Methods, apparatus, electronic equipment and storage media for determining the Tm value of melting curve

Abstract

This invention provides a method, apparatus, electronic device, and storage medium for determining the Tm value of a melting curve, relating to the field of PCR detection technology. In determining the Tm value, this invention first obtains the initial melting curve for each well of a PCR plate; then, based on the wavelet modulus maxima peak-finding principle of continuous wavelet transform, it searches for peaks in the initial melting curve to obtain the initial Tm value; finally, it uses a fixed threshold method to denoise and filter the initial Tm value to obtain the target Tm value. This method does not require any smoothing filtering, avoiding the sensitivity to noise and background information problems of conventional melting curve Tm value calculation methods, and is easy to understand and implement.

Description

Technical Field

[0001] This invention relates to the field of PCR detection technology, and in particular to a method, apparatus, electronic device, and storage medium for determining the Tm value of a melting curve. Background Technology

[0002] After PCR (polymerase chain reaction) amplification, to examine the specificity of the amplified products or perform SNP (Single Nucleotide Polymorphism) genotyping, the negative derivative of fluorescence intensity, i.e., the melting curve, is often obtained by gradually increasing the temperature to degrade the amplified products. During the heating process, when the temperature reaches half of the melting point, a large amount of fluorescent dye is released, and the fluorescence intensity decreases rapidly, thus forming a peak point on the melting curve. The temperature corresponding to this peak point is the Tm value (i.e., the melting temperature), and the number and location of Tm values ​​are key factors to consider.

[0003] Currently, commonly used methods for determining the Tm value of melting curves include direct search and higher-order derivative methods. However, the direct search method is very sensitive to noise and background information; although the higher-order derivative method can improve the resolution of the melting point peak and remove the influence of first- and second-order background noise, complex smoothing filtering is required before solving for the higher-order derivative, otherwise serious noise will be introduced after the higher-order derivative is calculated. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, electronic device, and storage medium for determining the Tm value of a melting curve, so as to avoid the problem of conventional melting curve Tm value solving methods being sensitive to noise and background information.

[0005] In a first aspect, embodiments of the present invention provide a method for determining the Tm value of a melting curve, comprising:

[0006] Obtain the initial melting curve for each reaction well of the PCR plate;

[0007] Based on the principle of finding the peak of the wavelet modulus maxima in continuous wavelet transform, the initial melting curve is searched to obtain the initial Tm value;

[0008] The initial Tm value is denoised and filtered using a fixed threshold method to obtain the target Tm value.

[0009] Furthermore, the above-mentioned acquisition of the initial melting curve for each reaction well of the PCR plate includes:

[0010] Collect fluorescence intensity data for each reaction well of the PCR plate in the amplicon melting experiment after quantitative real-time PCR;

[0011] The fluorescence intensity data were processed using the direct difference method to obtain the initial melting curves of the corresponding reaction wells.

[0012] Furthermore, based on the principle of finding the peak of the wavelet modulus maxima in continuous wavelet transform, the initial melting curve is peaked to obtain the initial Tm value, including:

[0013] Obtain the predetermined wavelet mother function and scaling parameters, including multiple scaling values;

[0014] Continuous wavelet transforms were performed on the initial melting curve at various scale values ​​to obtain the wavelet coefficient matrix;

[0015] Based on the wavelet coefficient matrix, determine the initial Tm value and the corresponding modulus maxima.

[0016] Furthermore, the determination of the initial Tm value and the corresponding modulus maxima based on the wavelet coefficient matrix includes:

[0017] Based on the wavelet coefficient matrix, determine the location of the modulus maxima at each scale value;

[0018] When the positions of the modulus maxima of a preset number of consecutive scale values ​​starting from the minimum value in the scale parameter are within the same preset range, that position is determined as the peak position;

[0019] Find the largest modulus maxima corresponding to the peak position;

[0020] The position corresponding to the largest modulus maxima found is determined as the initial Tm value, and the largest modulus maxima found is determined as the modulus maxima corresponding to the initial Tm value.

