Melting curve analysis method and system for HPV (human papillomavirus) typing detection
Through single-color fluorescent labeling and melting curve analysis methods, the problems of complex operation and low accuracy of existing HPV detection methods have been solved, and high-precision, low-cost HPV typing detection has been achieved.
Patent Information
- Application Number
- CN202411457643.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-18
- Publication Date
- 2025-01-24
AI Technical Summary
The existing HPV detection methods require multi-color fluorescent markers and multiple fluorescent channels, which are complex in operation and high hardware requirements of the equipment, resulting in reduced detection accuracy and increased cost.
Using monochrome fluorescence to mark the primers of different viruses DNA sequences, the melting curve of samples, positive controls, and negative controls is used to build noise pollution weights and fusion weights for data to correct and fuse to obtain a fusion sample fusion curve for determining HPV virus to determine HPV virus virus type.
It improves the accuracy of sample data, improves detection accuracy, reduces detection costs and hardware requirements, and simplifies the primer preparation process.
Smart Images
Figure CN119360980A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of gene detection, and in particular to a melting curve analysis method and system for HPV typing detection. Background Art
[0002] When testing for HPV (human papillomavirus) in clinical practice, an HPV kit is usually used to extract sample DNA from cervical cells, and then the qPCR (real-time fluorescence quantitative detection) method is used to detect whether the sample contains HPV DNA, thereby completing the HPV test on the human body.
[0003] In the process of HPV detection, multiplex PCR technology is usually used to detect multiple types of HPV at the same time, improve the detection throughput, and ensure the rapid completion of HPV detection. Existing multiplex PCR technology mostly uses different fluorescent substances to label different primers, monitors the fluorescence emitted by different primers through different fluorescent channels, and then monitors the characteristic amplification of different DNA sequences, and then completes the detection of different DNA sequences in one PCR reaction solution. However, this method requires the use of multi-color fluorescent labels for different primers, and requires the detection instrument to have multiple fluorescent channels, which makes the operation more complicated and requires high equipment hardware. Using monochrome fluorescent labels for primers of different viral DNA sequences makes it difficult to determine which fluorescent signals come from which specific HPV type, resulting in a decrease in sensitivity and specificity, thereby affecting the accuracy of the detection.
[0004] Therefore, there is an urgent need for a melting curve analysis method and system for HPV typing detection, which can improve the accuracy of sample data, thereby improving detection accuracy and reducing detection costs and hardware requirements. Summary of the invention
[0005] In order to solve the above technical problems, the present invention provides a melting curve analysis method and system for HPV typing detection, which can improve the accuracy of sample data, thereby improving the detection accuracy and reducing the detection cost and hardware requirements.
[0006] The present invention provides a melting curve analysis method for HPV typing detection, which specifically comprises the following steps: S1. Obtain multiple HPV test samples, corresponding negative control samples and multiple types of positive control samples; S2, mixing the HPV test sample, the negative control sample, and the positive control sample with the PCR reaction solution respectively to obtain a melting curve of each test sample, a melting curve of the negative control sample, and a melting curve of each positive control sample; S3, analyzing the melting curve of each positive control sample with the melting curve of the negative control sample to determine the melting curve of each decontaminated positive sample control; analyzing the melting curve of each test sample with the melting curve of the negative control sample to determine the melting curve of each decontaminated test sample; S4, determining the noise contamination weight of the fluorescence at each data point in the melting curve of the negative control sample according to the difference between the inverse of the first-order derivative function of the melting curve of the negative control sample and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each identical data point; S5, respectively analyzing the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample to be tested and the value 0, and the fluorescence at each same data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve, to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample to be tested melting curve; S6, performing weighted calculation according to the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence, to obtain the deviation-corrected fluorescence at each data point position; S7, according to the noise pollution weight and the deviation correction fluorescence, combined with the average value of the fluorescence at each data point position in all the decontaminated sample melting curves, determine the fusion value of the fluorescence at each data point position, and obtain the fusion sample melting curve; S8. Determine the HPV virus type of the sample to be tested based on the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample.
[0007] Furthermore, in S1, multiple HPV test samples all correspond to the same HPV typing.
[0008] Further, in S3, each positive control sample melting curve is analyzed with the negative control sample melting curve to determine each decontaminated positive sample control melting curve; each test sample melting curve is analyzed with the negative control sample melting curve to determine each decontaminated test sample melting curve, including: S31, determining each decontaminated positive sample control melting curve according to the difference in fluorescence between all identical data point positions of each positive control sample melting curve and the negative control sample melting curve; S32. Obtaining the melting curve of each decontaminated sample to be tested according to the difference in fluorescence between all identical data points of the melting curve of each sample to be tested and the melting curve of the negative control sample.
[0009] Further, in S4, according to the difference between the inverse of the first-order derivative function of the negative control sample melting curve and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each same data point position, the noise contamination weight of the fluorescence at each data point position in the negative control sample melting curve is determined, including: S41, recording the inverse of the first-order derivative function of the negative control sample melting curve as the negative control melting derivative curve, and recording the inverse of the first-order derivative function of the decontaminated positive sample control melting curve as the decontaminated positive control melting derivative curve; S42, calculating the absolute value of the ratio of the fluorescence at the nth data point position of the melting derivative curve of each decontamination positive control to the fluorescence at the nth data point position of the melting derivative curve of the negative control; S43. Calculate the average of the absolute values according to all the absolute values corresponding to the fluorescence at the nth data point, and use the average of the absolute values as the noise contamination weight of the fluorescence at the nth data point in the negative control melting derivative curve.
