QPCR curve fluorescence threshold detection method and device and electronic equipment

Abstract

The invention discloses a qPCR curve fluorescence threshold detection method and device and electronic equipment, and relates to the technical field of biological detection and the technical field of computers, and the method comprises the following steps: obtaining curve data of a to-be-detected qPCR curve; according to a plurality of background period cycles included in the background period of the qPCR curve, calculating an average value of fluorescence values of the plurality of background period cycles; for each cycle in the plurality of cycles, calculating a difference value obtained by subtracting the average value from the fluorescence value of the cycle; calculating a natural logarithm of the adjusted fluorescence value of the cycle as a fluorescence logarithm value of the cycle; analyzing the logarithmic curve based on curve characteristics of a background period, an index growth period and a linear growth period of a standard qPCR curve; and calculating a fluorescence threshold value of the qPCR curve based on fluorescence logarithmic values of a plurality of exponential growth period cycles in the logarithmic curve. By adopting the scheme, the accuracy of determining the fluorescence threshold of the qPCR curve and the detection efficiency are improved.

Description

Technical Field

[0001] This application relates to the fields of biological detection technology and computer technology, and particularly relates to a method, device, and electronic device for detecting the fluorescence threshold of a qPCR curve. Background Art

[0002] qPCR, that is, quantitative fluorescence PCR, is a method that uses the change of fluorescence signals to detect the change of the amount of amplification products in each cycle of PCR amplification in real time and perform quantitative analysis. As Figure 1 shown in the figure, the qPCR curve (which can also be called the qPCR amplification curve) reflects the change of the corresponding fluorescence signal as the qPCR reaction progresses. In the qPCR curve, the horizontal axis data is the number of cycles. During the qPCR detection process, from the reagent temperature rising to a preset higher value to dropping to a preset lower value is one cycle. When the reagent temperature drops to the preset lower value, the fluorescence value of the reagent is collected as the fluorescence value of this cycle, that is, the vertical axis data in the qPCR curve.

[0003] As Figure 1 shown, the standard qPCR amplification curve presents an "S" shape, with a characteristic shape: first is the background signal (i.e., the background period, also called the baseline period), and then there are three growth stages (exponential growth period, linear growth period, and plateau period).

[0004] When performing quantitative analysis on the qPCR curve, it is first necessary to determine the background period and the exponential growth period, and based on the background period and the exponential growth period, determine the threshold (Threshhold) of the qPCR curve, which can also be called the fluorescence threshold, and then calculate the Ct (threshold cycle number, Threshold Cycle) value of the qPCR curve according to the fluorescence threshold.

[0005] Currently, there is no unified method for automatically determining the fluorescence threshold and Ct value in the qPCR curve quantitative analysis technology. Existing technologies have different performances in terms of detection speed, detection scenarios, and whether human assistance is required.

[0006] Currently, for the fluorescence threshold and Ct value of the qPCR curve, based on experience, 10 times the standard deviation of the fluorescence values of multiple cycles included in the background period can be determined as the fluorescence threshold, and the straight line passing through this fluorescence threshold and parallel to the X-axis is used as the threshold line. It is also possible to manually observe the exponential growth period of the qPCR curve. In the exponential growth period, at the position where it is just possible to clearly see the obvious increase in the fluorescence value, a straight line parallel to the X-axis is drawn as the threshold line. After determining the threshold line, further, the Ct value of the qPCR curve can be determined.

[0007] However, in practical applications, the fluorescence threshold and Ct value determined based on experience are often not accurate enough, and the efficiency is low when determined by manual observation.

[0008] Therefore, in the prior art, there are problems that the fluorescence threshold and Ct value of the determined qPCR curve are not accurate enough, and the efficiency is low. Summary of the Invention

[0009] Embodiments of the present application provide a method, device and electronic device for detecting the fluorescence threshold of a qPCR curve, so as to solve the problems in the prior art that the fluorescence threshold of the determined qPCR curve is not accurate enough and the efficiency is low.

[0010] Embodiments of the present application provide a method for detecting the fluorescence threshold of a qPCR curve, including:

[0011] Obtain the curve data of the qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle;

[0012] Calculate the average value of the fluorescence values of the plurality of background period cycles included in the background period of the qPCR curve;

[0013] For each cycle in the plurality of cycles, calculate the difference between the fluorescence value of this cycle and the average value as the adjusted fluorescence value of this cycle;

[0014] For each cycle in the plurality of cycles, calculate the natural logarithm of the adjusted fluorescence value of this cycle as the fluorescence logarithm value of this cycle. If the adjusted fluorescence value of a cycle is not greater than 0, then the fluorescence logarithm value of this cycle does not exist. The plurality of cycles and the fluorescence logarithm values of the plurality of cycles represent the logarithmic curve corresponding to the qPCR curve;

[0015] Based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve, analyze the logarithmic curve to obtain a plurality of exponential growth period cycles included in the exponential growth period of the qPCR curve;

[0016] Based on the fluorescence logarithm values of the plurality of exponential growth period cycles in the logarithmic curve, calculate the fluorescence threshold of the qPCR curve.