[0021] Furthermore, the aforementioned initial Tm value corresponds to a modulus maxima; the initial Tm value is denoised and filtered using a fixed threshold method to obtain the target Tm value, including:

[0022] Determine the wavelet coefficients of the noise band corresponding to the initial melting curve;

[0023] The noise band threshold is determined based on the wavelet coefficients of the noise band.

[0024] The initial Tm value where the modulus maxima are greater than the noise band threshold is determined as the target Tm value.

[0025] Furthermore, the above determination of the wavelet coefficients of the noise band corresponding to the initial melting curve includes:

[0026] Determine the maximum scale value for noise testing based on the sampling frequency of the initial melting curve;

[0027] Determine whether the wavelet coefficients corresponding to the maximum scale value satisfy the normality requirement; where the wavelet coefficients corresponding to the maximum scale value refer to the wavelet coefficients obtained by performing continuous wavelet transform on the initial melting curve at the maximum scale value;

[0028] If so, the wavelet coefficients corresponding to the maximum scale value are determined as the noise band wavelet coefficients corresponding to the initial melting curve;

[0029] If not, the maximum scale value is decreased by a preset scale interval until the preset scale lower limit is reached. When there are wavelet coefficients that meet the normality requirement, the wavelet coefficients that meet the normality requirement are determined as the noise band wavelet coefficients corresponding to the initial melting curve. When there are no wavelet coefficients that meet the normality requirement, the wavelet coefficients corresponding to the preset scale lower limit are determined as the noise band wavelet coefficients corresponding to the initial melting curve.

[0030] Furthermore, the determination of the noise band threshold based on the wavelet coefficients of the noise band includes:

[0031] The root mean square of the wavelet coefficients in the noise band is calculated based on the absolute deviation of the median of the wavelet coefficients in the noise band.

[0032] Substituting the root mean square into the following formula, we can calculate the noise band threshold xlim:

[0033]

[0034] Where σ represents the root mean square and N represents the length of the temperature sequence corresponding to the initial melting curve.

[0035] Secondly, embodiments of the present invention also provide a device for determining the Tm value of a melting curve, comprising:

[0036] The acquisition module is used to acquire the initial melting curve of each reaction well of the PCR plate;

[0037] The peak finding module is used to find the peak of the initial melting curve based on the peak finding principle of wavelet modulus maxima in continuous wavelet transform, so as to obtain the initial Tm value.

[0038] The filtering module is used to filter the initial Tm value for noise reduction based on a fixed threshold method to obtain the target Tm value.

[0039] Thirdly, embodiments of the present invention also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the melting curve Tm value determination method of the first aspect.

[0040] Fourthly, embodiments of the present invention also provide a storage medium storing a computer program, wherein the computer program is executed by a processor to perform the melting curve Tm value determination method of the first aspect.

[0041] The method, apparatus, electronic device, and storage medium for determining the melting curve Tm value provided in this invention first acquire the initial melting curve of each reaction well in a PCR plate; then, based on the wavelet modulus maxima peak-finding principle of continuous wavelet transform, the initial melting curve is peak-findinged to obtain the initial Tm value; finally, the initial Tm value is denoised and filtered using a fixed threshold method to obtain the target Tm value. This method does not require any smoothing filtering operations, avoiding the sensitivity to noise and background information problems of conventional melting curve Tm value solving methods, and is easy to understand and implement. Attached Figure Description

[0042] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0043] Figure 1 A flowchart illustrating a method for determining the Tm value of a melting curve according to an embodiment of the present invention;

[0044] Figure 2 The initial melting curve of a certain reaction orifice provided in this embodiment of the invention is calculated using the direct difference method;

[0045] Figure 3 for Figure 2 The wavelet coefficients corresponding to the first 5 scales;

[0046] Figure 4 For the reason Figure 2 The maximum modulus maxima corresponding to each temperature were obtained;

[0047] Figure 5 This is a schematic diagram of a device for determining the Tm value of a melting curve according to an embodiment of the present invention;