[0010] Further, in S5, the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample to be tested and the value 0 and the fluorescence at each same data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve is analyzed respectively to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample to be tested melting curve, including: S51, recording the inverse of the first-order derivative function of the decontaminated sample melting curve as the decontaminated sample melting derivative curve; S52, analyzing the difference between the fluorescence at each data point in the melting derivative curve of the decontaminated sample to be tested and the value 0, and recording it as a first difference; S53, analyzing the difference between the fluorescence at each data point in the melting derivative curve of the decontaminated sample to be tested and the fluorescence at the same data point in the melting derivative curve of each decontaminated positive control, and averaging all the differences corresponding to the fluorescence at the data point, which is recorded as the second difference; S54. Calculate the fusion weight of the fluorescence at each data point in the decontaminated sample melting derivative curve according to the first difference and the second difference of the fluorescence at each data point in the decontaminated sample melting derivative curve.
[0011] Further, in S6, weighted calculation is performed based on the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence to obtain the deviation-corrected fluorescence at each data point position, including: S61, taking the fusion weight of the fluorescence at each data point position in the melting derivative curve of the decontaminated sample as a weight, and performing weighted calculation on the fluorescence at each data point position in the melting curve of the decontaminated sample to be tested; S62, summing up the weighted calculation results of the fluorescence at the same data point position in the melting curves of each decontaminated sample to be tested, to obtain the deviation-corrected fluorescence at each data point position.
[0012] Further, in S7, the fluorescence is corrected according to the noise pollution weight and the deviation, and the average value of the fluorescence at each data point position in the melting curve of all decontaminated samples to be tested is combined to determine the fusion value of the fluorescence at each data point position, and obtain the fusion sample melting curve, wherein the calculation formula of the fusion value of the element at each position is as follows: ; in, is the fusion value of the fluorescence at the nth data point of the melting curve of the fused sample, is the noise contamination weight of the fluorescence at the nth data point, It is the average fluorescence value corresponding to the nth data point position of the melting curve of all decontaminated samples to be tested. is the bias-corrected fluorescence at the nth data point.
[0013] Further, in S8, the HPV virus type of the sample to be tested is determined according to the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample, including: S81, calculating the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample; S82. Select the HPV typing of the positive control sample corresponding to the maximum similarity value as the HPV virus type of the sample to be tested.
[0014] Furthermore, the abscissa of the melting curve is the measurement temperature, and the ordinate is the inverse of the derivative of the fluorescence corresponding to the sample at the measurement temperature with respect to the measurement temperature.
[0015] The present invention also provides a melting curve analysis system for HPV typing detection, which is used to implement any of the above-mentioned melting curve analysis methods for HPV typing detection, and the system comprises: A melting curve acquisition module is used to obtain multiple HPV test samples, corresponding negative control samples and multiple types of positive control samples; the HPV test samples, negative control samples and positive control samples are mixed with PCR reaction solution to obtain melting curves of each test sample, melting curve of negative control samples and melting curves of each positive control sample; The decontamination melting curve acquisition module is connected to the melting curve acquisition module, and is used to analyze the melting curve of each positive control sample with the melting curve of the negative control sample to determine the melting curve of each decontamination positive sample control; and analyze the melting curve of each sample to be tested with the melting curve of the negative control sample to determine the melting curve of each decontamination sample to be tested; A noise pollution weight acquisition module is connected to the decontaminated melting curve acquisition module, and is used to determine the noise pollution weight of the fluorescence at each data point position in the negative control sample melting curve according to the difference between the inverse of the first-order derivative function of the negative control sample melting curve and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each same data point position; A fusion weight acquisition module is connected to the decontaminated melting curve acquisition module, and is used to respectively analyze the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample melting curve and the value 0, and the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve, to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample melting curve; The fluorescence correction module is connected to the fusion weight acquisition module and is used to perform weighted calculation based on the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence to obtain the deviation-corrected fluorescence at each data point position; A fusion sample melting curve acquisition module is connected to the noise pollution weight acquisition module and the fluorescence correction module, and is used to correct the fluorescence according to the noise pollution weight and the deviation, and determine the fusion value of the fluorescence at each data point position in combination with the average value of the fluorescence at each data point position in all decontaminated sample melting curves to obtain the fusion sample melting curve; The typing output module is connected to the fusion sample melting curve acquisition module and the decontamination melting curve acquisition module, and is used to determine the HPV virus type of the sample to be tested based on the similarity between the inverse of the first-order derivative function of the fusion sample melting curve and the inverse of the first-order derivative function of each decontamination positive control sample melting curve.