[0017] Further, it further includes:

[0018] Based on the adjusted fluorescence value and fluorescence threshold of the qPCR curve, calculate the Ct value of the qPCR curve.

[0019] Further, analyzing the logarithmic curve based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve includes:

[0020] From the logarithmic curve, find the initial growth stage. The initial growth stage is the longest continuous cycle stage starting from the first cycle after the background period of the qPCR curve. Each cycle included in the longest continuous cycle stage has a fluorescence logarithmic value, and the fluorescence logarithmic values are all greater than 0. Moreover, the previous cycle and the next cycle of the longest continuous cycle stage do not have fluorescence logarithmic values or the fluorescence logarithmic values are not greater than 0;

[0021] Based on the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage, exclude the stages corresponding to the linear growth period and the plateau period of the qPCR curve from the initial growth stage to obtain the initial exponential growth stage;

[0022] By optimizing the initial exponential growth stage, determine the exponential growth stage from it. The multiple cycles included in the exponential growth stage are the multiple exponential growth period cycles included in the exponential growth period of the qPCR curve.

[0023] Further, based on the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage, excluding the stages corresponding to the linear growth period and the plateau period of the qPCR curve from the initial growth stage includes:

[0024] Calculate the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage;

[0025] Starting from the first cycle included in the initial growth stage, when the growth rate of the fluorescence logarithmic values of a continuous preset number of cycles is less than the preset growth rate threshold, exclude this continuous preset number of cycles and the cycles after them from the initial growth stage.

[0026] Further, the method of determining the exponential growth stage by optimizing the initial exponential growth stage includes:

[0027] Starting from the first cycle included in the initial exponential growth stage, for each cycle in turn, determine whether the fluorescence logarithmic value of this cycle is not greater than the fluorescence logarithmic value of the next cycle. If it is not greater, it means that this cycle and its next cycle are in the same growth trend stage. If it is less, it means that the growth trend stage ends at this cycle;

[0028] Determine the number of cycles included in the longest growth trend stage from the various growth trend stages included in the initial exponential growth stage;

[0029] If the quantity is not less than the preset phase value threshold, determine the quantity as the longest growth trend phase value; otherwise, determine the preset phase value threshold as the longest growth trend phase value;

[0030] For multiple phase values included in the range from the preset phase value threshold to the longest growth trend phase value, determine, from the growth phases respectively represented by the multiple phase values, the phase value corresponding to the growth phase with the smallest fluctuation as the optimal longest rising interval length;

[0031] Based on the optimal longest rising period phase represented by the optimal longest rising interval length, determine the exponential growth phase, where the optimal longest rising period phase is the phase represented by adding 1 cycle to the optimal longest rising interval length starting from the first cycle after the background period.

[0032] The embodiments of the present application further provide a qPCR curve background period detection device, including:

[0033] A data acquisition module, configured to acquire curve data of a qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle;

[0034] An average value calculation module, configured to calculate the average value of the fluorescence values of the plurality of background period cycles included in the background period of the qPCR curve;

[0035] A fluorescence value adjustment module, configured to calculate, for each cycle in the plurality of cycles, the difference between the fluorescence value of the cycle and the average value as the adjusted fluorescence value of the cycle;

[0036] A logarithm calculation module, configured to calculate, for each cycle in the plurality of cycles, the natural logarithm of the adjusted fluorescence value of the cycle as the fluorescence logarithm value of the cycle, where if the adjusted fluorescence value of a cycle is not greater than 0, the fluorescence logarithm value of the cycle does not exist, and the plurality of cycles and the fluorescence logarithm values of the plurality of cycles represent the logarithmic curve corresponding to the qPCR curve;

[0037] A logarithmic curve analysis module, configured to analyze the logarithmic curve based on the curve characteristics of the background period, exponential growth period, and linear growth period of a standard qPCR curve to obtain a plurality of exponential growth period cycles included in the exponential growth period of the qPCR curve;

[0038] A fluorescence threshold calculation module, configured to calculate the fluorescence threshold of the qPCR curve based on the fluorescence logarithm values of the plurality of exponential growth period cycles in the logarithmic curve.

