PCR curve fitting method, device, storage medium and computer equipment

Abstract

The PCR curve fitting method, device, storage medium and computer equipment provided by the present application can first determine the background period of the original PCR curve after obtaining the original PCR curve, and then pre-process the original PCR curve when it is determined that the original PCR curve has amplification according to the fluorescence value of the background period, and then calculate the first Ct value corresponding to the pre-processed original PCR curve, so that the accuracy of the first Ct value calculated in this way is relatively high; the present application can also determine the exponential growth period, linear growth area and plateau period of the original PCR curve based on the fluorescence value of the background period, and use the data points of each stage to perform curve fitting, and then calculate the second Ct value corresponding to the fitted PCR curve, and finally determine the final fitting curve according to the difference between the first Ct value and the second Ct value, so as to obtain a fitting curve with high fidelity and not over-modified.

Description

Technical Field

[0001] The present application relates to the field of PCR detection technology, and in particular to a PCR curve fitting method, device, storage medium and computer equipment. Background Art

[0002] In real-time fluorescence quantitative PCR (polymerase chain reaction) technology, the Ct value refers to the number of cycles experienced when the fluorescent signal in each reaction tube reaches the set threshold. The more the starting template amount, the smaller the Ct value; the less the starting template amount, the larger the Ct value.

[0003] At present, in traditional real-time fluorescence quantitative PCR technology, Ct values ​​are often detected using threshold setting methods, auxiliary baseline methods, maximum second-order derivative methods, etc. Traditional methods can be used for routine detection, but in low fluorescence signal or low-depth sample environments, traditional methods have problems such as kinetic mismatch or poor fidelity. In addition, traditional methods also have problems with unsightly or over-modified display of curves. Summary of the invention

[0004] The purpose of the present application is to solve at least one of the above-mentioned technical defects, especially the technical defects of low Ct value detection accuracy, poor fidelity of fitting curve and insufficient aesthetics in the PCR curve fitting method in the prior art.

[0005] The present application provides a PCR curve fitting method, the method comprising:

[0006] Obtaining an original PCR curve, and determining a background period of the original PCR curve;

[0007] When it is determined that the original PCR curve has an amplification phenomenon according to the fluorescence value of the background period, preprocessing the original PCR curve, and calculating a first Ct value corresponding to the preprocessed original PCR curve;

[0008] Determine the exponential growth phase, linear growth region and plateau phase of the original PCR curve based on the fluorescence value of the background phase, perform curve fitting using the data points of the background phase, exponential growth phase, linear growth region and plateau phase, and calculate the second Ct value corresponding to the fitted PCR curve;

[0009] A final fitting curve is determined according to the difference between the first Ct value and the second Ct value.

[0010] Optionally, determining whether the original PCR curve has amplification according to the fluorescence value of the background period includes:

[0011] Subtracting the fluorescence values ​​at every two cycle numbers in the background period, and determining the maximum fluorescence difference value in the background period according to the subtraction result;

[0012] Determine the maximum fluorescence value of the original PCR curve;

[0013] Whether the original PCR curve has amplification is determined according to the maximum fluorescence difference in the background period and the maximum fluorescence value.

[0014] Optionally, preprocessing the original PCR curve and calculating a first Ct value corresponding to the preprocessed original PCR curve includes:

[0015] Performing interpolation filtering on the original PCR curve, and performing smoothing processing on the filtered original PCR curve;

[0016] Calculate the first Ct value corresponding to the original PCR curve after smoothing.

[0017] Optionally, the calculating a first Ct value corresponding to the original PCR curve after smoothing includes:

[0018] Calculate the platform value of the original PCR curve after smoothing;

[0019] Based on the original PCR curve after the smoothing process and the corresponding platform value, normalizing the original PCR curve after the smoothing process to obtain a normalized curve;

[0020] The cycle number at the intersection of the normalized curve and the preset threshold line is taken as the first Ct value.

[0021] Optionally, determining the exponential growth phase, linear growth region and plateau phase of the original PCR curve based on the fluorescence value of the background phase comprises:

[0022] Determine the exponential growth phase and the corresponding baseline value of the original PCR curve according to the fluorescence value of the background phase;

[0023] interpolating the original PCR curve, and determining a linear growth region corresponding to the interpolated original PCR curve based on the baseline value;

[0024] The plateau phase of the original PCR curve is determined according to the cycle interval of the linear growth zone.

[0025] Optionally, determining the exponential growth period and the corresponding baseline value of the original PCR curve according to the fluorescence value of the background period includes:

[0026] Determining the maximum fluorescence difference and the maximum fluorescence value during the background period;

[0027] Determine the starting point of the exponential growth phase of the original PCR curve according to the maximum fluorescence difference value and the maximum fluorescence value of the background phase, and determine the end point of the exponential growth phase according to the fluorescence value corresponding to each cycle number in the original PCR curve;

[0028] Determine the cycle interval of the exponential growth phase of the original PCR curve according to the starting point and the ending point, and divide the cycle interval of the exponential growth phase into two sub-intervals;

[0029] The maximum fluorescence value of the background period is used as the initial baseline value, and the maximum fluorescence difference of the background period is used as the initial step length. The initial baseline value is iteratively calculated until the slope difference between the two sub-intervals no longer decreases or reaches the maximum number of iterations, thereby obtaining the final baseline value.

[0030] Optionally, determining the linear growth region corresponding to the interpolated original PCR curve based on the baseline value includes:

[0031] Correcting the interpolated original PCR curve using the baseline value to obtain a corrected original PCR curve;

[0032] Determine the upper limit of the linear growth region of the corrected original PCR curve according to the fluorescence value corresponding to each cycle number in the original PCR curve;

[0033] Determine the PCR efficiency and the number of iterations in the linear growth region, and use the PCR efficiency as a threshold value in the linear growth region;

[0034] Taking the upper limit value as the initial upper limit value, the PCR efficiency variance corresponding to the sampling points whose PCR efficiency is not greater than the threshold value in the corrected original PCR curve is iteratively calculated until the number of iterations is reached, and the cycle interval corresponding to a group of sampling points with the smallest PCR efficiency variance during the iteration process is selected as the final linear growth area.

[0035] Optionally, the curve fitting using the data points of the background period, the exponential growth period, the linear growth area and the plateau period includes:

[0036] Determine the center point value of the original PCR curve according to the data points of the background period, exponential growth period, linear growth area and plateau period;

[0037] The minimum fluorescence value of the background period is used as the background fluorescence intensity value of the original PCR curve;

[0038] Calculate the steepness value of the exponential growth period, the steepness value of the linear growth area, and the maximum fluorescence intensity value of the plateau period according to the center point value and the background fluorescence intensity value;

[0039] The center point value, the background fluorescence intensity value, the steepness value of the exponential growth phase, the steepness value of the linear growth region, and the maximum fluorescence intensity value of the plateau phase are input into the Richard function to fit the original PCR curve.