[0048] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Finding the Tm value is not difficult when the amplitude characteristics of each peak point of the melting curve are obvious. However, when the melting curve has a lot of noise and large amplitude fluctuations, existing methods for determining the Tm value of the melting curve, such as direct search methods and higher-order derivative methods, are easily affected by noise and background information, resulting in inaccurate Tm values. Based on this, this invention provides a method, apparatus, electronic device, and storage medium for determining the Tm value of a melting curve. By using CWT (Continuous Wavelet Transform) to obtain the modulus maxima of each transform level to determine the initial Tm value, and then using a fixed threshold method to determine the final Tm value (target Tm value), this method avoids the sensitivity of conventional melting curve Tm value solving methods to noise and background information, does not require any smoothing filtering operations, and is easy to understand and implement.

[0051] To facilitate understanding of this embodiment, a method for determining the Tm value of a melting curve disclosed in this embodiment of the invention will first be described in detail.

[0052] This invention provides a method for determining the Tm value of a melting curve, which can be executed by an electronic device with data processing capabilities. See also... Figure 1 The diagram shows a method for determining the Tm value of a melting curve. This method mainly includes the following steps S102 to S106:

[0053] Step S102: Obtain the initial melting curve of each reaction well of the PCR plate.

[0054] A PCR plate, also known as a PCR reaction plate, uses a melting curve whose ordinate represents the first negative derivative of the fluorescence signal with respect to temperature. In some possible embodiments, fluorescence intensity data can be collected from each well of the PCR plate during the amplicon melting experiment after quantitative real-time PCR. The fluorescence intensity data can then be processed using the direct difference method to obtain the initial melting curve for each well. It should be noted that this invention does not limit the method of obtaining the initial melting curve; in other embodiments, other methods can also be used to process the fluorescence intensity data to obtain the initial melting curve.

[0055] Step S104: Based on the principle of finding the peak of the wavelet modulus maxima in continuous wavelet transform, the initial melting curve is peaked to obtain the initial Tm value.

[0056] In some possible embodiments, a predetermined wavelet mother function and scaling parameters can be obtained first, including multiple scaling values. Then, a continuous wavelet transform is performed on the initial melting curve at each scaling value to obtain a wavelet coefficient matrix, where each row of the wavelet coefficient matrix corresponds to a scaling value. Finally, based on the wavelet coefficient matrix, the initial Tm value and the corresponding modulus maxima are determined. Wavelet coefficients are parameters in wavelet decomposition that allow the original signal to be reconstructed. Scaling 2 indicates that the wavelet coefficients are obtained by scaling the original wavelet basis (i.e., the wavelet mother function) by a factor of 2 using CWT.

[0057] The wavelet mother function can be selected based on similarity. For example, the wavelet mother function can be the Mexh wavelet or the Gauss wavelet. The scale parameter can be selected based on the wavelet mother function and resolution requirements. For example, if the wavelet mother function is the Mexh wavelet, the scale parameter can include multiple consecutive positive integers starting from 1, such as 1, 2, 3, 4, etc.

[0058] In one possible implementation, the specific process of determining the initial Tm value and its corresponding modulus maxima based on the wavelet coefficient matrix can be as follows: Determine the position of the modulus maxima at each scale value based on the wavelet coefficient matrix; when the modulus maxima positions of a preset number of consecutive scale values ​​starting from the minimum value in the scale parameter are within a preset range of the same position, this position is determined as the peak position; find the largest modulus maxima corresponding to this peak position; determine the position corresponding to the found largest modulus maxima as the initial Tm value, and determine the found largest modulus maxima as the modulus maxima corresponding to the initial Tm value. The preset number and preset range can be set according to actual needs and are not limited here. For example, if the preset number is 3, the preset range is three sampling points (including itself and its left and right sides), and the scale parameter is multiple consecutive positive integers starting from 1, if the modulus maxima positions of only two consecutive scale values ​​starting from 1 are located near the same position A (i.e., three sampling points including itself and its left and right sides), then position A is determined not to be a peak position and is discarded.