[0016] The embodiments of the present invention have the following technical effects: The present invention uses primers of different viral DNA sequences to label with monochromatic fluorescence, and obtains melting curves of samples, positive controls and negative controls by measurement; constructs noise pollution weights by the difference between the melting curves of the negative control and the positive control, and characterizes the data credibility of the melting curves of samples at different temperature positions; selects the sample melting curve showing strong specific amplification characteristics within the temperature range with low data credibility by comparing the melting curve of the positive control with the sample melting curve, and performs data correction to obtain the deviation-corrected fluorescence; further combines the deviation-corrected fluorescence, the noise pollution weights and the average fluorescence to complete the data fusion of multiple sample melting curves and obtain the fused sample melting curve, which makes full use of the information of repeated PCR experiments, improves the accuracy of sample data, and further improves the detection accuracy; In addition, compared with the multi-color fluorescence detection method, the present invention does not need to use different fluorescent dyes to label different primers, and only requires the detection equipment to have one fluorescence channel, which simplifies the primer preparation process and reduces the detection cost and hardware requirements. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0018] Figure 1 It is a flow chart of a melting curve analysis method for HPV typing detection provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the inverse number of the first-order derivative function of each decontaminated positive sample control melting curve provided by an embodiment of the present invention; Figure 3 It is a flow chart of calculating the fusion weight of the fluorescence at each data point position in the melting curve of the decontaminated sample to be tested provided by an embodiment of the present invention; Figure 4 It is a structural schematic diagram of a melting curve analysis system for HPV typing detection provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0019] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.
[0020] The present invention proposes a melting curve analysis method for HPV typing detection. Figure 1 is a flow chart of a melting curve analysis method for HPV typing detection provided by an embodiment of the present invention, see Figure 1 , specifically including the following steps: S1. Obtain multiple HPV test samples, corresponding negative control samples, and multiple types of positive control samples.
[0021] For example, a female cervical exfoliated cell sample is collected by an HPV kit, the exfoliated cell sample is melted with physiological saline, and a cervical exfoliated cell solution is obtained after multiple centrifugation to obtain a precipitate, and then the cells are lysed by a 100°C dry bath or water bath for 10 minutes, and finally a purified DNA sample is extracted from the solution after multiple centrifugation to obtain a clear liquid, as an HPV test sample. The specific sample preparation process is a common technology in the field of genetic testing and will not be described in detail.
[0022] As for the method of obtaining negative control samples and positive control samples, preferably, in this embodiment, the process of obtaining the negative control sample is: based on the process of obtaining the HPV test sample, physiological saline is used to replace the exfoliated cell sample at the beginning, and the subsequent experimental steps are the same as the steps of obtaining the HPV test sample to obtain the negative control sample; In this embodiment, the process of obtaining the positive control sample is as follows: based on the process of obtaining the HPV test sample, a mixture of different types of HPV viral plasmid DNA is used to replace the exfoliated cell sample at the beginning, and the subsequent experimental steps are the same as the steps of obtaining the HPV test sample to prepare the positive control sample; the setting of negative control and positive control is a commonly used technique in the field of genetic testing and will not be repeated here.
[0023] Furthermore, corresponding primers are designed for various HPV virus plasmids, and the primers are labeled with the same fluorescent marker dye to prepare PCR reaction solution. The design of primers is designed by technicians for the DNA sequences of different viruses. It is a common technology in the field of gene detection and will not be described in detail.
[0024] Among them, multiple HPV test samples all correspond to the same HPV typing. The same individual sample can be retested multiple times to obtain multiple HPV test samples, or different individual samples with the same signal marked as belonging to the same HPV typing can be collected to obtain multiple HPV test samples.
[0025] S2. The HPV test sample, negative control sample, and positive control sample are mixed with the PCR reaction solution respectively to obtain the melting curve of each test sample, the melting curve of the negative control sample, and the melting curve of each positive control sample.
[0026] Specifically, the HPV test samples, negative control samples, positive control samples and PCR reaction solution are mixed respectively, and the samples are measured on a machine to obtain the melting curves of the test samples, the negative control samples and the positive control samples.
[0027] Exemplarily, the present embodiment sets the measurement temperature range to 40°C to 90°C, and the sampling interval to 0.1°C. Therefore, in the obtained melting curve data, one melting curve corresponds to one reaction liquid, and the data format is a vector with a length of N=500. The value of each data point in the vector represents the fluorescence of the mixed liquid at the corresponding collection temperature, where N is the number of data point samples; exemplarily, the sampling interval is 0.1°C, the sampling range is 0-50°C, and the sampling is 500 times, then N=500.
[0028] For example, this embodiment takes M=8 types of HPV viruses as an example (M represents the number of types of HPV typing), and detects 8 types of HPV viruses, including: HPV types 16, 45, 51, 52, 56, 59, 73, and 68. Therefore, in the melting curve data obtained in this embodiment, there are a total of M positive control sample melting curves, corresponding to the M types of HPV viruses in sequence. At the same time, in the melting curve data, there is 1 negative control melting curve.
[0029] Furthermore, since qPCR (quantitative polymerase chain reaction) determination usually involves multiple measurements of the sample to be tested to ensure that the data of the sample to be tested is accurate, in the melting curve data obtained in this embodiment, this embodiment preferably sets a total of K=10 melting curves of the sample to be tested (K represents the number of melting curves of the sample to be tested), which are recorded as the melting curves of the sample to be tested.
[0030] Furthermore, in the obtained melting curve, the melting curve of the sample to be tested contains the DNA of the sample to be tested, so the characteristic information of different HPV viruses can be extracted from the melting curve of the sample to be tested to determine whether the virus exists. At the same time, since the melting curve of the sample to be tested contains the fluorescence intensity information of different DNA sequences, the melting curve of the sample to be tested obtained in this embodiment is equivalent to the superposition of multiple melting curves for a single virus. Therefore, this embodiment uses signal decomposition means to decompose the characteristic information of different DNA sequences from the melting curve of the sample to be tested.