[0039] An embodiment of the present application further provides an electronic device, including a processor and a machine-readable storage medium. The machine-readable storage medium stores machine-executable instructions that can be executed by the processor, and the processor is urged by the machine-executable instructions to implement the qPCR curve fluorescence threshold detection method described in any one of the above.

[0040] An embodiment of the present application further provides a computer-readable storage medium. A computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the qPCR curve fluorescence threshold detection method described in any one of the above is implemented.

[0041] An embodiment of the present application further provides a computer program product containing instructions. When it runs on a computer, it causes the computer to execute the qPCR curve fluorescence threshold detection method described in any one of the above.

[0042] The beneficial effects of the present application include:

[0043] In the method provided by the embodiment of the present application, for the qPCR curve to be detected, first, based on the average value of the fluorescence values of multiple cycles included in the background period, the fluorescence values of the qPCR curve are adjusted to obtain adjusted fluorescence values, and then the natural logarithm of the adjusted fluorescence values is calculated to obtain the logarithm of the fluorescence, so as to obtain the logarithmic curve corresponding to the qPCR curve. Then, based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve, the logarithmic curve is analyzed to determine the exponential growth period of the qPCR curve. Thus, based on the logarithm of the fluorescence values of each cycle included in the exponential growth period in the logarithmic curve, the fluorescence threshold of the qPCR curve is calculated. Compared with the prior art, after adjusting the fluorescence values of the qPCR curve and taking the natural logarithm to obtain the logarithmic curve, the exponential growth period can be determined more accurately based on the curve characteristics of the standard qPCR curve, and then the fluorescence threshold can be determined more accurately. Moreover, automatic detection of the fluorescence threshold can be realized, improving the detection efficiency.

[0044] Other features and advantages of the present application will be described in the following specification, and, in part, will become obvious from the specification, or will be understood by implementing the present application. The objectives and other advantages of the present application can be achieved and obtained by the structures specifically pointed out in the written specification, claims, and drawings. Description of the Drawings

[0045] The drawings are used to provide a further understanding of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation to the present application. In the drawings:

[0046] Figure 1 It is a schematic diagram of a standard qPCR curve;

[0047] Figure 2 Flow chart of the qPCR curve fluorescence threshold detection method provided by the embodiment of the present application;

[0048] Figure 3 Flow chart of the qPCR curve fluorescence threshold detection method provided by Embodiment 1 of the present application;

[0049] Figure 4 Flow chart of determining the stage value corresponding to the growth stage with the smallest fluctuation in Embodiment 1 of the present application;

[0050] Figure 5 Flow chart of the qPCR curve background period detection method provided by the embodiment of the present application;

[0051] Figure 6 Flow chart of the qPCR curve background period detection method provided by Embodiment 2 of the present application;

[0052] Figure 7 Flow chart of the qPCR curve background period detection method provided by Embodiment 3 of the present application;

[0053] Figure 8 Structural schematic diagram of the qPCR curve fluorescence threshold detection device provided by the embodiment of the present application;

[0054] Figure 9 Structural schematic diagram of the qPCR curve fluorescence threshold detection device provided by another embodiment of the present application;

[0055] Figure 10 Structural schematic diagram of the electronic device provided by the embodiment of the present application. Detailed implementation manners

[0056] In order to provide a solution for improving the accuracy of determining the fluorescence threshold of the qPCR curve and the detection efficiency, the embodiment of the present application provides a qPCR curve fluorescence threshold detection method, device and electronic device. The following describes the preferred embodiments of the present application with reference to the accompanying drawings of the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application, and are not used to limit the present application. And without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0057] The embodiment of the present application provides a qPCR curve fluorescence threshold detection method, as Figure 2 shown, including:

[0058] Step 21, obtain the curve data of the qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle;

[0059] Step 22: Calculate the average of the fluorescence values of the multiple background period cycles included in the background period of the qPCR curve;

[0060] Step 23: For each cycle in the multiple cycles, calculate the difference between the fluorescence value of this cycle and the average value as the adjusted fluorescence value of this cycle;

[0061] Step 24: For each cycle in the multiple cycles, calculate the natural logarithm of the adjusted fluorescence value of this cycle as the fluorescence logarithm value of this cycle. If the adjusted fluorescence value of a cycle is not greater than 0, then the fluorescence logarithm value of this cycle does not exist. The multiple cycles and the fluorescence logarithm values of the multiple cycles represent the logarithmic curve corresponding to the qPCR curve;

[0062] Step 25: Based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve, analyze this logarithmic curve to obtain the multiple exponential growth period cycles included in the exponential growth period of the qPCR curve;

[0063] Step 26: Calculate the fluorescence threshold of the qPCR curve based on the fluorescence logarithm values of the multiple exponential growth period cycles in this logarithmic curve.