[0059] Step S106: The initial Tm value is denoised and filtered based on the fixed threshold method to obtain the target Tm value.

[0060] In some possible embodiments, the noise band wavelet coefficients corresponding to the initial melting curve can be determined first; then the noise band threshold can be determined based on the noise band wavelet coefficients; finally, the initial Tm value with a modulus maxima greater than the noise band threshold can be determined as the target Tm value.

[0061] Optionally, the wavelet coefficients of the noise band can be determined as follows: Based on the sampling frequency of the initial melting curve, determine the maximum scale value for noise testing; determine whether the wavelet coefficients corresponding to the maximum scale value satisfy the normality requirement; wherein, the wavelet coefficients corresponding to the maximum scale value refer to the wavelet coefficients obtained by performing continuous wavelet transform on the initial melting curve at the maximum scale value; if yes, the wavelet coefficients corresponding to the maximum scale value are determined as the wavelet coefficients of the noise band corresponding to the initial melting curve; if no, decrease the maximum scale value at preset scale intervals until a preset lower scale limit is reached; when there are wavelet coefficients that satisfy the normality requirement, determine the wavelet coefficients that satisfy the normality requirement as the wavelet coefficients of the noise band corresponding to the initial melting curve; when there are no wavelet coefficients that satisfy the normality requirement, determine the wavelet coefficients corresponding to the preset lower scale limit as the wavelet coefficients of the noise band corresponding to the initial melting curve.

[0062] According to the Nyquist sampling theorem, the highest analysis frequency must be less than half the sampling frequency. Since the noise frequency is higher than the signal frequency, the scale value corresponding to the highest analysis frequency (i.e., the maximum scale value for noise testing) is initially used as the CWT level where the noise resides, and a normality test is performed on the white noise. The preset scale interval can be set according to actual needs, for example, a preset scale interval of 0.1. The preset lower limit of the scale is determined by the selected wavelet mother function; for example, for the Mexh wavelet, its center frequency f... c =0.25. According to the Nyquist sampling theorem, the highest analysis frequency must be less than 1 / 2 of the sampling frequency, so its scale value a≥0.5. Therefore, the preset scale lower limit for the Mexh wavelet is 0.5.

[0063] Optionally, the noise band threshold can be determined by the following process: first, calculate the root mean square of the noise band wavelet coefficients based on the median absolute deviation of the wavelet coefficients; then, substitute the root mean square into the following formula to calculate the noise band threshold xlim:

[0064]

[0065] Where σ represents the root mean square, and N represents the length of the temperature sequence corresponding to the initial melting curve (the number of fluorescence intensity data).

[0066] The method for determining the melting curve Tm value provided in this invention first obtains the initial melting curve for each reaction well of the PCR plate; then, based on the wavelet modulus maxima peak-finding principle of continuous wavelet transform, the initial melting curve is peak-findinged to obtain the initial Tm value; finally, the initial Tm value is denoised and filtered using a fixed threshold method to obtain the target Tm value. This method does not require any smoothing filtering operations, avoiding the sensitivity to noise and background information problems of conventional melting curve Tm value calculation methods, and is easy to understand and implement.

[0067] For ease of understanding, the embodiments of the present invention also provide specific examples of the above-described method for determining the Tm value of the melting curve, as follows:

[0068] a) The initial melting curves of each well in the PCR reaction plate were obtained using the direct difference method.

[0069] Step a1: Collect fluorescence intensity data in the amplicon melting experiment after quantitative real-time PCR;

[0070] Simply record the raw fluorescence intensity data as needed; no processing is required.

[0071] Step a2: Process the fluorescence intensity data using the direct difference method to obtain the initial melting curve.

[0072] Since the melting curve is the negative derivative of the fluorescence intensity, the derivative curve of the fluorescence intensity data is negative after being obtained using the direct difference method.

[0073] b) Select the wavelet mother function and scale range (scale parameter), perform CWT peak finding on the initial melting curve, and obtain the initial Tm value.