[0031] Since the acquisition of melting curves is easily affected by changing environmental parameters, noisy data will often appear in the melting curves. When performing signal decomposition on the melting curves of the samples to be tested, data fusion of multiple melting curves of the samples to be tested should be used to improve the data quality of the melting curves of the samples to be tested and improve the accuracy of signal decomposition.
[0032] S3. Analyze the melting curve of each positive control sample with the melting curve of the negative control sample to determine the melting curve of each decontaminated positive sample control; analyze the melting curve of each test sample with the melting curve of the negative control sample to determine the melting curve of each decontaminated test sample.
[0033] Specifically, the negative control sample melting curve is a data curve used to observe whether there is exogenous contamination in the PCR process. Ideally, no fluorescence will be detected in the negative control sample, and the fluorescence value of the negative control sample melting curve is always 0. When the PCR process is contaminated by the PCR reaction solution, the environmental parameters change, or the primers form primer dimers, the fluorescence value in the negative control sample melting curve may not be 0, indicating that the fluorescence signal detected at the corresponding temperature may be noise data caused by interference.
[0034] Therefore, when processing the melting curve, the noise pollution of the data in the melting curve of the sample to be tested or the melting curve of the positive control sample is eliminated through the melting curve of the negative control sample. At the same time, the larger the fluorescence value of the melting curve of the negative control sample at the corresponding temperature, the less reliable the melting curve data at the corresponding temperature; in the melting curve of the positive control sample, the greater the change in the slope of the fluorescence at the corresponding temperature position, the more important the melting curve data at the corresponding temperature position is, and if the fluorescence at the corresponding temperature position in the melting curve of the sample to be tested decreases, it is more likely to be a normal phenomenon, rather than an abnormal phenomenon caused by contamination.
[0035] Therefore, this embodiment performs data fusion processing on the melting curve of the sample to be tested according to the melting curve of the positive control sample and the melting curve of the negative control sample, removes interference such as contamination from the melting curve of the sample to be tested, and improves the data quality of the melting curve of the sample to be tested.
[0036] S31. Determine each decontaminated positive sample control melting curve according to the difference in fluorescence between all identical data point positions of each positive control sample melting curve and the negative control sample melting curve.
[0037] S32. Obtaining the melting curve of each decontaminated sample to be tested according to the difference in fluorescence between all identical data points of the melting curve of each sample to be tested and the melting curve of the negative control sample.
[0038] Specifically, each positive control sample melting curve, each test sample melting curve and the negative control sample melting curve are subtracted to obtain each decontaminated positive sample control melting curve and each decontaminated test sample melting curve; thereby eliminating some interfering data in the melting curve.
[0039] S4. Determine the noise contamination weight of the fluorescence at each data point in the melting curve of the negative control sample according to the difference between the inverse of the first-order derivative function of the melting curve of the negative control sample and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each identical data point.
[0040] S41. The inverse of the first-order derivative function of the negative control sample melting curve is recorded as the negative control melting derivative curve, and the inverse of the first-order derivative function of the decontaminated positive sample control melting curve is recorded as the decontaminated positive control melting derivative curve.
[0041] Specifically, Figure 2 is a schematic diagram of the inverse of the first-order derivative function of each decontaminated positive sample control melting curve provided by an embodiment of the present invention, see Figure 2 , respectively taking the negative control sample melting curve, the decontaminated positive sample control melting curve, and the decontaminated test sample melting curve as inputs, adopting the first-order derivative calculation method to obtain the derivative of each melting curve, and then taking the inverse of the derivative to be obtained, and outputting the negative control melting derivative curve, the decontaminated positive control melting derivative curve, and the decontaminated test sample melting derivative curve, that is, converting the negative derivative of each melting curve to obtain the corresponding melting derivative curve, there is a melting peak in the derivative curve, and the temperature corresponding to the melting peak is the Tm value. The first-order derivative calculation algorithm is a commonly used data processing technology in PCR experiments, and the specific derivation process is a prior art, which will not be described in detail in this embodiment.
[0042] The horizontal axis of the melting curve is the measurement temperature, and the vertical axis is the inverse of the derivative of the fluorescence (RFU) of the sample at the measurement temperature (T). Figure 2 In the figure, multiple decontamination positive control melting derivative curves are put into one figure, and the curve number corresponds to the HPV virus type. In the melting derivative curve, the higher the value of the inverse number of the derivative of the fluorescence (RFU) to the measured temperature (T), the faster the fluorescence of the sample decreases, and the corresponding temperature is more likely to be the temperature position for specific amplification of the viral DNA sequence.
[0043] S42. Calculate the absolute value of the ratio of the fluorescence at the nth data point position of the melting derivative curve of each decontamination positive control to the fluorescence at the nth data point position of the melting derivative curve of the negative control.
[0044] S43. Calculate the average of the absolute values according to all the absolute values corresponding to the fluorescence at the nth data point, and use the average of the absolute values as the noise contamination weight at the nth data point in the negative control melting derivative curve.
[0045] Exemplarily, in this embodiment, the absolute value of the ratio of the fluorescence of the nth data point of the mth decontaminated positive control melting derivative curve to the fluorescence of the nth data point of the negative control melting derivative curve is analyzed. For the convenience of description and understanding, the result of taking the absolute value of the ratio is recorded as the fluorescence contamination intensity at the nth data point of the mth decontaminated positive control melting derivative curve in this embodiment. To avoid the situation where the denominator is zero when calculating the ratio, 1 is added to the denominator when calculating the ratio in this embodiment to prevent the denominator from being 0; accordingly, the fluorescence contamination intensity at the nth data point of all decontaminated positive control melting derivative curves is obtained; further, the fluorescence contamination intensity at the nth data point of all decontaminated positive control melting derivative curves is averaged to obtain the noise contamination weight of the fluorescence at the nth data point in the negative control melting derivative curve.