[0040] Optionally, determining a final fitting curve according to a difference between the first Ct value and the second Ct value comprises:

[0041] comparing the difference between the first Ct value and the second Ct value with a preset difference threshold;

[0042] If the difference is less than the preset difference threshold, the fitted PCR curve is directly used as the final PCR curve;

[0043] If the difference is not less than the preset difference threshold, the original PCR curve is refitted until the difference between the first Ct value and the second Ct value corresponding to the fitted PCR curve is less than the preset difference threshold, thereby obtaining a final fitting curve.

[0044] The present application also provides a PCR curve fitting device, comprising:

[0045] A PCR curve acquisition module, used to acquire an original PCR curve and determine a background period of the original PCR curve;

[0046] A first Ct value determination module is used to pre-process the original PCR curve when it is determined according to the fluorescence value of the background period that the original PCR curve has an amplification phenomenon, and calculate a first Ct value corresponding to the pre-processed original PCR curve;

[0047] A second Ct value determination module is used to determine the exponential growth period, linear growth area and plateau period of the original PCR curve based on the fluorescence value of the background period, and to perform curve fitting using the data points of the background period, exponential growth period, linear growth area and plateau period, and to calculate a second Ct value corresponding to the fitted PCR curve;

[0048] The fitting curve determination module is used to determine a final fitting curve according to the difference between the first Ct value and the second Ct value.

[0049] The present application also provides a computer-readable storage medium, in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the PCR curve fitting method described in any of the above embodiments.

[0050] The present application also provides a computer device, comprising: one or more processors, and a memory;

[0051] The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the PCR curve fitting method described in any one of the above embodiments are performed.

[0052] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0053] The PCR curve fitting method, device, storage medium and computer equipment provided by the present application can first determine the background period of the original PCR curve after obtaining the original PCR curve, and then determine whether the original PCR curve has an amplification phenomenon based on the fluorescence value of the background period. At this time, since the present application makes a judgment based on the fluorescence value of the background period, rather than directly judging by the multiple of the lowest fluorescence intensity point, even in an environment with a low fluorescence signal or a low-depth sample, the judgment method of the present application can be used to accurately judge whether the original PCR curve has an amplification phenomenon, and when there is an amplification phenomenon, the original PCR curve is first preprocessed, and then the first Ct value corresponding to the preprocessed original PCR curve is calculated, so that the accuracy of the calculated first Ct value will be relatively high; secondly, the present application can also be based on the fluorescence value of the background period. The exponential growth period, linear growth area and plateau period of the original PCR curve are determined by using the data points of the background period, exponential growth period, linear growth area and plateau period for curve fitting, and then the second Ct value corresponding to the fitted PCR curve is calculated. This process solves the problem of some points that are still in the background period but are included in the exponential growth period, thereby effectively improving the calculation accuracy of the second Ct value. Finally, the present application can determine the final fitting curve according to the difference between the first Ct value and the second Ct value. For example, when the difference between the two is within 1, it means that the fidelity of the fitting curve is high and the modification is appropriate. When the difference between the two is greater than 1, the fitting can be re-performed according to the difference to obtain a fitting curve with high fidelity and not over-modified. The accuracy of the final second Ct value calculated by the fitting curve is also high. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0055] Figure 1A schematic diagram of a PCR curve fitting method provided in an embodiment of the present application;

[0056] Figure 2 A schematic diagram of the structure of the original PCR curve provided in the embodiment of the present application;

[0057] Figure 3 A statistical graph of the mean square error of the original PCR curve after interpolation and filtering provided in the embodiment of the present application;

[0058] Figure 4 A schematic diagram of the structure of a normalized curve and a preset threshold line provided in an embodiment of the present application;

[0059] Figure 5 A schematic diagram of a baseline variation trend provided in an embodiment of the present application;

[0060] Figure 6 A schematic diagram of the structure of the linear growth region of the PCR curve provided in the embodiment of the present application;

[0061] Figure 7 A schematic diagram of the Richard function provided in an embodiment of the present application;

[0062] Figure 8 A schematic diagram of PCR curve fitting comparison provided in the examples of the present application;

[0063] Fig. 9 A schematic diagram of the structure of a PCR curve fitting device provided in an embodiment of the present application;

[0064] Fig.10 A schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0066] At present, in traditional real-time fluorescence quantitative PCR technology, Ct values ​​are often detected using threshold setting methods, auxiliary baseline methods, maximum second-order derivative methods, etc. Traditional methods can be used for routine detection, but in low fluorescence signal or low-depth sample environments, traditional methods have problems such as kinetic mismatch or poor fidelity. In addition, traditional methods also have problems with unsightly or over-modified display of curves.

[0067] Based on this, this application proposes the following technical solutions, see below for details:

[0068] In one embodiment, Figure 1 As shown, Figure 1 A schematic diagram of a process flow of a PCR curve fitting method provided in an embodiment of the present application; the present application provides a PCR curve fitting method, which may include:

[0069] S110: Obtaining an original PCR curve, and determining a background period of the original PCR curve.

[0070] In this step, when fitting the PCR curve, the original PCR curve can be obtained first. The horizontal axis of the original PCR curve is the cycle number, and the vertical axis is the fluorescence signal value (referred to as fluorescence value) corresponding to each cycle number. After preliminary processing of the original PCR curve, preparation for subsequent analysis can be made.

[0071] Indicatively, if Figure 2 As shown, Figure 2 A schematic diagram of the structure of the original PCR curve provided in the embodiment of the present application; Figure 2 The original PCR curve in not only shows the fluorescence signal value at the end of each cycle in the PCR reaction, but also reflects the changes in the amount of target DNA as the number of cycles increases. However, since the original PCR curve may have noise and fluctuations, the present application can fit the original PCR curve, which can make the curve smoother, make it easier to observe trends and features, and help reduce the impact of random errors, making the data more stable and reliable. For example, during the fluorescent PCR process, instrument noise, sample heterogeneity, or changes in other experimental conditions may cause the original PCR curve to have jagged or irregular fluctuations. After the fitting operation of the present application, these noises can be removed, making the curve smoother and better reflecting the actual amplification process.

[0072] Moreover, fitting can also help determine key parameters in the fluorescence PCR curve, such as the Ct value (cycle threshold). The Ct value refers to the number of cycles experienced when the fluorescence signal reaches the set threshold, which is an important indicator for determining whether the target nucleic acid exists in the sample. By fitting the curve, the present application can more accurately determine the Ct value and reduce the error of human judgment. At the same time, fitting can also provide other parameters, such as amplification efficiency, starting template amount, etc., which are also very important for the analysis and interpretation of experimental results.

[0073] Furthermore, after obtaining the original PCR curve, in order to determine whether the original PCR curve has amplification, and then determine whether to perform curve fitting operations and calculate Ct values, etc., the present application can first determine the background period of the original PCR curve, and then determine whether the original PCR curve has amplification according to the fluorescence value of the background period.