[0074] Step b1: Select the wavelet mother function and scale range based on similarity and resolution requirements;

[0075] The selection of wavelet mother functions generally requires that their shape be similar to the peak shape and preferably have symmetry, so as to effectively suppress background information. Therefore, the Mexh wavelet can be selected as the wavelet mother function for analysis, as shown in equation (1):

[0076]

[0077] According to the wavelet modulus maxima peak finding principle, when the scale parameter increases to the peak half-width at half-maximum (HWHM), the wavelet coefficient reaches its maximum value at that peak position. Further increasing the scale parameter will decrease this coefficient. To identify peak positions at different HWHMs in the melting curve, multiple scales need to be selected for peak finding. The minimum scale determines the identification capability of the minimum HWHM peak. The relationship between wavelet analysis scale and frequency is as follows:

[0078]

[0079] Where a represents the scale value, Δ represents the sampling period, and f c f represents the center frequency of the wavelet mother function. For the Mexh wavelet, f c =0.25, f a Let a represent the analysis frequency corresponding to 'a'. According to the Nyquist sampling theorem, the highest analysis frequency must be less than half of the sampling frequency, so a ≥ 0.5. We initially choose a = 1.

[0080] Step b2: Calculate the CWT of the initial melting curve at each scale;

[0081] The CWT transformation method is shown in equation (3):

[0082]

[0083] Where f(t) is the signal, ψ(t) is the wavelet mother function represented by equation (1), a is the scaling parameter, and b is the translation parameter. As the value of a changes, CWT returns a two-dimensional wavelet coefficient matrix, with one a value per row.

[0084] Step b3: Compare the locations of the modulus maxima at each scale to determine the initial Tm value and the corresponding modulus maxima.

[0085] Find the maximum points of wavelet coefficients at each scale, i.e., the modulus maxima. If there are 3 consecutive modulus maxima at a certain location starting from a smaller scale (from scale 1 to 3, stop when the requirement is met), then the location is initially determined to be the peak position. On this basis, continue to expand the scale to find the largest modulus maxima. The scale value corresponding to this is the half-peak width, and the corresponding position is the initial Tm value. Record the modulus maxima corresponding to the initial Tm value.

[0086] c) Remove clutter using a fixed threshold method to obtain the final Tm value (target Tm value).

[0087] Step c1: Determine the CWT level where the noise is located based on the sampling frequency;

[0088] Since the noise frequency is higher than the signal frequency, the highest analysis frequency, i.e., the minimum value of 1 among the above scale parameters, is initially used as the CWT level where the noise is located. Then, a normality test for white noise is performed. If the wavelet coefficients of this level meet the normality requirement, then this level (scale 1) is determined to be the noise band, and the wavelet coefficients corresponding to this level are the wavelet coefficients of the noise band. If this level does not meet the normality test requirement, then scale 1 is decreased by 0.1 until it reaches 0.5. The process stops when the wavelet coefficients corresponding to a certain scale meet the normality requirement. If the wavelet coefficients corresponding to scale 0.5 still do not meet the normality requirement, then the wavelet coefficients corresponding to scale 0.5 are determined to be the wavelet coefficients of the noise band.

[0089] Step c2: Calculate the noise band threshold based on the fixed threshold method;

[0090] Let the noise band threshold be xlim, the temperature sequence length be N, and the noise band wavelet coefficient be X. The root mean square σ is calculated from the median absolute deviation (MAD).

[0091] MAD = median(|X - median(X)|)

[0092] σ = 1.4826 × MAD

[0093] The noise band threshold is:

[0094]

[0095] Step c3: Determine the final Tm value based on the noise band threshold.

[0096] Compare the magnitude maxima corresponding to each initial Tm with xlim, retain all magnitude maxima greater than xlim, and their corresponding Tm values ​​are the final Tm values.