[0046] Among them, the fluorescence value of the negative control melting derivative curve is not 0 due to contamination and the like, while the fluorescence value of the decontaminated positive control melting derivative curve is not 0 due to viral DNA sequence-specific amplification. The larger the ratio of the former to the latter, the more likely it is that the derivative of the decontaminated test sample melting derivative curve at the nth data point position is data caused by noise pollution rather than data represented by viral DNA sequence-specific amplification; at this time, the larger the absolute value of the fluorescence of the decontaminated test sample melting derivative curve at the nth data point position, the more serious the data contamination of the fluorescence at the nth data point position in the decontaminated test sample melting curve.
[0047] S5. Analyze the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of the melting curve of each decontaminated sample to be tested and the value 0, and the fluorescence at each data point position in the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample, and obtain the fusion weight of the fluorescence at each data point position in the melting curve of the decontaminated sample to be tested.
[0048] Specifically, Figure 3 is a flow chart of calculating the fusion weight of the fluorescence at each data point in the melting curve of the decontaminated sample to be tested provided by an embodiment of the present invention, see Figure 3 , the calculation process of fusion weight specifically includes: S51. Record the inverse of the first-order derivative function of the melting curve of the decontaminated sample to be tested as the melting derivative curve of the decontaminated sample to be tested.
[0049] Specifically, considering the melting derivative curve of the decontaminated sample to be tested, the fluorescence value at the nth data point should be judged as normal data when there are two situations: The first case is that the fluorescence value is 0, which means that the temperature is not within the specific amplification temperature range of the DNA sequence; The second case is that its fluorescence value is close to the fluorescence value of a decontamination positive control melting derivative curve, which means that this temperature is within the specific amplification temperature range of the DNA sequence of the HPV virus corresponding to the positive control sample.
[0050] S52, analyzing the difference between the fluorescence at each data point in the melting derivative curve of the decontaminated sample to be tested and the value 0, and recording it as the first difference.
[0051] S53. Analyze the difference between the fluorescence at each data point in the melting derivative curve of the decontaminated sample to be tested and the fluorescence at the same data point in the melting derivative curve of each decontaminated positive control, and calculate the average of all differences corresponding to the fluorescence at the data point, which is recorded as the second difference.
[0052] S54. Calculate the fusion weight of the fluorescence at each data point in the decontaminated sample melting derivative curve according to the first difference and the second difference of the fluorescence at each data point in the decontaminated sample melting derivative curve.
[0053] For example, in this embodiment, for the kth decontaminated sample melting derivative curve, the fluorescence value at the nth data point position is subtracted from 0 and the absolute value is taken, which is recorded as the first difference of the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve. At the same time, the fluorescence value at the nth data point position of the kth decontaminated sample melting derivative curve and the fluorescence value at the nth data point position of all decontaminated positive control melting derivative curves are respectively obtained by taking the average of the absolute values, which is recorded as the second difference of the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve. The smaller the first difference and the second difference, the more the fluorescence value at the nth data point position conforms to the above two normal data situations. It should be noted that in this embodiment, the difference is taken to characterize the difference between the data (i.e., the first difference and the second difference), but in actual application, it can be set according to the actual situation, and no special limitation is made here.
[0054] Then, the first difference and the second difference of the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve are added. In this embodiment, for the convenience of description and understanding, the result of adding the first difference and the second difference is recorded as the curve credibility of the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve; finally, the curve credibility of the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve is normalized and recorded as the fusion weight of the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve. The greater the fusion weight, the more credible the fluorescence at the nth data point position of the kth decontaminated sample melting derivative curve is compared with other decontaminated sample melting derivative curves. It should be noted that there are many normalization processing methods. This embodiment selects the Z-score normalization method. It can be selected according to needs in the actual process. The specific normalization process is a prior art and will not be repeated.
[0055] S6. Perform weighted calculation based on the fluorescence at each data point in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence to obtain the deviation-corrected fluorescence at each data point.
[0056] S61. Using the fusion weight of the fluorescence at each data point in the melting derivative curve of the decontaminated sample as a weight, weighted calculation is performed on the fluorescence at each data point in the melting curve of the decontaminated sample to be tested.
[0057] S62, summing up the weighted calculation results of the fluorescence at the same data point position in the melting curves of each decontaminated sample to be tested, to obtain the deviation-corrected fluorescence at each data point position.
[0058] Exemplarily, the fusion weight of the fluorescence intensity at the nth data point position of the first decontaminated sample to be tested melting curve×the fluorescence intensity at the nth data point position of the first decontaminated sample to be tested melting curve=weighted result 1; The fluorescence intensity at the nth data point of the melting curve of the second decontaminated sample to be tested × the fusion weight of the fluorescence intensity at the nth data point of the melting curve of the second decontaminated sample to be tested = weighted result 2; And so on, ... the fluorescence intensity at the nth data point position of the melting curve of the kth decontaminated sample to be tested × the fusion weight of the fluorescence intensity at the nth data point position of the melting curve of the kth decontaminated sample to be tested = weighted result k; Weighted result 1 + weighted result 2 + … + weighted result k = deviation-corrected fluorescence at the nth data point position.