[0074] When determining the background period of the original PCR curve, the present application can determine the number of cycles corresponding to the background period based on the number of cycles corresponding to the PCR curve where the amplification phenomenon usually occurs. For example, the amplification phenomenon usually occurs around the 20th cycle, and the 3rd to 15th cycles are basically in the background period; and, starting from the third cycle, the fluorescence intensity is relatively stable, which can alleviate the impact caused by the positive and negative deviations of the fluorescence intensity of the first two cycles. Therefore, the present application can define the 3rd to 15th cycles in the original PCR curve as the background period, and judge whether the original PCR curve has amplification phenomenon based on the background period.

[0075] It can be understood that, in general, the PCR curve can be divided into the background phase, exponential growth phase, linear growth region and plateau phase, as follows:

[0076] 1. Background period: In the early stage of PCR reaction, the fluorescence signal is weak, mainly due to the background noise of the instrument itself and the influence of non-specific fluorescence. The fluorescence intensity does not change significantly in this stage and is relatively stable, so it can provide a basic reference value for subsequent data analysis and be used to determine the starting level of the fluorescence signal.

[0077] 2. Exponential growth phase: As the PCR cycle progresses, the target nucleic acid fragment is exponentially amplified and the fluorescence signal is rapidly enhanced. The slope of the curve in this phase is large, and the fluorescence intensity increases very quickly. Therefore, this phase is a key phase for quantitative analysis, and the initial concentration of the target nucleic acid can be determined by the curve characteristics of this phase.

[0078] 3. Linear growth zone: After the exponential growth period, due to the limitations of various factors in the reaction system, such as the consumption of primers, enzymes, dNTPs, and the accumulation of reaction products, the amplification rate gradually slows down and enters the linear growth stage. The increase rate of fluorescence intensity in this stage is slower than that in the exponential growth period, but it still shows a linear growth trend.

[0079] 4. Plateau phase: When the PCR reaction proceeds to a certain extent, various factors in the reaction system reach a balance, the amplification rate of the target nucleic acid approaches zero, the fluorescence signal intensity no longer increases, and the plateau phase is entered. In this stage, the fluorescence intensity is relatively stable and the curve tends to be flat. Therefore, the final amount of amplified product can be determined by the fluorescence intensity in the plateau phase.

[0080] S120: When it is determined according to the fluorescence value of the background period that the original PCR curve has an amplification phenomenon, preprocessing the original PCR curve, and calculating a first Ct value corresponding to the preprocessed original PCR curve.

[0081] In this step, after obtaining the original PCR curve through S110 and determining the background period of the original PCR curve, the present application can also determine whether the original PCR curve has an amplification phenomenon based on the fluorescence value of the background period, and if there is an amplification phenomenon, pre-process the original PCR curve to calculate the first Ct value corresponding to the pre-processed original PCR curve.

[0082] Specifically, since the fluorescence intensity of the background period does not change significantly and is relatively stable, the present application can determine the fluorescence value of the background period and compare it with other values ​​in the original PCR curve to determine whether the original PCR curve has an amplification phenomenon. In addition, when it is determined that the original PCR curve has an amplification phenomenon, in order to improve the fidelity of the fitting curve, the present application can first pre-process the original PCR curve and calculate the first Ct value corresponding to the pre-processed original PCR curve, so that the first Ct value can be compared with the second Ct value corresponding to the fitted curve to determine the fidelity of the fitting curve. The process can also optimize the number and frequency of acquisition points to obtain a smoother curve, and can also mark important data points, peaks or turning points to avoid excessive modification.

[0083] Among them, when the original PCR curve is preprocessed in the present application, the preprocessing process includes but is not limited to data cleaning, background correction, smoothing, etc. For example, when the original PCR curve is cleaned, it can be cleaned by removing outliers or processing missing values; when the original PCR curve is background corrected, it can be corrected by determining the baseline or deducting the baseline; when the original PCR curve is smoothed, it can be processed by moving average method, polynomial fitting or low-pass filtering. In short, preprocessing the original PCR curve is an important step in data analysis. This process can improve the quality and accuracy of the data and provide a better basis for subsequent analysis and interpretation. The specific method of preprocessing can be selected according to the characteristics of the data and the purpose of analysis, and care should be taken to avoid introducing too many human errors during the processing, which is not limited here.

[0084] S130: Determine the exponential growth phase, linear growth region and plateau phase of the original PCR curve based on the fluorescence value of the background phase, and use the data points of the background phase, exponential growth phase, linear growth region and plateau phase to perform curve fitting, and calculate the second Ct value corresponding to the fitted PCR curve.

[0085] In this step, after determining that the original PCR curve has amplification according to the fluorescence value of the background period through S120, the present application can not only calculate the first Ct value corresponding to the original PCR curve after pretreatment, but also determine the exponential growth period, linear growth area and plateau period of the original PCR curve based on the fluorescence value of the background period, and use the data points of each stage to perform curve fitting, so as to calculate the second Ct value corresponding to the fitted PCR curve.

[0086] Among them, when the present application determines the exponential growth period, linear growth area and plateau period of the original PCR curve based on the fluorescence value of the background period, since the background period is adjacent to the exponential growth period, the exponential growth period is adjacent to the linear growth area, and the linear growth area is adjacent to the plateau period. Therefore, the present application can first determine the cycle interval of the exponential growth period based on the fluorescence value of the background period, and then use the cycle interval of the exponential growth period to determine the cycle interval of the linear growth area, and finally determine the cycle interval of the plateau period.

[0087] Next, the present application can use the data points of each stage to perform curve fitting. When fitting, the present application can use S-type curve fitting (Logistic model, etc.), which can better describe the entire process of the PCR curve from the initial baseline period to the exponential growth period and then to the plateau period; polynomial fitting can also be used, which can flexibly adapt to different curve shapes; segmented fitting can also be used, which can accurately describe the curve characteristics of each stage, especially when the PCR curve has significantly different change trends in different stages; nonlinear least squares fitting can also be selected, which can also obtain more accurate parameter estimates. Of course, the specific method selected for curve fitting can be set according to the actual situation and is not limited here.

[0088] S140: Determine a final fitting curve according to the difference between the first Ct value and the second Ct value.

[0089] In this step, after calculating the first Ct value corresponding to the preprocessed original PCR curve through S120, and calculating the second Ct value corresponding to the fitted PCR curve through S130, the present application can determine the final fitting curve based on the difference between the first Ct value and the second Ct value, and then determine the final second Ct value.

[0090] In detail, after the present application preprocesses the original PCR curve and calculates the first Ct value corresponding to the preprocessed original PCR curve, the first Ct value reflects the number of cycles experienced when the fluorescence signal in the original PCR curve reaches the set threshold; and after the present application calculates the second Ct value corresponding to the fitted PCR curve, the second Ct value reflects the number of cycles experienced when the fluorescence signal in the fitted PCR curve reaches the set threshold; therefore, after the present application subtracts the first Ct value from the second Ct value, the difference between the fitted PCR curve and the original PCR curve can be determined, and then the fidelity of the fitted PCR curve can be determined.