[0097] To verify the effectiveness of the above method for determining the Tm value of the melting curve, we performed PCR amplification-melting experiments on multiple reagents using the Borui Real-Time PCR detection system and analyzed the fluorescence intensity data collected during the melting phase. Here, we use one set of data analysis results as an example, employing continuous sampling mode with a temperature sampling interval of approximately 0.3℃. Figure 2 The initial melting curve of a certain reaction well obtained by the direct difference method shows that it has a relatively obvious melting peak at around 67℃, and a weak shoulder peak near 72℃ to the right of the peak. Figure 3 These are the wavelet coefficients for the first five scales corresponding to the initial melting curve. Figure 4 For each temperature, the maximum modulus value is given. It can be seen that there are three initial Tm values. Based on this, the maximum scale value (the minimum scale parameter) is determined by the noise test. Figure 3 The wavelet coefficients corresponding to mesoscale 1 (scale 1 meets the normal noise test requirements) are calculated to have a noise band threshold of 98. Since the modulus maximum value corresponding to temperature 60.33℃ is 55.4, it is discarded. The final Tm values ​​of this reaction hole are 67.23℃ and 72.33℃.

[0098] Corresponding to the above-described method for determining the Tm value of the melting curve, this embodiment of the invention also provides a device for determining the Tm value of the melting curve. See also... Figure 5 The diagram shows a structural schematic of a device for determining the Tm value of a melting curve. The device includes:

[0099] The acquisition module 52 is used to acquire the initial melting curve of each reaction well of the PCR plate;

[0100] Peak finding module 54 is used to find the peak of the initial melting curve according to the peak finding principle of wavelet modulus maxima of continuous wavelet transform, and obtain the initial Tm value;

[0101] The filtering module 56 is used to filter the initial Tm value for noise reduction based on the fixed threshold method to obtain the target Tm value.

[0102] The melting curve Tm value determination device provided in this embodiment of the invention first obtains the initial melting curve of each reaction well of the PCR plate when determining the melting curve Tm value; then, based on the wavelet modulus maxima peak finding principle of continuous wavelet transform, the initial melting curve is peaked to obtain the initial Tm value; finally, the initial Tm value is denoised and filtered based on the fixed threshold method to obtain the target Tm value. This eliminates the need for any smoothing filtering operations, avoiding the sensitivity to noise and background information problems of conventional melting curve Tm value calculation methods, and is easy to understand and implement.

[0103] Optionally, the acquisition module 52 is specifically used to: collect fluorescence intensity data of each reaction well of the PCR plate in the amplicon melting experiment after quantitative real-time PCR; and process the fluorescence intensity data using the direct difference method to obtain the initial melting curve of the corresponding reaction well.

[0104] Optionally, the peak finding module 54 is specifically used to: obtain a predetermined wavelet mother function and scale parameters, the scale parameters including multiple scale values; perform continuous wavelet transform on the initial melting curve at each scale value to obtain the wavelet coefficient matrix; and determine the initial Tm value and the corresponding modulus maxima based on the wavelet coefficient matrix.

[0105] Optionally, the peak finding module 54 is further configured to: determine the position of the modulus maxima at each scale value based on the wavelet coefficient matrix; when the modulus maxima positions of a preset number of consecutive scale values ​​starting from the minimum value in the scale parameters are within a preset range of the same position, determine the position as the peak position; find the largest modulus maxima corresponding to the peak position; determine the position corresponding to the largest modulus maxima found as the initial Tm value, and determine the largest modulus maxima found as the modulus maxima corresponding to the initial Tm value.

[0106] Optionally, the initial Tm value mentioned above corresponds to a modulus maxima. The filtering module 56 is specifically used to: determine the noise band wavelet coefficients corresponding to the initial melting curve; determine the noise band threshold based on the noise band wavelet coefficients; and determine the initial Tm value with a modulus maxima greater than the noise band threshold as the target Tm value.