[0064] In the above qPCR curve fluorescence threshold detection method provided by the embodiments of the present application, after adjusting the fluorescence value of the qPCR curve and taking the natural logarithm to obtain the logarithmic curve, the more accurate exponential growth period can be determined based on the curve characteristics of the standard qPCR curve, and then the more accurate fluorescence threshold can be determined. Moreover, the automatic detection of the fluorescence threshold can be realized, improving the detection efficiency.

[0065] Furthermore, in the embodiments of the present application, the Ct value of the qPCR curve can also be calculated based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve. Thus, a more accurate Ct value can be determined, and the automatic detection of the Ct value is realized, improving the detection efficiency.

[0066] The method and device provided by the present application will be described in detail below with specific embodiments in conjunction with the accompanying drawings.

[0067] Embodiment 1:

[0068] Embodiment 1 of the present application provides a qPCR curve fluorescence threshold detection method, as Figure 3 shown, including:

[0069] Step 301: Obtain the curve data of the qPCR curve to be detected. The curve data includes multiple consecutive cycles included in the qPCR curve and the fluorescence value of each cycle.

[0070] Step 302: Calculate the average value of the fluorescence values of the multiple background period cycles included in the background period of the qPCR curve.

[0071] In Embodiment 1 of the present application, the background period of the qPCR curve can be determined based on various feasible methods or based on empirical values. For example, set the multiple cycles included in the background period as the 3rd - 15th cycles. For the convenience of description, the cycles included in the background period are called background period cycles.

[0072] Step 303: For each cycle in the multiple cycles of the qPCR curve, calculate the difference between the fluorescence value of this cycle and the average value as the adjusted fluorescence value of this cycle.

[0073] In this step, the following formula can be used for calculation:

[0074] FA_A(i) = FA(i) - AVG;

[0075] where FA(i) is the fluorescence value of the i-th cycle, AVG is the average value of the fluorescence values of the multiple background period cycles, and FA_A(i) is the adjusted fluorescence value of the i-th cycle.

[0076] Step 304: For each cycle in the multiple cycles of the qPCR curve, calculate the natural logarithm of the adjusted fluorescence value of this cycle as the logarithmic fluorescence value of this cycle. If the adjusted fluorescence value of a cycle is not greater than 0, then the logarithmic fluorescence value of this cycle does not exist. The multiple cycles and the multiple logarithmic fluorescence values represent the logarithmic curve corresponding to the qPCR curve.

[0077] In this step, the following formula can be used for calculation:

[0078] Ln(i) = ln FA(i);

[0079] where Ln(i) is the logarithmic fluorescence value of the i-th cycle.

[0080] For each cycle, since there are cycles with adjusted fluorescence values not greater than 0, the logarithmic fluorescence values of these cycles do not exist. Therefore, the logarithmic curve corresponding to the qPCR curve represented is a segmented curve. From the dimension of the multiple cycles, it can be understood as a discontinuous curve, which is convenient for subsequently determining the exponential growth phase based on this logarithmic curve.

[0081] Step 305: Search for the initial growth stage from the logarithmic curve.

[0082] In this step, the initial growth stage is the longest continuous cycle stage starting from the first cycle after the background period of the qPCR curve. Each cycle included in the longest continuous cycle stage has a logarithmic fluorescence value, and the logarithmic fluorescence value is greater than 0. Moreover, the previous cycle and the next cycle of the longest continuous cycle stage do not have a logarithmic fluorescence value or the logarithmic fluorescence value is not greater than 0.

[0083] In the embodiments of the present application, the cycles included in the initial growth stage all satisfy the following relational expression:

[0084] Ln(i)>0.

[0085] Step 306: Based on the growth rate of the logarithmic fluorescence value of each cycle included in the initial growth stage, exclude the stages corresponding to the linear growth period and the plateau period of the qPCR curve from the initial growth stage to obtain the initial exponential growth stage.

[0086] In this step, first, the growth rate of the logarithmic fluorescence value of each cycle included in the initial growth stage can be calculated. For example, it is calculated using the following formula:

[0087] Δr(i)=(Ln(i)-Ln(i - 1)) / Ln(i - 1);

[0088] Among them, Δr(i) is the growth rate of the i-th cycle.

[0089] Then, starting from the first cycle included in the initial growth stage, when the growth rate of the logarithmic fluorescence value of a consecutive preset number of cycles is less than the preset growth rate threshold, exclude these consecutive preset number of cycles and the cycles after them from the initial growth stage;

[0090] In practical applications, the preset number and the preset growth rate threshold can be flexibly set according to the actual application needs. For example, the preset number can be 3, and the preset growth rate threshold can be 0.2.

