, the first ratio, the second ratio, and the number of cycles of PCR.

[0126] (Appendix 10) The computer program described in Appendix 10 is characterized by operating a computer to obtain distribution information of microsatellites in a gene after PCR, obtain a first ratio indicating an amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating a ratio of stutters occurring from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR, and calculate the distribution of the microsatellites in the gene before the PCR based on the distribution information of the microsatellites in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR.

[0127] (Appendix 11) The recording medium described in Appendix 11 is a recording medium having the computer program described in Appendix 10 recorded thereon.

[0128] This disclosure is not limited to the above-mentioned embodiment. This disclosure can be modified as appropriate within the scope of the claims and the gist or idea of ​​the invention that can be read from the entire specification, and the genetic information processing system, genetic information processing method, computer program, and recording medium that involve such modifications are also included in the technical idea of ​​this disclosure.

[0129] To the extent permitted by law, this application claims priority based on Japanese Patent Application No. 2021-041423, filed on March 15, 2021, the disclosure of which is incorporated herein in its entirety. In addition, to the extent permitted by law, all publications and papers described in this specification are incorporated herein by reference. [Explanation of symbols]

[0130] 10 Genetic information processing system 110 First acquisition part 120 Second acquisition part 121 Parameter Estimation Unit 130 Calculation section 131 Amplicon quantity estimation section 132 Stutter ratio estimator 133 Amplification matrix calculation unit a PCR amplification rate b. Percentage of negative stutter occurrence c) Proportion of positive stutters n PCR cycle number

Claims

1. A first acquisition means for acquiring distribution information of microsatellites in a gene after PCR; A second acquisition means for acquiring a first ratio indicating an amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating a ratio of stutters generated from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR; a calculation means for calculating a distribution of the microsatellite in the gene before the PCR based on distribution information of the microsatellite in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR; Equipped with The calculation means calculates the distribution of the microsatellites in the gene before the PCR using an amplification matrix that is a matrix that models the amplification by the PCR and that includes the first ratio, the second ratio, and the number of cycles of the PCR as components. A genetic information processing system comprising:

2. The genetic information processing system according to claim 1, characterized in that the calculation means estimates the amount of a stutter amplicon having one less or one more repeat unit using the first ratio, the second ratio, and the number of PCR cycles.

3. The genetic information processing system according to claim 1 or 2, characterized in that the calculation means estimates the amount of an amplicon of a stutter having two fewer or two more repeat units using the first ratio, the second ratio, and the number of PCR cycles.

4. The genetic information processing system according to any one of claims 1 to 3, characterized in that the calculation means estimates a stutter ratio, which is the ratio of the amount of the stutter amplicon to the amount of the microsatellite amplicon amplified by the PCR, using the first ratio, the second ratio, and the number of PCR cycles.

5. A genetic information processing system described in any one of claims 1 to 4, characterized in that the second ratio includes both the ratio of occurrence of negative stutters with a small number of repeat units and the ratio of positive stutters with a large number of repeat units.

6. The genetic information processing system according to any one of claims 1 to 5, characterized in that the second acquisition means estimates and acquires at least one of the first ratio, the second ratio, and the number of cycles of the PCR from distribution information of the microsatellite in the gene after the PCR.

7. 7. The genetic information processing system according to claim 6, wherein the second acquisition means estimates at least one of the first ratio, the second ratio, and the number of PCR cycles by a hill climbing method or data fitting.

8. At least one computer, Obtaining distribution information of microsatellites in genes after PCR; A first ratio indicating an amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating a rate of stutters occurring from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR are obtained; Calculating a distribution of the microsatellite in the gene before the PCR based on distribution information of the microsatellite in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR; When calculating the distribution of the microsatellites, an amplification matrix that models the amplification by PCR and includes the first ratio, the second ratio, and the number of cycles of the PCR as components is used to calculate the distribution of the microsatellites in the gene before the PCR. A method for processing genetic information.

9. Obtaining distribution information of microsatellites in genes after PCR; A first ratio indicating an amplification rate of the microsatellite for each cycle of the PCR, a second ratio indicating a rate of stutters occurring from the microsatellite for each cycle of the PCR, and the number of cycles of the PCR are obtained; Calculating a distribution of the microsatellite in the gene before the PCR based on distribution information of the microsatellite in the gene after the PCR, the first ratio, the second ratio, and the number of cycles of the PCR; When calculating the distribution of the microsatellites, an amplification matrix that models the amplification by PCR and includes the first ratio, the second ratio, and the number of cycles of the PCR as components is used to calculate the distribution of the microsatellites in the gene before the PCR. A computer program for causing a computer to operate in such a manner.

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