[0107] Optionally, the screening module 56 is further configured to: determine the maximum scale value for noise testing based on the sampling frequency of the initial melting curve; determine whether the wavelet coefficients corresponding to the maximum scale value meet the normality requirement; wherein, the wavelet coefficients corresponding to the maximum scale value refer to the wavelet coefficients obtained by performing continuous wavelet transform on the initial melting curve at the maximum scale value; if yes, determine the wavelet coefficients corresponding to the maximum scale value as the noise band wavelet coefficients corresponding to the initial melting curve; if no, decrease the maximum scale value by a preset scale interval until a preset lower scale limit is reached; when there are wavelet coefficients that meet the normality requirement, determine the wavelet coefficients that meet the normality requirement as the noise band wavelet coefficients corresponding to the initial melting curve; when there are no wavelet coefficients that meet the normality requirement, determine the wavelet coefficients corresponding to the preset lower scale limit as the noise band wavelet coefficients corresponding to the initial melting curve.

[0108] Optionally, the filtering module 56 is further configured to: calculate the root mean square of the wavelet coefficients of the noise band based on the median absolute deviation of the wavelet coefficients of the noise band; and substitute the root mean square into the following formula to calculate the noise band threshold xlim:

[0109]

[0110] Where σ represents the root mean square and N represents the length of the temperature sequence corresponding to the initial melting curve.

[0111] The melting curve Tm value determination device provided in this embodiment has the same implementation principle and technical effect as the aforementioned melting curve Tm value determination method embodiment. For the sake of brevity, any parts not mentioned in the melting curve Tm value determination device embodiment can be referred to the corresponding content in the aforementioned melting curve Tm value determination method embodiment.

[0112] See Figure 6 This invention also provides an electronic device 100, including: a processor 60, a memory 61, a bus 62 and a communication interface 63, wherein the processor 60, the communication interface 63 and the memory 61 are connected through the bus 62; the processor 60 is used to execute executable modules, such as computer programs, stored in the memory 61.

[0113] The memory 61 may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 63 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0114] Bus 62 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0115] The memory 61 is used to store the program. After receiving the execution instruction, the processor 60 executes the program. The melting curve Tm value determination method executed by the melting curve Tm value determination device in the process definition disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 60, or implemented by the processor 60.

[0116] Processor 60 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above-described method for determining the melting curve Tm value can be completed by the integrated logic circuitry in the hardware of processor 60 or by software instructions. Processor 60 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 61. The processor 60 reads the information in memory 61 and, in conjunction with its hardware, completes the steps of the above-described method for determining the melting curve Tm value.

[0117] This invention also provides a storage medium storing a computer program, which, when executed by a processor, performs the melting curve Tm value determination method described in the preceding method embodiments. The storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), RAM, magnetic disk, or optical disk.

[0118] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not as limitations; therefore, other examples of exemplary embodiments may have different values.

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0120] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0121] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0122] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining a melting curve Tm value, characterized in that, The method comprises the following steps: acquiring an initial melting curve of each reaction well of a PCR plate; performing peak searching on the initial melting curve according to a wavelet modulus maximum value peak searching principle of continuous wavelet transform to obtain an initial Tm value; performing denoising screening on the initial Tm value based on a fixed threshold method to obtain a target Tm value; the initial Tm value corresponds to a modulus maximum value; the denoising screening on the initial Tm value based on the fixed threshold method to obtain the target Tm value comprises the following steps: determining a noise band wavelet coefficient corresponding to the initial melting curve; determining a noise band threshold value according to the noise band wavelet coefficient; determining an initial Tm value with a modulus maximum value greater than the noise band threshold value as a target Tm value; the determination of the noise band wavelet coefficient corresponding to the initial melting curve comprises the following steps: determining a maximum scale value of noise detection according to a sampling frequency of the initial melting curve; determining whether a wavelet coefficient corresponding to the maximum scale value meets a normal requirement; wherein the wavelet coefficient corresponding to the maximum scale value refers to a wavelet coefficient obtained by performing continuous wavelet transform on the initial melting curve at the maximum scale value; if yes, determining the wavelet coefficient corresponding to the maximum scale value as the noise band wavelet coefficient corresponding to the initial melting curve; if no, decreasing the maximum scale value by a preset scale interval until a preset lower limit of scale is reached; when there is a wavelet coefficient meeting the normal requirement, determining the wavelet coefficient meeting the normal requirement as the noise band wavelet coefficient corresponding to the initial melting curve; when there is no wavelet coefficient meeting the normal requirement, determining a wavelet coefficient corresponding to the preset lower limit of scale as the noise band wavelet coefficient corresponding to the initial melting curve.