[0091] Step 307: Starting from the first cycle included in the initial exponential growth stage, for each cycle in turn, determine whether the logarithmic fluorescence value of this cycle is not greater than the logarithmic fluorescence value of the next cycle. If it is not greater, it means that this cycle and its next cycle are in the same growth trend stage. If it is less, it means that the growth trend stage ends at this cycle.

[0092] Two adjacent cycles in the same growth trend stage satisfy the following relational expression:

[0093] Ln(i + 1)≥Ln(i).

[0094] In the embodiments of the present application, in each growth trend stage, the logarithmic fluorescence values of the cycles all show an increasing trend.

[0095] Step 308: Determine the number of cycles included in the cycle of the longest growth trend stage from each growth trend stage included in the initial exponential growth stage.

[0096] In this step, the longest growth trend stage is the growth trend stage with the largest number of included cycles.

[0097] Step 309: If this number is not less than the preset stage value threshold, determine this number as the longest growth trend stage value; otherwise, determine the preset stage value threshold as the longest growth trend stage value.

[0098] In the embodiments of the present application, the longest growth trend stage value is represented by maxLen.

[0099] In practical applications, the preset stage value threshold can be flexibly set according to needs. For example, it can be set to 5.

[0100] Step 310: For multiple stage values included in the range from the preset stage value threshold to the longest growth trend stage value, determine the stage value corresponding to the growth stage with the smallest fluctuation from the growth stages represented by these multiple stage values as the optimal longest rising interval length.

[0101] Assume that the preset stage value threshold is 5 and the longest growth trend stage value is 10. Then the multiple stage values included in this range are 5, 6, 7, 8, 9, and 10 respectively.

[0102] The growth stage represented by a stage value is: starting from the first cycle after the background period of the qPCR curve, the stage represented by the consecutive number of cycles equal to this stage value.

[0103] For example, if the background period is the 3rd - 15th cycles and this stage value is 5, then the growth stage represented by this stage value is: the stage represented by the 16th - 20th cycles.

[0104] In the embodiments of the present application, as Figure 4 shown, specifically, the following steps can be used to determine the stage value corresponding to the growth stage with the smallest fluctuation, including:

[0105] Step 41: For each stage value among the multiple stage values included in the range from the preset stage value threshold to the longest growth trend stage value, calculate the mean fluorescence value of each cycle within the range of this stage value for the consecutive number of cycles starting from the first cycle after the background period of the qPCR curve, and obtain the first mean curve corresponding to this stage value;

[0106] Among them, the following formula is used to calculate the mean fluorescence value of the i-th cycle within the range of this stage value:

[0107] Sum(i) = FA_A(i) + FA_A(i + 1) + … + FA_A(i + len - 1);

[0108] FA_A_AVG(i) = Sum(k) / len;

[0109] Wherein, FA_A(i) is the adjusted fluorescence value of the i-th cycle in a number of consecutive cycles equal to the number of values in this stage, len is the value of this stage, and FA_A_AVG(i) is the average fluorescence value of the i-th cycle within the range of the value of this stage;

[0110] For example, if the value of this stage is 5, and the growth stage it represents is: the stage represented by the 16th - 20th cycles, then the values of i are 16, 17, 18, 19, and 20 respectively. That is to say, 5 average fluorescence values are obtained respectively. Correspondingly, the data of the first average value curve corresponding to the value of this stage includes: the 16th - 20th cycles, and the corresponding average fluorescence values respectively.

[0111] In this step, the first average value curve is represented by Line1.

[0112] Step 42: For each value of this stage, calculate the first derivative curve of the first average value curve corresponding to this stage value as the second average value curve corresponding to this stage value.

[0113] In this step, the second average value curve can be calculated using the following formula:

[0114] Line2(i) = Line1(i + 1) - Line1(i).

[0115] In this step, the second average value curve is represented by Line2.

[0116] Step 43: Calculate the second derivative curve of the first average value curve corresponding to this stage value as the third average value curve corresponding to this stage value.

[0117] In this step, the third average value curve can be calculated using the following formula:

[0118] Line3(i) = Line2(i + 1) - Line2(i).

[0119] In this step, the third average value curve is represented by Line3.

[0120] Through the above steps 41 - 43, for each value of this stage, a first average value curve, a second average value curve, and a third average value curve are obtained, totaling three average value curves.

[0121] Step 44: Calculate the volatility of the first average value curve, the second average value curve, and the third average value curve corresponding to this stage value.

[0122] In this step, for a mean curve, starting from its first cycle, if the value of a cycle on this mean curve is greater than the value of the next cycle on this mean curve, it is recorded as a fluctuation. The volatility of this mean curve is the number of recorded fluctuations divided by the stage value corresponding to this mean curve.