[0091] Therefore, the present application can determine whether to adjust the relevant parameters during curve fitting based on the difference between the first Ct value and the second Ct value, so that the difference between the second Ct value corresponding to the fitted PCR curve and the first Ct value is within a preset difference range. This can improve both the fidelity of the fitting curve and the detection accuracy of the Ct value.

[0092] In the above embodiment, after obtaining the original PCR curve, the present application can first determine the background period of the original PCR curve, and then determine whether the original PCR curve has an amplification phenomenon based on the fluorescence value of the background period. At this time, since the present application makes a judgment based on the fluorescence value of the background period, rather than directly judging by the multiple of the lowest fluorescence intensity point, even in an environment with a low fluorescence signal or a low-depth sample, the judgment method of the present application can be used to accurately judge whether the original PCR curve has an amplification phenomenon, and when there is an amplification phenomenon, the original PCR curve is first preprocessed, and then the first Ct value corresponding to the preprocessed original PCR curve is calculated. The accuracy of the first Ct value calculated in this way will also be relatively high; secondly, the present application can also determine the index of the original PCR curve based on the fluorescence value of the background period. The data points of the background period, exponential growth period, linear growth area and plateau period are used to perform curve fitting, and then the second Ct value corresponding to the fitted PCR curve is calculated. This process solves the problem of some points that are still in the background period but are included in the exponential growth period, thereby effectively improving the calculation accuracy of the second Ct value. Finally, the present application can determine the final fitting curve according to the difference between the first Ct value and the second Ct value. For example, when the difference between the two is within 1, it means that the fidelity of the fitting curve is high and the modification is appropriate. When the difference between the two is greater than 1, the fitting can be re-performed according to the difference to obtain a fitting curve with high fidelity and not over-modified. The accuracy of the final second Ct value calculated by the fitting curve is also high.

[0093] In one embodiment, determining whether the original PCR curve has amplification according to the fluorescence value of the background period in S120 may include:

[0094] S121: Subtract the fluorescence values ​​at every two cycle numbers in the background period, and determine the maximum fluorescence difference value in the background period according to the subtraction result.

[0095] S122: Determine the maximum fluorescence value of the original PCR curve.

[0096] S123: Determine whether the original PCR curve has amplification according to the maximum fluorescence difference value of the background period and the maximum fluorescence value.

[0097] In this embodiment, after determining the background period of the original PCR curve, the present application can also determine whether the original PCR curve has an amplification phenomenon based on the fluorescence value of the background period. This can not only determine whether a curve fitting operation is required, but also accurately determine whether there is an amplification phenomenon based on the fluorescence value of the background period.

[0098] Specifically, when determining whether the original PCR curve has amplification, the present application can first subtract the fluorescence values ​​at every two cycles in the background period to determine the maximum fluorescence difference in the background period. Then, the present application can determine the maximum fluorescence value of the original PCR curve. In this way, it can be determined whether the original PCR curve has amplification based on the maximum fluorescence difference and the maximum fluorescence value of the background period.

[0099] For example, the present application can define the 3rd to 15th cycles in the original PCR curve as the background period, and then calculate the maximum fluorescence difference in the background period by subtracting the fluorescence values ​​at every two cycles in the background period, and compare the difference with the maximum fluorescence value of the original PCR curve at 10 times to determine whether amplification occurs.

[0100] It is understandable that since the existing method (LineRegPCR method) directly uses the multiple of the lowest fluorescence intensity point to determine whether the original PCR curve has amplification, this determination method is not applicable when the background fluorescence intensity of the original PCR curve is very high. However, the present application determines whether there is amplification by comparing the maximum fluorescence difference of the background period with the maximum fluorescence value of the original PCR curve. In this way, regardless of the background fluorescence intensity or the depth of the sample environment, a relatively accurate determination result can be obtained by the determination method of the present application.

[0101] In one embodiment, preprocessing the original PCR curve in S120 and calculating the first Ct value corresponding to the preprocessed original PCR curve may include:

[0102] S124: performing interpolation filtering on the original PCR curve, and performing smoothing processing on the filtered original PCR curve.

[0103] S125: Calculate the first Ct value corresponding to the original PCR curve after smoothing.

[0104] In this embodiment, in order to improve the detection accuracy of the first Ct value, when determining that the original PCR curve has amplification, the present application can perform a preprocessing operation on it, and then calculate the first Ct value corresponding to the preprocessed original PCR curve.

[0105] Specifically, when the present application performs preprocessing on the original PCR curve, since the original PCR curve usually only goes through 40-50 cycles and the sample points are relatively few, the present application can use the interpolation method to increase the number of sample points, so that the amplification curve will not be distorted in the subsequent filtering stage. When the present application uses the interpolation method to increase the number of sample points, linear interpolation, polynomial interpolation, spline interpolation or segmented interpolation can be used for interpolation calculation, which can be selected according to the actual situation and is not limited here.

[0106] For example, when a curve has certain oscillations, the makima interpolation method has a better performance effect. Therefore, the present application can use the makima method to interpolate the curve, thereby avoiding the sudden flattening phenomenon near the local extreme value.

[0107] Next, the present application can filter the original PCR curve after interpolation, and smooth the original PCR curve after filtering. For example, the present application can perform median filtering on the original PCR curve after interpolation. When filtering, the median of the N points before and after the current point, a total of 2N+1 points, can be selected as the value of the current point. This method can filter out some glitches and jump points; then, the present application can smooth the original PCR curve after filtering. Specifically, it can be calculated that the N points before and after the current point, a total of 2N+1 points, are used as the window average value, and this is used as the value of the point. This method can remove noise in the original PCR curve. After the original PCR curve is interpolated, filtered, and smoothed, the first Ct value of the original PCR curve after smoothing can be calculated.

[0108] Furthermore, if Figure 3 As shown, Figure 3 A statistical graph of the mean square error of the original PCR curve after interpolation and filtering provided in the embodiment of the present application; Figure 3 The mean square error of the PCR curve before and after interpolation filtering under different window points is statistically analyzed. Figure 3 It can be seen that when the present application performs smoothing on the filtered original PCR curve, the mean square error is more ideal when the window number of points is selected to be 3-5.

[0109] In one embodiment, calculating the first Ct value corresponding to the original PCR curve after smoothing in S125 may include:

[0110] S1251: Calculate the platform value of the original PCR curve after smoothing.

[0111] S1252: Based on the original PCR curve after the smoothing process and the corresponding platform value, the original PCR curve after the smoothing process is normalized to obtain a normalized curve.

[0112] S1253: The cycle number at the intersection of the normalized curve and the preset threshold line is taken as the first Ct value.

[0113] In this embodiment, when calculating the first Ct value corresponding to the original PCR curve after smoothing, the original PCR curve can be normalized first, and then the preset threshold line is determined. Then, the preset threshold line is drawn on the normalized curve to determine the first Ct value.

[0114] Among them, when normalizing the original PCR curve, the present application can first calculate the platform value of the original PCR curve after smoothing, and the platform value refers to the relatively stable value reached when the intensity of the fluorescent signal no longer changes significantly with the increase of the number of cycles during the fluorescent PCR process. After determining the platform value, the present application can use the platform value to normalize the original PCR curve after smoothing, and then obtain a normalized curve.