2. The melting curve Tm value determination method according to claim 1, characterized in that, The method comprises the following steps: acquiring an initial melting curve of each reaction well of a PCR plate; acquiring fluorescence intensity data of each reaction well of the PCR plate in an amplicon melting experiment after quantitative PCR; 3. The melting curve Tm value determination method according to claim 1, characterized in that, processing the fluorescence intensity data by using a direct difference method to obtain an initial melting curve of the corresponding reaction well. The method comprises the following steps: acquiring a pre-determined wavelet mother function and a scale parameter, wherein the scale parameter comprises a plurality of scale values; performing continuous wavelet transform on the initial melting curve at each scale value to obtain a wavelet coefficient matrix; 4. The melting curve Tm value determination method according to claim 3, characterized in that, determining an initial Tm value and a corresponding modulus maximum value according to the wavelet coefficient matrix. The method comprises the following steps: determining a modulus maximum value position at each scale value according to the wavelet coefficient matrix; when modulus maximum value positions of a continuous preset number of scale values starting from a minimum value in the scale parameter are located within a preset range at a same position, determining the position as a peak position; finding a maximum modulus maximum value corresponding to the peak position; 5. The melting curve Tm value determination method according to claim 1, characterized by, determining a position corresponding to the found maximum modulus maximum value as an initial Tm value, and determining the found maximum modulus maximum value as a modulus maximum value corresponding to the initial Tm value. The method comprises the following steps: According to the median absolute deviation of the noise band wavelet coefficients, a root mean square of the noise band wavelet coefficients is calculated; The root mean square is brought into the following formula to calculate a noise band threshold value xlim: ， Wherein, σ represents the root mean square, and N represents the length of the temperature sequence corresponding to the initial melting curve.

6. A melting curve Tm value determination apparatus, characterized by, Comprise: An acquisition module is configured to acquire an initial melting curve of each reaction well of a PCR plate; A peak searching module is configured to search for a peak of the initial melting curve according to a wavelet modulus maximum value peak searching principle of continuous wavelet transform to obtain an initial Tm value; A screening module is configured to denoise and screen the initial Tm value based on a fixed threshold method to obtain a target Tm value; The initial Tm value corresponds to a modulus maximum value; and the screening module is specifically configured to: determine noise band wavelet coefficients corresponding to the initial melting curve; determine a noise band threshold value according to the noise band wavelet coefficients; and determine an initial Tm value with a modulus maximum value greater than the noise band threshold value as a target Tm value; The screening module is further configured to: determine a maximum scale value of noise detection according to a sampling frequency of the initial melting curve; determine whether a wavelet coefficient corresponding to the maximum scale value meets a normal requirement; wherein the wavelet coefficient corresponding to the maximum scale value refers to a wavelet coefficient obtained by performing continuous wavelet transform on the initial melting curve at the maximum scale value; if yes, the wavelet coefficient corresponding to the maximum scale value is determined as the noise band wavelet coefficient corresponding to the initial melting curve; if no, the maximum scale value is decreased by a preset scale interval until a preset lower limit of scale is reached; when there is a wavelet coefficient meeting the normal requirement, the wavelet coefficient meeting the normal requirement is determined as the noise band wavelet coefficient corresponding to the initial melting curve; and when there is no wavelet coefficient meeting the normal requirement, a wavelet coefficient corresponding to the preset lower limit of scale is determined as the noise band wavelet coefficient corresponding to the initial melting curve.

7. An electronic device comprising a memory, a processor, the memory having stored therein a computer program executable on the processor, characterized in that, The processor executes the computer program to implement the method of any one of claims 1-5.

8. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to implement the method of any one of claims 1-5.

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