[0123] Step 45: Based on the volatilities of the first mean curve, the second mean curve, and the third mean curve corresponding to each stage value among the multiple stage values, determine the stage value corresponding to the curve with the minimum volatility as the optimal longest rising interval length.

[0124] In this step, the following method can be specifically used to determine the stage value corresponding to the curve with the minimum volatility:

[0125] First, select the first mean curve with the minimum volatility from the first mean curves corresponding to each stage value. If there is only one first mean curve, then the stage value corresponding to this first mean curve is used as the optimal longest rising interval length. If there are multiple first mean curves, obtain the stage values corresponding to these multiple first mean curves respectively as multiple candidate stage values.

[0126] Then, select the second mean curve with the minimum volatility from the second mean curves corresponding to these multiple candidate stage values. If there is only one second mean curve, then the stage value corresponding to this second mean curve is used as the optimal longest rising interval length. If there are multiple second mean curves, obtain the stage values corresponding to these multiple second mean curves respectively as the updated multiple candidate stage values.

[0127] Then, select the third mean curve with the minimum volatility from the third mean curves corresponding to the updated multiple candidate stage values. If there is only one third mean curve, then the stage value corresponding to this third mean curve is used as the optimal longest rising interval length. If there are multiple third mean curves, select any one of the stage values corresponding to these multiple third mean curves as the optimal longest rising interval length.

[0128] In the embodiment of this application, optimalLen is used to represent the optimal longest rising interval length.

[0129] Step 311: Determine the exponential growth stage based on the optimal longest rising period stage represented by the optimal longest rising interval length.

[0130] The optimal longest ascending period stage is the stage represented by adding 1 cycle to the length of the optimal longest ascending interval starting from the first cycle after the background period. That is to say, the optimal longest ascending period stage is from the first cycle after the background period of the qPCR curve to the optimal longest ascending interval length plus 1 cycle.

[0131] The range of cycles included in the optimal longest ascending period stage is [iStart, iStart + optimalLen], where iStart is the first cycle after the background period.

[0132] For example, if the background period is cycles 3 - 15 and the length of the optimal longest ascending interval is 5, then the cycles included in the optimal longest ascending period stage are: cycles 16 - 21, a total of 6 cycles.

[0133] In this step, specifically, first, the preset percentage of the difference between the adjusted fluorescence values of the last cycle and the first cycle of the optimal longest ascending period stage represented by the length of the optimal longest ascending interval can be calculated as the preset growth threshold.

[0134] In practical applications, this preset percentage can be flexibly set according to actual needs. For example, it can be set to 10%. Correspondingly, the calculation formula is as follows:

[0135] Δb = [FA_A(iStart + optimalLen) - FA_A(iStart)] * 10%;

[0136] Where Δb is the preset growth threshold.

[0137] Then, from each cycle included in the optimal longest ascending period stage, find the cycle whose last growth rate is greater than the preset growth threshold as the first cycle of the exponential growth stage, and the optimal longest ascending interval length plus 1 cycle starting from this first cycle as the last cycle of the exponential growth stage.

[0138] The cycle whose last growth rate is greater than the preset growth threshold can be represented by iOptStart as the first cycle of the exponential growth stage. The last cycle of the exponential growth stage is iOptStart + optimalLen, that is, the range of multiple exponential growth period cycles included in the exponential growth stage is [iStart, iStart + optimalLen], a total of optimalLen + 1 cycles.

[0139] Step 312: Calculate the fluorescence threshold of this qPCR curve based on the fluorescence logarithm values of multiple exponential growth period cycles in the logarithmic curve.

[0140] Specifically, the fluorescence threshold of this qPCR curve can be calculated using the following formula:

[0141] Ln(mean) = [Ln(iOptStart) + Ln(iOptStart + optimalLen)] * d;

[0142] Threshold = e Ln(mean) ;

[0143] Wherein, Ln(iOptStart) is the logarithm of fluorescence of the first cycle in multiple exponential growth phase cycles, Ln(iOptStart + optimalLen) is the logarithm of fluorescence of the last cycle in multiple exponential growth phase cycles, the value range of d can be [0.4, 0.6], and Threshold is the fluorescence threshold of the qPCR curve.

[0144] Step 313: Calculate the Ct value of the qPCR curve based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve.

[0145] Specifically, based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve, the Ct value of the qPCR curve can be calculated by using the method of simulating the exponential growth phase curve of this qPCR curve.

[0146] For example, linear simulation or exponential simulation can be used.