[0059] S7. Correct the fluorescence according to the noise pollution weight and the deviation, combine the average value of the fluorescence at each data point in the melting curve of all decontaminated samples to be tested, determine the fusion value of the fluorescence at each data point, and obtain the fused sample melting curve.
[0060] Specifically, the calculation formula for the fusion value of the fluorescence at each data point is as follows: ; in, is the fusion value of the fluorescence at the nth data point position of the melting curve of the fused sample; is the noise pollution weight of the fluorescence at the nth data point. The larger the value, the more serious the interference of the fluorescence pollution at the nth data point of the fused sample melting curve is. The more bias-corrected fluorescence should be used as the fusion value of the fluorescence at the nth data point of the fused sample melting curve. It is the average value of the fluorescence corresponding to the nth data point position of the melting curve of all decontaminated samples to be tested, representing the average level of fluorescence of the melting curve of the uncorrected decontaminated samples to be tested; is the bias-corrected fluorescence at the nth data point.
[0061] Furthermore, according to the above method, a fusion value can be obtained for the fluorescence of all data point positions, and the fusion sample melting curve can be obtained after fitting all the fusion values, thereby completing the data fusion of multiple melting curves of samples to be tested, making full use of the data information of repeated experiments and control experiments in the PCR process, which helps to improve the accuracy of subsequent signal decomposition.
[0062] S8. Determine the HPV virus type of the sample to be tested based on the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample.
[0063] S81. Calculate the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontamination positive control sample.
[0064] The inverse of the first-order derivative function of the fusion sample melting curve is recorded as the fusion sample melting derivative curve.
[0065] S82. Select the HPV typing of the positive control sample corresponding to the maximum similarity value as the HPV virus type of the sample to be tested.
[0066] Specifically, firstly, the fusion sample melting curve is used as input, and the first-order derivative calculation algorithm is used to calculate, and the first-order derivative function of the fusion sample melting curve is obtained, and then the inverse of the derivative is taken, and the output is the fusion sample melting derivative curve; correspondingly, the inverse of the first-order derivative function of the decontaminated positive control sample melting curve is recorded as the decontaminated positive control melting derivative curve. The first-order derivative calculation algorithm is a commonly used data processing technology in PCR experiments, and the meaning of the obtained melting derivative curve is the same as above, which will not be repeated here.
[0067] The HPV virus type of the sample to be tested is determined based on the similarity between the melting derivative curve of the fusion sample and the melting derivative curve of each decontaminated positive control.
[0068] Preferably, in this embodiment, the HPV typing corresponding to the decontaminated positive control melting derivative curve having the greatest similarity to the fusion sample melting derivative curve is determined as the HPV virus type of the sample to be tested, thereby completing the determination of the HPV virus type.
[0069] It should be noted that the measurement methods for calculating the similarity between the melting derivative curve of the fusion sample and the melting derivative curves of each decontamination positive control may include cosine similarity, the inverse of the Euclidean distance, the Pearson correlation coefficient, etc. Since the data type of the melting curve is described as a vector in S2 in this embodiment, the cosine similarity is used in this embodiment to measure the similarity between the melting derivative curve of the fusion sample and the melting derivative curves of each positive sample. In the actual process, you can choose according to your needs, and this embodiment does not impose any special restrictions on this.
[0070] The present invention uses primers of different viral DNA sequences to label with monochromatic fluorescence, and obtains melting curves of samples, positive controls and negative controls by measurement; constructs noise pollution weights by the difference between the melting curves of the negative control and the positive control, and characterizes the data credibility of the melting curves of samples at different temperature positions; selects the sample melting curve showing strong specific amplification characteristics within the temperature range with low data credibility by comparing the melting curve of the positive control with the sample melting curve, and performs data correction to obtain the deviation-corrected fluorescence; further combines the deviation-corrected fluorescence, the noise pollution weights and the average fluorescence to complete the data fusion of multiple sample melting curves and obtain the fused sample melting curve, which makes full use of the information of repeated PCR experiments, improves the accuracy of sample data, and further improves the detection accuracy; In addition, the present invention uses Gaussian fitting to perform signal decomposition on the melting curve of the fusion sample to obtain multiple characteristic peaks, and then compares each characteristic peak with the melting curve of the fusion sample to construct the fitting difference ratio, and compares it with the positive control melting curve to construct the positive control fitting degree, and finally obtains the peak significance, completes the screening of characteristic peaks, eliminates virtual characteristic peaks caused by noise data, optimizes the Tm value of the traditional virus type determination method, completes HPV virus detection, reduces false positive virus signals, can more accurately identify and distinguish different types of HPV viruses, and improves the accuracy and reliability of HPV virus detection.