[0115] In a specific embodiment, the present application can calculate the platform value of the original PCR curve after smoothing in two ways, as follows:

[0116] ① Calculate the average value of all points within the relative position range of the maximum second-order derivative value point of the smoothed original PCR curve, such as the average value of the first 5 points from the beginning to the maximum second-order derivative value point. This can not only better reflect the background value of the curve, but also prevent the background value from being underestimated, affecting subsequent judgments and preventing false positives.

[0117] ② Directly take the average of the fluorescence values ​​of the 6th to 12th points in the original PCR after smoothing as the platform value.

[0118] Furthermore, when the platform value is used to normalize the original PCR curve after smoothing, multiple processing methods can also be used, as follows:

[0119]

[0120] in, is the normalized curve obtained using the “relative fluorescence value method-log”; The normalized curve was obtained using the “relative fluorescence value method-linear”; is the original PCR curve after smoothing; is the platform value.

[0121] Of course, the present application can also normalize the original PCR curve by other methods, which can be selected according to the actual situation and are not limited here.

[0122] After obtaining the normalized curve, the present application draws a preset threshold line on the normalized curve. The preset threshold line can be set manually or according to the default value, or can be set with reference to the peak value of the negative control sample in the daily PCR experiment, which is not limited here. Figure 4 As shown, Figure 4 A schematic diagram of the structure of a normalized curve and a preset threshold line provided in an embodiment of the present application; Figure 4 The red line in the figure is the preset threshold line, and the blue line is the normalized curve. In the present application, the cycle number at the intersection of the normalized curve and the preset threshold line can be used as the first Ct value, and then the first Ct value can be used to determine the fidelity of the fitting curve.

[0123] In one embodiment, determining the exponential growth phase, the linear growth region, and the plateau phase of the original PCR curve based on the fluorescence value of the background phase in S130 may include:

[0124] S131: Determine the exponential growth period and the corresponding baseline value of the original PCR curve according to the fluorescence value of the background period.

[0125] S132: interpolating the original PCR curve, and determining a linear growth region corresponding to the interpolated original PCR curve based on the baseline value.

[0126] S133: Determine the plateau phase of the original PCR curve according to the cycle interval of the linear growth zone.

[0127] In this embodiment, when determining the exponential growth period, linear growth zone and plateau period of the original PCR curve, the exponential growth period and the corresponding baseline value of the original PCR curve can be determined based on the fluorescence value of the background period. The baseline value can not only remove non-specific fluorescence, but also be used to improve the signal-to-noise ratio, and can even be used to determine the Ct value and evaluate the amplification efficiency. Therefore, after determining the exponential growth period of the original PCR curve, the present application first interpolates the original PCR curve, and then determines the linear growth zone corresponding to the interpolated original PCR curve based on the baseline value. This can avoid the original PCR curve from flattening sharply near the local extreme value, and can correct the linear growth zone of the original PCR curve to obtain a more accurate cycle interval. Finally, after the present application determines the linear growth zone, the plateau period of the original PCR curve can be further determined.

[0128] In one embodiment, determining the exponential growth period and the corresponding baseline value of the original PCR curve according to the fluorescence value of the background period in S131 may include:

[0129] S1311: Determine the maximum fluorescence difference and the maximum fluorescence value in the background period.

[0130] S1312: Determine the starting point of the exponential growth phase of the original PCR curve according to the maximum fluorescence difference and the maximum fluorescence value of the background period, and determine the end point of the exponential growth phase according to the fluorescence value corresponding to each cycle number in the original PCR curve.

[0131] S1313: Determine the cycle interval of the exponential growth phase of the original PCR curve according to the starting point and the ending point, and divide the cycle interval of the exponential growth phase into two equal sub-intervals.

[0132] S1314: Taking the maximum fluorescence value of the background period as the initial baseline value and the maximum fluorescence difference of the background period as the initial step length, the initial baseline value is iteratively calculated until the slope difference between the two sub-intervals no longer decreases or reaches the maximum number of iterations, thereby obtaining a final baseline value.

[0133] In this embodiment, when determining the exponential growth period and the corresponding baseline value of the original PCR curve, the maximum fluorescence value and the maximum fluorescence difference of the background period can be selected first, and then the maximum fluorescence value plus the fluorescence intensity of 1 times the maximum fluorescence difference can be used as the starting point of the exponential growth period, which can reduce the impact of the background period, ensure the accuracy of the baseline, and prevent false positives. Next, the present application can use the SDM point as the end point of the exponential growth period, and divide the estimated exponential growth period into two parts, and then use the maximum fluorescence value of the background period as the initial baseline value and the maximum fluorescence difference of the background period as the initial step length, and iterate the initial baseline value until the slope difference between the two sub-intervals no longer decreases or reaches the maximum number of iterations, and obtain the final baseline value.

[0134] The SDM point in this application refers to the maximum second-order derivative value point obtained by calculating the second-order derivative of the fluorescence value of each cycle in the original PCR curve. So far, the specific iterative process of this application is as follows:

[0135] initialization:

[0136] Assume that the maximum fluorescence difference during the background period is Δmax = 10.

[0137] The initial baseline position baseline_init=background_max+Δmax, where background_max is the maximum fluorescence value during the background period.

[0138] The initial step size is step = Δmax.

[0139] Set the maximum number of iterations max_iter = 10.

[0140] The slope difference threshold is threshold = 0.01.

[0141] Iteration process:

[0142] In each iteration, the baseline position is moved downward by the distance step and a new baseline position is calculated.

[0143] Using the new baseline position, calculate the difference in slope between the upper and lower parts of the exponential growth period.

[0144] If the slope difference is less than the threshold or reaches the minimum value, the current baseline position and slope difference are recorded.

[0145] If the slope difference is greater than the previous minimum, reduce the step size and continue iterating.

[0146] Repeat the above steps until the maximum number of iterations is reached or the slope difference no longer decreases.

[0147] Example iteration:

[0148] First iteration: baseline position baseline = baseline_init - step, slope difference slope_diff = 0.03.

[0149] Second iteration: baseline position baseline = baseline - step, slope difference slope_diff = 0.02.

[0150] Third iteration: baseline position baseline = baseline - step, slope difference slope_diff = 0.015.

[0151] Fourth iteration: baseline position baseline = baseline - step, slope difference slope_diff = 0.012.

[0152] Fifth iteration: baseline position baseline = baseline - step, slope difference slope_diff = 0.011.

[0153] Sixth iteration: baseline position baseline = baseline - step, slope difference slope_diff = 0.013.

[0154] In the above example, the minimum slope difference occurs in the fifth iteration, with a slope difference of 0.011, so the baseline position of the fifth iteration is the optimal baseline position to be found. Figure 5 As shown, Figure 5 A schematic diagram of a baseline variation trend provided in an embodiment of the present application; Figure 5 It can be seen that as the number of iterations increases, the baseline value tends to be stable, and the baseline value estimated during the iteration process is between the minimum fluorescence value in the background period and the minimum fluorescence value in the exponential growth period.