[0147] For linear simulation, the linear simulation equation of the exponential growth phase curve is: y = kx + b;

[0148] Correspondingly, the calculation process is as follows:

[0149] k = [FA_A(iOptStart + optimalLen) - FA_A(iOptStart)] / optimalLen;

[0150] Ct = iOptStart + (Threshold - FA_A(iOptStart)) / k.

[0151] For exponential simulation, the exponential simulation equation of the exponential growth phase curve is: y = ka x ;

[0152] Correspondingly, the calculation process is as follows:

[0153] a = e ln[FA_A(iOptStart+optimalLen) / FA_A(iOptStart)I / optimalLen ;

[0154] Ct = iOptStart + ln(Threshold / FA_A(iOptStart)) / lna;

[0155] By using the above-mentioned qPCR curve fluorescence threshold detection method provided in Embodiment 1 of the present application, the fluorescence values of the qPCR curve are adjusted and the natural logarithm is taken to obtain a logarithmic curve. Further, based on the curve characteristics of the standard qPCR curve, a more accurate exponential growth period can be determined, and then a more accurate fluorescence threshold and Ct value can be determined. Moreover, the automatic detection of the fluorescence threshold and Ct value can be realized, improving the detection efficiency.

[0156] In the above-mentioned qPCR curve fluorescence threshold detection method, it is first necessary to determine the background period of the qPCR curve. In the embodiments of the present application, the following method for determining the background period of the qPCR curve is proposed.

[0157] The embodiments of the present application provide a method for detecting the background period of a qPCR curve, as Figure 5 shown, including:

[0158] Step 51: Obtain the curve data of the qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle;

[0159] This step 51 is the same as the above step 21. After executing the above step 21, this step 51 does not need to be executed repeatedly.

[0160] Step 52: Calculate the average value of the fluorescence values of the multiple background period cycles included in the current background period, and the multiple background period cycles included in the initial background period are preset;

[0161] Step 53: Calculate the deviation degree of the fluorescence value of the last background period cycle of the current background period based on the average value;

[0162] Step 54: Determine whether the deviation degree meets the preset deviation degree judgment standard, and the deviation degree judgment standard is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve;

[0163] Step 55: If the deviation degree meets the preset deviation degree judgment standard, determine the background period of the qPCR curve based on the current background period. If the deviation degree does not meet the preset deviation degree judgment standard, adjust the current background period to obtain the updated current background period, and return to execute step 52.

[0164] In the above-mentioned method for detecting the background period of the qPCR curve provided by the embodiments of the present application, since the deviation degree judgment standard is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve, therefore, compared with the prior art, based on this deviation degree judgment standard, a more accurate background period can be detected, and the automatic detection of the background period can be realized, improving the detection efficiency.

[0165] Embodiment 2:

[0166] Embodiment 2 of the present application provides a method for detecting the background period of a qPCR curve, as Figure 6 shown, including:

[0167] Step 61, obtain the curve data of the qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle.

[0168] Step 62, calculate the average value of the fluorescence values of the plurality of background period cycles included in the current background period, and the plurality of background period cycles included in the initial background period are preset.

[0169] In Embodiment 2 of the present application, the plurality of cycles included in the initial background period can be preset as the 3rd - 15th cycles. For convenience of description, the cycles included in the background period are called background period cycles.

[0170] When this step is first executed, the current background period is the initial background period, that is, calculate the average value of the fluorescence values of the plurality of background period cycles included in the initial background period.

[0171] In Embodiment 2 of the present application, the current background period does not mean that the background period of the qPCR curve is changing, but during the process of detecting the background period of the qPCR curve, that is, during the continuous adjustment of the background period, as the current background period to be judged. For convenience of description, it is called the current background period.

[0172] Step 63, based on the average value, calculate the deviation degree of the fluorescence value of the last background period cycle of the current background period.

[0173] In this step, the absolute value of the difference between the fluorescence value of the last background period cycle of the current background period and the average value can be calculated as the deviation degree of the fluorescence value of the last background period cycle of the current background period, that is, it can be calculated using the following formula:

[0174] Flat(i) = |FA(i) - AVG|;

[0175] where i represents the last background period cycle of the current background period, FA(i) represents the fluorescence value of the last background period cycle of the current background period, AVG represents the average value of the fluorescence values of the plurality of background period cycles included in the current background period, and Flat(i) represents the deviation degree of the fluorescence value of the last background period cycle of the current background period.

[0176] Step 64, calculate the variance of the fluorescence values of the plurality of background period cycles included in the current background period.

[0177] There is no strict order between this step 64 and the above steps 62 - 63.

[0178] Step 65: Determine whether the above deviation is within the preset deviation threshold range.