[0071] The embodiment of the present invention further provides a melting curve analysis system for HPV typing detection, which is used to implement the melting curve analysis method for HPV typing detection described in the above embodiment. Figure 4is a schematic diagram of a melting curve analysis system for HPV typing detection provided by an embodiment of the present invention, see Figure 4 , the system includes: A melting curve acquisition module is used to obtain multiple HPV test samples, corresponding negative control samples and multiple types of positive control samples; the HPV test samples, negative control samples and positive control samples are mixed with PCR reaction solution to obtain melting curves of each test sample, melting curve of negative control samples and melting curves of each positive control sample; The decontamination melting curve acquisition module is connected to the melting curve acquisition module, and is used to analyze the melting curve of each positive control sample with the melting curve of the negative control sample to determine the melting curve of each decontamination positive sample control; and analyze the melting curve of each sample to be tested with the melting curve of the negative control sample to determine the melting curve of each decontamination sample to be tested; A noise pollution weight acquisition module is connected to the decontaminated melting curve acquisition module, and is used to determine the noise pollution weight of the fluorescence at each data point position in the negative control sample melting curve according to the difference between the inverse of the first-order derivative function of the negative control sample melting curve and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each data point position; A fusion weight acquisition module is connected to the decontaminated melting curve acquisition module, and is used to respectively analyze the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample melting curve and the value 0, and the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve, to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample melting curve; The fluorescence correction module is connected to the fusion weight acquisition module and is used to perform weighted calculation based on the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence to obtain the deviation-corrected fluorescence at each data point position; A fusion sample melting curve acquisition module is connected to the noise pollution weight acquisition module and the fluorescence correction module, and is used to correct the fluorescence according to the noise pollution weight and the deviation, and to determine the fusion value of the fluorescence at each data point position in combination with the average value of the fluorescence at each data point position in all decontaminated sample melting curves to obtain the fusion sample melting curve; The typing output module is connected to the fusion sample melting curve acquisition module and the decontamination melting curve acquisition module, and is used to determine the HPV virus type of the sample to be tested based on the similarity between the inverse of the first-order derivative function of the fusion sample melting curve and the inverse of the first-order derivative function of each decontamination positive control sample melting curve.
[0072] The present invention detects HPV viruses by using primers that label different viral DNA sequences with single-color fluorescence. Compared with the multicolor fluorescence detection method, the present invention does not need to label different primers with different fluorescent dyes, and only requires the detection equipment to have one fluorescence channel, which simplifies the primer preparation process and reduces the detection cost and hardware requirements.
[0073] It should be noted that the terms used in the present invention are only for describing specific embodiments, rather than limiting the scope of the present application. As shown in the present specification, unless the context clearly indicates an exception, the words "one", "a", "a kind of" and / or "the" do not specifically refer to the singular, but may also include the plural. The terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method or device. In the absence of more restrictions, the elements defined by the sentence "include one..." do not exclude the presence of other identical elements in the process, method or device including the elements.
[0074] It should also be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. Unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", etc. should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.
[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.
Claims
1. A melting curve analysis method for HPV typing detection, characterized in that: The specific steps include: S1. Obtain multiple HPV test samples, corresponding negative control samples and multiple types of positive control samples; S2, mixing the HPV test sample, the negative control sample, and the positive control sample with the PCR reaction solution to obtain a melting curve of each test sample, a melting curve of the negative control sample, and a melting curve of each positive control sample; S3, analyzing the melting curve of each positive control sample with the melting curve of the negative control sample to determine the melting curve of each decontaminated positive sample control; analyzing the melting curve of each test sample with the melting curve of the negative control sample to determine the melting curve of each decontaminated test sample; S4, determining the noise contamination weight of the fluorescence at each data point in the melting curve of the negative control sample according to the difference between the inverse of the first-order derivative function of the melting curve of the negative control sample and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each identical data point; S5, respectively analyzing the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample to be tested and the value 0, and the fluorescence at each same data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve, to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample to be tested melting curve; S6, performing weighted calculation according to the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence, to obtain the deviation-corrected fluorescence at each data point position; S7, determining the fusion value of the fluorescence at each data point position according to the noise pollution weight and the deviation-corrected fluorescence, combined with the average value of the fluorescence at each data point position in all decontaminated sample melting curves, to obtain a fused sample melting curve; S8. Determine the HPV virus type of the sample to be tested based on the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample.
2. A melting curve analysis method for HPV typing detection according to claim 1, characterized in that: In S3, each positive control sample melting curve and each negative control sample melting curve are analyzed to determine each decontaminated positive sample control melting curve; The melting curve of each test sample is analyzed with the melting curve of the negative control sample to determine the melting curve of each decontaminated test sample, including: S31, determining each decontaminated positive sample control melting curve according to the difference in fluorescence between all identical data point positions of each positive control sample melting curve and the negative control sample melting curve; S32. Obtaining the melting curve of each decontaminated sample to be tested according to the difference in fluorescence between all identical data points of the melting curve of each sample to be tested and the melting curve of the negative control sample.
3. A melting curve analysis method for HPV typing detection according to claim 2, characterized in that: In S4, according to the difference between the inverse of the first-order derivative function of the negative control sample melting curve and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each same data point position, the noise contamination weight of the fluorescence at each data point position in the negative control sample melting curve is determined, including: S41, recording the inverse of the first-order derivative function of the negative control sample melting curve as the negative control melting derivative curve, and recording the inverse of the first-order derivative function of the decontaminated positive sample control melting curve as the decontaminated positive control melting derivative curve; S42, calculating the absolute value of the ratio of the fluorescence at the nth data point position of the melting derivative curve of each decontamination positive control to the fluorescence at the nth data point position of the melting derivative curve of the negative control; S43. Calculate the average of the absolute values according to all the absolute values corresponding to the fluorescence at the nth data point position, and use the average of the absolute values as the noise contamination weight of the fluorescence at the nth data point position in the negative control melting derivative curve.