[0155] In one embodiment, determining the linear growth region corresponding to the interpolated original PCR curve based on the baseline value in S132 may include:

[0156] S1321: Correcting the interpolated original PCR curve using the baseline value to obtain a corrected original PCR curve.

[0157] S1322: Determine the upper limit of the linear growth region of the corrected original PCR curve according to the fluorescence value corresponding to each cycle number in the original PCR curve.

[0158] S1323: Determine the PCR efficiency and the number of iterations in the linear growth region, and use the PCR efficiency as a threshold value in the linear growth region.

[0159] S1324: Taking the upper limit value as the initial upper limit value, iteratively calculate the PCR efficiency variance corresponding to the sampling points whose PCR efficiency is not greater than the threshold value in the corrected original PCR curve until the number of iterations is reached, and select the cycle interval corresponding to a group of sampling points with the smallest PCR efficiency variance during the iteration process as the final linear growth area.

[0160] In this embodiment, after the original PCR curve is interpolated, the baseline value can be used to correct the interpolated original PCR curve to obtain the corrected original PCR curve. Then, the present application can determine the upper limit value corresponding to the linear growth area of ​​the corrected original PCR curve based on the fluorescence value corresponding to each cycle number in the original PCR curve, and then set the PCR efficiency and the number of iterations in the linear growth area. After using the PCR efficiency as the threshold value, the upper limit value is used as the initial upper limit value to iteratively calculate the PCR efficiency variance corresponding to the sampling points in the corrected original PCR curve whose PCR efficiency is not greater than the threshold value until the number of iterations is reached. At this time, the cycle interval corresponding to a group of sampling points with the smallest PCR efficiency variance in the iterative process can be selected as the final linear growth area.

[0161] In a specific embodiment, the present application can interpolate the original PCR curve based on the standard method, set the amplification efficiency to 0.8, and set the number of iterations to 10 times. The specific iteration process is as follows:

[0162] initialization:

[0163] Use the baseline value estimated in the previous step to process the interpolated original PCR curve.

[0164] The default linear growth area must have at least 16 sampling points.

[0165] The SDM point (the point with the maximum second-order derivative value) is taken as the upper limit of the linear growth region.

[0166] The default PCR efficiency is 0.8, which is used as the threshold value of the linear growth region.

[0167] Calculate PCR efficiency:

[0168] The average PCR efficiency of the points still within the linear window at this time was calculated.

[0169] The variance of PCR efficiency was recorded.

[0170] Iteration process:

[0171] The set upper limit value is continuously reduced during the iteration process.

[0172] Each time the upper limit value is lowered, the PCR efficiency and variance are recalculated.

[0173] The number of iterations is usually 10.

[0174] Determine the linear growth region:

[0175] The group with the smallest PCR efficiency variance during the iteration process is selected as the final linear growth zone.

[0176] Indicatively, if Figure 6 As shown, Figure 6 A schematic diagram of the structure of the linear growth region of the PCR curve provided in the embodiment of the present application; Figure 6 It can be seen that the linear growth area of ​​the original PCR curve can be quickly determined by the above-mentioned iterative method of the present application.

[0177] In one embodiment, performing curve fitting using the data points of the background period, the exponential growth period, the linear growth region, and the plateau period in S130 may include:

[0178] S134: Determine the center point value of the original PCR curve according to the data points of the background period, exponential growth period, linear growth area and plateau period.

[0179] S135: Taking the minimum fluorescence value of the background period as the background fluorescence intensity value of the original PCR curve.

[0180] S136: Calculate the steepness value of the exponential growth period, the steepness value of the linear growth area, and the maximum fluorescence intensity value of the plateau period according to the center point value and the background fluorescence intensity value.

[0181] S137: Input the center point value, the background fluorescence intensity value, the steepness value of the exponential growth phase, the steepness value of the linear growth region, and the maximum fluorescence intensity value of the plateau phase into the Richard function to fit the original PCR curve.

[0182] In this embodiment, after determining the background period, exponential growth period, linear growth zone and plateau period of the original PCR curve, in order to obtain a fitting curve with higher aesthetics and appropriate modification, the present application can first determine the center point value of the original PCR curve based on the data points of the background period, exponential growth period, linear growth zone and plateau period, and then use the minimum fluorescence value of the background period as the background fluorescence intensity value of the original PCR curve. After calculating the steepness value of the exponential growth period, the steepness value of the linear growth zone and the maximum fluorescence intensity value of the plateau period based on the center point value and the background fluorescence intensity value, the original PCR curve is fitted based on these key values. In this way, a fitting curve with higher fidelity can be obtained while avoiding excessive modification.

[0183] Among them, when determining the center point value of the original PCR curve, the background fluorescence intensity value, the steepness value of the exponential growth period, the steepness value of the linear growth zone, and the maximum fluorescence intensity value of the plateau period, the present application can use the following method to determine:

[0184] like Figure 7 As shown, Figure 7 A schematic diagram of the Richard function provided in the embodiment of the present application; Figure 7 It can be seen that this application needs to give F in the curve fitting process max 、F b The initial values ​​of the five parameters , d, c and b. max Refers to the maximum fluorescence intensity value in the plateau period, F b refers to the steepness value of the exponential growth period, d refers to the steepness value of the linear growth zone, c refers to the center point value of the original PCR curve, and b refers to the background fluorescence intensity value. b , d, F max The initial values ​​are given in the order of a and b.

[0185] First, when the application uses the Richard function for curve fitting, c can be determined by the second-order derivative of the data. c corresponds to the center point of the Richards function. The second-order derivative of the corresponding point can be seen in the following formula:

[0186]

[0187] In the initial case, we can assume that d is approximately equal to 1, and the second-order derivative corresponding to point c is 0; in the case of d>1 and d<1, the second-order derivative of point c is also greater than and less than 0, respectively, but in general, point c is near the point where the sign of the second-order derivative changes. Therefore, the point where the sign of the second-order derivative changes can be calculated here, and the threshold of the first-order derivative value (for example, it can be more than 1 / 3 of the maximum point of the first-order derivative, which can be set by yourself) can be used for judgment.

[0188] After estimating point c, the data of the background period can be processed. Since the value of each point on the fitting curve is greater than 0, the point with the minimum fluorescence intensity during the background period can be selected as F. b The initial value of .