4. A melting curve analysis method for HPV typing detection according to claim 3, characterized in that: In S5, the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample to be tested and the value 0 and the fluorescence at each same data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve is analyzed respectively to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample to be tested melting curve, including: S51, recording the inverse of the first-order derivative function of the decontaminated sample melting curve as the decontaminated sample melting derivative curve; S52, analyzing the difference between the fluorescence at each data point in the melting derivative curve of the decontaminated sample to be tested and the value 0, and recording it as a first difference; S53, analyzing the difference between the fluorescence at each data point in the melting derivative curve of the decontaminated sample to be tested and the fluorescence at the same data point in the melting derivative curve of each decontaminated positive control, and averaging all the differences corresponding to the fluorescence at the data point, which is recorded as the second difference; S54. Calculate the fusion weight of the fluorescence at each data point in the decontaminated sample melting derivative curve according to the first difference and the second difference of the fluorescence at each data point in the decontaminated sample melting derivative curve.
5. A melting curve analysis method for HPV typing detection according to claim 4, characterized in that: In S6, weighted calculation is performed based on the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence to obtain the deviation-corrected fluorescence at each data point position, including: S61, taking the fusion weight of the fluorescence at each data point position in the melting derivative curve of the decontaminated sample as a weight, and performing weighted calculation on the fluorescence at each data point position in the melting curve of the decontaminated sample to be tested; S62, summing up the weighted calculation results of the fluorescence at the same data point position in the melting curves of each decontaminated sample to be tested, to obtain the deviation-corrected fluorescence at each data point position.
6. A melting curve analysis method for HPV typing detection according to claim 5, characterized in that: In S7, according to the noise pollution weight and the deviation-corrected fluorescence, combined with the average value of the fluorescence at each data point position in all decontaminated sample melting curves, the fusion value of the fluorescence at each data point position is determined to obtain a fused sample melting curve, wherein the calculation formula for the fusion value of the fluorescence at each data point position is as follows: ； in, is the fusion value of the fluorescence at the nth data point of the melting curve of the fused sample, is the noise contamination weight of the fluorescence at the nth data point, It is the average fluorescence value corresponding to the nth data point position of the melting curve of all decontaminated samples to be tested. is the bias-corrected fluorescence at the nth data point.
7. A melting curve analysis method for HPV typing detection according to claim 6, characterized in that: In S8, the HPV virus type of the sample to be tested is determined according to the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of the melting curve of each decontaminated positive control sample, including: S81, calculating the similarity between the inverse of the first-order derivative function of the melting curve of the fusion sample and the inverse of the first-order derivative function of each decontamination positive control sample melting curve; S82. Select the HPV typing of the positive control sample corresponding to the maximum similarity value as the HPV virus type of the sample to be tested.
8. A melting curve analysis method for HPV typing detection according to claim 1, characterized in that: The abscissa of the melting curve is the measurement temperature, and the ordinate is the inverse number of the derivative of the fluorescence corresponding to the sample at the measurement temperature with respect to the measurement temperature.
9. A melting curve analysis system for HPV typing detection, used to implement a melting curve analysis method for HPV typing detection as described in any one of claims 1 to 8, characterized in that the system include: A melting curve acquisition module is used to obtain multiple HPV test samples, corresponding negative control samples and multiple types of positive control samples; the HPV test samples, the negative control samples and the positive control samples are mixed with PCR reaction solution to obtain melting curves of each test sample, melting curves of negative control samples and melting curves of each positive control sample; A decontamination melting curve acquisition module, connected to the melting curve acquisition module, is used to analyze the melting curve of each positive control sample with the melting curve of the negative control sample to determine the melting curve of each decontamination positive sample control; analyze the melting curve of each sample to be tested with the melting curve of the negative control sample to determine the melting curve of each decontamination sample to be tested; A noise pollution weight acquisition module is connected to the decontaminated melting curve acquisition module, and is used to determine the noise pollution weight of the fluorescence at each data point position in the negative control sample melting curve according to the difference between the inverse of the first-order derivative function of the negative control sample melting curve and the inverse of the first-order derivative function of each decontaminated positive sample control melting curve at each same data point position; A fusion weight acquisition module is connected to the decontaminated melting curve acquisition module, and is used to respectively analyze the difference between the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated sample melting curve and the value 0, and the fluorescence at each data point position in the inverse of the first-order derivative function of each decontaminated positive control sample melting curve, to obtain the fusion weight of the fluorescence at each data point position in the decontaminated sample melting curve; A fluorescence correction module, connected to the fusion weight acquisition module, is used to perform weighted calculation based on the fluorescence at each data point position in the melting curve of each decontaminated sample to be tested and the fusion weight of the fluorescence to obtain the deviation-corrected fluorescence at each data point position; A fusion sample melting curve acquisition module is connected to the noise pollution weight acquisition module and the fluorescence correction module, and is used to correct the fluorescence according to the noise pollution weight and the deviation, and to determine the fusion value of the fluorescence at each data point position in all decontaminated sample melting curves, so as to obtain a fusion sample melting curve; The typing output module is connected to the fusion sample melting curve acquisition module and the decontamination melting curve acquisition module, and is used to determine the HPV virus type of the sample to be tested based on the similarity between the inverse of the first-order derivative function of the fusion sample melting curve and the inverse of the first-order derivative function of each decontamination positive control sample melting curve.