[0189] Then we can select two points on the curve to jointly calculate d and F max . Assume that the two selected points are x1 and x2, and they satisfy the following relationship:

[0190]

[0191] At this time, if , by dividing the logarithmic value by the first-order derivative, we can get the following formula:

[0192]

[0193]

[0194] In this application, a=-1 can be used. In this case, the above two formulas can be divided to directly obtain t, and then d can be calculated by substituting it into formula (1). Similarly, a=0 can be used. In this case, x2 directly corresponds to point c. The two formulas are divided to convert into a linear equation of t, and t can also be obtained, and then d can be calculated. The following formula can be used as a reference:

[0195]

[0196] Then substitute the estimated value into point c and calculate F according to the following formula: max :

[0197]

[0198] Finally, the b value can be estimated based on the calculated t, which can be referred to the following formula:

[0199]

[0200] When this application chooses to take a=0, x2 directly corresponds to point c, and x1 is required to fall within the exponential growth period and the linear growth zone as much as possible. In addition, the effect of selecting the middle position between the SDM point and point c is better. At this time, the fluorescence intensity is basically at the junction of the exponential growth period and the linear growth zone, and a better t value can be obtained, which is suitable for the calculation of subsequent steps.

[0201] Furthermore, the fitting formula of the Richard function in this application is as follows:

[0202]

[0203] This application can complete data fitting by calling the designed function interface. The effect after fitting is as follows Figure 8 As shown, Figure 8 Schematic diagram of PCR curve fitting comparison provided in the examples of the present application; Figure 8 It can be seen that a relatively smooth fitting curve with higher fidelity can be obtained through the fitting method of the present application.

[0204] In one embodiment, determining the final fitting curve according to the difference between the first Ct value and the second Ct value in S140 may include:

[0205] S141: Compare the difference between the first Ct value and the second Ct value with a preset difference threshold.

[0206] S142: If the difference is less than the preset difference threshold, directly taking the fitted PCR curve as the final PCR curve.

[0207] S143: If the difference is not less than the preset difference threshold, refit the original PCR curve until the difference between the first Ct value and the second Ct value corresponding to the fitted PCR curve is less than the preset difference threshold, thereby obtaining a final fitting curve.

[0208] In this embodiment, since the present application subtracts the first Ct value from the second Ct value, the difference between the fitted PCR curve and the original PCR curve can be determined, and the fidelity of the fitted PCR curve can be further determined.

[0209] Therefore, after calculating the difference between the first Ct value and the second Ct value, the present application can compare the difference with the preset difference threshold. If the difference is less than the preset difference threshold, it means that the fidelity of the fitted PCR curve is relatively high, and the fitted PCR curve can be directly used as the final PCR curve; if the difference is not less than the preset difference threshold, it means that the fidelity of the fitted PCR curve is relatively low. At this time, the original PCR curve can be refitted until the difference between the first Ct value and the second Ct value corresponding to the fitted PCR curve is less than the preset difference threshold, thereby obtaining the final fitting curve.

[0210] When the application refits the original PCR curve, the Richard parameter can be adjusted first, and then the original PCR curve can be fitted. The way to adjust the Richard parameter includes but is not limited to increasing the number of iterations: if the previous number of iterations is not enough to achieve convergence, the maximum number of iterations can be increased; trust region adjustment: adjust the size of the trust region according to the fitting results; check the initial value: first check whether the initial estimate is appropriate. If the initial estimate is far from the actual value, it may lead to poor fitting results.

[0211] The above method can ensure that the difference between the second Ct value and the first Ct value corresponding to the fitted PCR curve is less than the preset difference threshold, which can improve the fidelity of the fitting curve and the detection accuracy of the Ct value.

[0212] The PCR curve fitting device provided in the embodiment of the present application is described below. The PCR curve fitting device described below and the PCR curve fitting method described above can be referred to each other.

[0213] In one embodiment, Fig. 9 As shown, Fig. 9 A schematic diagram of the structure of a PCR curve fitting device provided in an embodiment of the present application; the present application also provides a PCR curve fitting device, including a PCR curve acquisition module 210, a first Ct value determination module 220, a second Ct value determination module 230, and a fitting curve determination module 240, which specifically includes the following:

[0214] The PCR curve acquisition module 210 is used to acquire an original PCR curve and determine the background period of the original PCR curve.

[0215] The first Ct value determination module 220 is used to preprocess the original PCR curve when it is determined according to the fluorescence value of the background period that the original PCR curve has an amplification phenomenon, and calculate the first Ct value corresponding to the preprocessed original PCR curve.

[0216] The second Ct value determination module 230 is used to determine the exponential growth period, linear growth area and plateau period of the original PCR curve based on the fluorescence value of the background period, and use the data points of the background period, exponential growth period, linear growth area and plateau period to perform curve fitting, and calculate the second Ct value corresponding to the fitted PCR curve.

[0217] The fitting curve determination module 240 is used to determine a final fitting curve according to the difference between the first Ct value and the second Ct value.

[0218] In the above embodiment, after obtaining the original PCR curve, the present application can first determine the background period of the original PCR curve, and then determine whether the original PCR curve has an amplification phenomenon based on the fluorescence value of the background period. At this time, since the present application makes a judgment based on the fluorescence value of the background period, rather than directly judging by the multiple of the lowest fluorescence intensity point, even in an environment with a low fluorescence signal or a low-depth sample, the judgment method of the present application can be used to accurately judge whether the original PCR curve has an amplification phenomenon, and when there is an amplification phenomenon, the original PCR curve is first preprocessed, and then the first Ct value corresponding to the preprocessed original PCR curve is calculated. The accuracy of the first Ct value calculated in this way will also be relatively high; secondly, the present application can also determine the index of the original PCR curve based on the fluorescence value of the background period. The data points of the background period, exponential growth period, linear growth area and plateau period are used to perform curve fitting, and then the second Ct value corresponding to the fitted PCR curve is calculated. This process solves the problem of some points that are still in the background period but are included in the exponential growth period, thereby effectively improving the calculation accuracy of the second Ct value. Finally, the present application can determine the final fitting curve according to the difference between the first Ct value and the second Ct value. For example, when the difference between the two is within 1, it means that the fidelity of the fitting curve is high and the modification is appropriate. When the difference between the two is greater than 1, the fitting can be re-performed according to the difference to obtain a fitting curve with high fidelity and not over-modified. The accuracy of the final second Ct value calculated by the fitting curve is also high.

[0219] In one embodiment, the present application also provides a computer-readable storage medium, in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the PCR curve fitting method described in any of the above embodiments.

[0220] In one embodiment, the present application also provides a computer device, including: one or more processors, and a memory.

[0221] The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the PCR curve fitting method described in any one of the above embodiments are performed.

[0222] Indicatively, Fig.10 As shown, Fig.10 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. The computer device 300 may be provided as a server. Fig.10The computer device 300 includes a processing component 302, which further includes one or more processors, and a memory resource represented by a memory 301, for storing instructions that can be executed by the processing component 302, such as an application. The application stored in the memory 301 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 302 is configured to execute instructions to perform the PCR curve fitting method of any of the above embodiments.

[0223] The computer device 300 may further include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate based on an operating system stored in the memory 301, such as Windows Server TM, Mac OS X TM, Unix TM, Linux TM, Free BSD TM, or the like.

[0224] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0225] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0226] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can refer to each other.

[0227] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A PCR curve fitting method, characterized in that: The method comprises: Obtaining an original PCR curve, and determining a background period of the original PCR curve; When it is determined that the original PCR curve has an amplification phenomenon according to the fluorescence value of the background period, preprocessing the original PCR curve, and calculating a first Ct value corresponding to the preprocessed original PCR curve; Determine the exponential growth phase, linear growth region and plateau phase of the original PCR curve based on the fluorescence value of the background phase, perform curve fitting using the data points of the background phase, exponential growth phase, linear growth region and plateau phase, and calculate the second Ct value corresponding to the fitted PCR curve; Determining a final fitting curve according to the difference between the first Ct value and the second Ct value; The curve fitting using the data points of the background period, exponential growth period, linear growth area and plateau period includes: Determine the center point value of the original PCR curve according to the data points of the background period, exponential growth period, linear growth area and plateau period; The minimum fluorescence value of the background period is used as the background fluorescence intensity value of the original PCR curve; Calculate the steepness value of the exponential growth period, the steepness value of the linear growth area, and the maximum fluorescence intensity value of the plateau period according to the center point value and the background fluorescence intensity value; The center point value, the background fluorescence intensity value, the steepness value of the exponential growth phase, the steepness value of the linear growth region, and the maximum fluorescence intensity value of the plateau phase are input into the Richard function to fit the original PCR curve.

2. The PCR curve fitting method according to claim 1, characterized in that: The determining whether the original PCR curve has amplification according to the fluorescence value of the background period includes: Subtracting the fluorescence values ​​at every two cycle numbers in the background period, and determining the maximum fluorescence difference value in the background period according to the subtraction result; Determine the maximum fluorescence value of the original PCR curve; Whether the original PCR curve has amplification is determined according to the maximum fluorescence difference in the background period and the maximum fluorescence value.

3. The PCR curve fitting method according to claim 1, characterized in that: The preprocessing of the original PCR curve and calculating the first Ct value corresponding to the preprocessed original PCR curve includes: Performing interpolation filtering on the original PCR curve, and performing smoothing processing on the filtered original PCR curve; Calculate the first Ct value corresponding to the original PCR curve after smoothing.

4. The PCR curve fitting method according to claim 3, characterized in that: The calculating the first Ct value corresponding to the original PCR curve after smoothing includes: Calculate the platform value of the original PCR curve after smoothing; Based on the original PCR curve after the smoothing process and the corresponding platform value, normalizing the original PCR curve after the smoothing process to obtain a normalized curve; The cycle number at the intersection of the normalized curve and the preset threshold line is taken as the first Ct value.

5. The PCR curve fitting method according to any one of claims 1 to 4, characterized in that: The step of determining the exponential growth phase, the linear growth region and the plateau phase of the original PCR curve based on the fluorescence value of the background phase comprises: Determine the exponential growth phase and the corresponding baseline value of the original PCR curve according to the fluorescence value of the background phase; Interpolating the original PCR curve, and determining a linear growth region corresponding to the interpolated original PCR curve based on the baseline value; The plateau phase of the original PCR curve is determined according to the cycle interval of the linear growth zone.

6. The PCR curve fitting method according to claim 5, characterized in that: Determining the exponential growth period and the corresponding baseline value of the original PCR curve according to the fluorescence value of the background period includes: Determining the maximum fluorescence difference and the maximum fluorescence value during the background period; Determine the starting point of the exponential growth phase of the original PCR curve according to the maximum fluorescence difference value and the maximum fluorescence value of the background phase, and determine the end point of the exponential growth phase according to the fluorescence value corresponding to each cycle number in the original PCR curve; Determine the cycle interval of the exponential growth phase of the original PCR curve according to the starting point and the ending point, and divide the cycle interval of the exponential growth phase into two sub-intervals; The maximum fluorescence value of the background period is used as the initial baseline value, and the maximum fluorescence difference of the background period is used as the initial step length. The initial baseline value is iteratively calculated until the slope difference between the two sub-intervals no longer decreases or reaches the maximum number of iterations, thereby obtaining the final baseline value.

7. The PCR curve fitting method according to claim 5, characterized in that: The determining of the linear growth region corresponding to the interpolated original PCR curve based on the baseline value comprises: Using the baseline value to correct the interpolated original PCR curve to obtain a corrected original PCR curve; Determine the upper limit of the linear growth region of the corrected original PCR curve according to the fluorescence value corresponding to each cycle number in the original PCR curve; Determine the PCR efficiency and the number of iterations in the linear growth region, and use the PCR efficiency as a threshold value in the linear growth region; Taking the upper limit value as the initial upper limit value, the PCR efficiency variance corresponding to the sampling points whose PCR efficiency is not greater than the threshold value in the corrected original PCR curve is iteratively calculated until the number of iterations is reached, and the cycle interval corresponding to a group of sampling points with the smallest PCR efficiency variance during the iteration process is selected as the final linear growth area.

8. The PCR curve fitting method according to any one of claims 1 to 4, characterized in that: Determining a final fitting curve according to the difference between the first Ct value and the second Ct value includes: comparing the difference between the first Ct value and the second Ct value with a preset difference threshold; If the difference is less than the preset difference threshold, the fitted PCR curve is directly used as the final PCR curve; If the difference is not less than the preset difference threshold, the original PCR curve is refitted until the difference between the first Ct value and the second Ct value corresponding to the fitted PCR curve is less than the preset difference threshold, thereby obtaining a final fitting curve.

9. A PCR curve fitting device, characterized in that: include: A PCR curve acquisition module is used to acquire an original PCR curve and determine a background period of the original PCR curve; A first Ct value determination module is used to pre-process the original PCR curve when it is determined according to the fluorescence value of the background period that the original PCR curve has an amplification phenomenon, and calculate a first Ct value corresponding to the pre-processed original PCR curve; A second Ct value determination module is used to determine the exponential growth period, linear growth area and plateau period of the original PCR curve based on the fluorescence value of the background period, and to perform curve fitting using the data points of the background period, exponential growth period, linear growth area and plateau period, and to calculate a second Ct value corresponding to the fitted PCR curve; A fitting curve determination module, used to determine a final fitting curve according to the difference between the first Ct value and the second Ct value; The second Ct value determination module uses the data points of the background period, exponential growth period, linear growth area and plateau period to perform curve fitting, including: Determine the center point value of the original PCR curve according to the data points of the background period, exponential growth period, linear growth area and plateau period; The minimum fluorescence value of the background period is used as the background fluorescence intensity value of the original PCR curve; Calculate the steepness value of the exponential growth period, the steepness value of the linear growth area, and the maximum fluorescence intensity value of the plateau period according to the center point value and the background fluorescence intensity value; The center point value, the background fluorescence intensity value, the steepness value of the exponential growth phase, the steepness value of the linear growth region, and the maximum fluorescence intensity value of the plateau phase are input into the Richard function to fit the original PCR curve.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the PCR curve fitting method as described in any one of claims 1 to 8.

11. A computer device, characterized in that: include: one or more processors, and memory; The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the PCR curve fitting method according to any one of claims 1 to 8 are performed.

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