[0179] If it is within the preset deviation threshold range, determine that the deviation meets the preset deviation judgment criterion, and execute Step 66;

[0180] If it is not within the preset deviation threshold range, determine that the deviation does not meet the preset deviation judgment criterion, and execute Step 67.

[0181] In Embodiment 2 of the present application, the preset deviation threshold range is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve.

[0182] From Figure 1 As can be seen from the ranges of the background period and the exponential growth period of the shown standard qPCR curve, from the background period to the exponential growth period, the fluorescence value will have a significant increase.

[0183] Furthermore, in Embodiment 1 of the present application, the preset deviation threshold range can be related to the variance of the fluorescence values of the multiple background period cycles included in the current background period determined in Step 64 above.

[0184] For example, the preset deviation threshold range is from the first preset multiple of the variance to the second preset multiple of the variance, and the first preset multiple is less than the second preset multiple.

[0185] In practical applications, the first preset multiple and the second preset multiple can be set to appropriate values based on the amplification performance of the instrument. If the amplification performance of the instrument is less sensitive, the values of the first preset multiple and the second preset multiple can be set relatively large. If the amplification performance of the instrument is more sensitive, the values of the first preset multiple and the second preset multiple can be set relatively small.

[0186] Specifically, in Embodiment 1 of the present application, the preset deviation threshold range can be set to 1.9 times the variance to 2 times the variance, or, set to 1.8 times the variance to 1.9 times the variance, or, set to 1.7 times the variance to 1.8 times the variance, or, set to 1.6 times the variance to 1.7 times the variance, or, set to 1.5 times the variance to 1.6 times the variance.

[0187] Step 66: If the deviation meets the preset deviation judgment criterion, determine that the current background period is the background period of the qPCR curve.

[0188] According to Step 65 above, if the deviation is within the preset deviation threshold range, it means that the last background period cycle of the current background period is at the junction of the background period and the exponential growth period. Therefore, the current background period can be determined as the background period of the qPCR curve.

[0189] Step 67: If the deviation does not meet the preset deviation judgment criterion, adjust the current background period to obtain an updated current background period, and return to execute the above Step 62 to continue determining whether the conditions for being a background period are met for the updated current background period.

[0190] In this step, if the deviation is greater than the variance of the second preset multiple, it indicates that the last cycle of the current background period is still within the exponential growth period range. Therefore, eliminate the last background period cycle from the multiple background period cycles included in the current background period to obtain an updated current background period. For example, if the multiple cycles included in the current background period are the 3rd - 15th cycles, then eliminate the 15th cycle, and the multiple cycles included in the updated current background period change to the 3rd - 14th cycles;

[0191] If the deviation is less than the variance of the first preset multiple, it indicates that the last cycle of the current background period has not yet reached the junction between the background period and the exponential growth period. Therefore, add the next cycle to the multiple background period cycles included in the current background period to obtain an updated current background period. For example, if the multiple cycles included in the current background period are the 3rd - 15th cycles, then add the next cycle, that is, the 16th cycle, and the multiple cycles included in the updated current background period change to the 3rd - 16th cycles.

[0192] Adopt the above Figure 6 qPCR curve background period detection method provided in Embodiment 2 of the present application. The preset deviation judgment criterion adopts a preset deviation threshold range, and this preset deviation threshold range is related to the variance of the fluorescence values of the multiple background period cycles included in the current background period and is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve. Therefore, it is possible to accurately find out the cycle located at the junction between the background period and the exponential growth period from multiple cycles as the last cycle of the background period to be detected for this qPCR curve. Compared with the prior art, a more accurate background period can be detected, and automatic detection of the background period can be achieved, improving the detection efficiency.

[0193] Embodiment 3:

[0194] Embodiment 3 of the present application provides a qPCR curve background period detection method, as Figure 7 shown, including:

[0195] Steps 701 - 704 are respectively the same as Steps 61 - 64 in Embodiment 2 above and will not be described repeatedly here.

[0196] Step 705: Determine whether the above deviation is not greater than the preset deviation threshold.

[0197] If it is greater than the preset deviation threshold, execute step 706.

[0198] If it is not greater than the preset deviation threshold, execute step 709.

[0199] In Embodiment 3 of the present application, the preset deviation threshold is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve.

[0200] From Figure 1 As can be seen from the ranges of the background period and the exponential growth period of the shown standard qPCR curve, from the background period to the exponential growth period, the fluorescence value will have an obvious increase.

[0201] Furthermore, in Embodiment 3 of the present application, the preset deviation threshold range can be related to the variance of the fluorescence values of multiple background period cycles included in the current background period determined in step 74 above.

[0202] For example, the preset deviation threshold is the third preset multiple of this variance.

[0203] In practical applications, for the third preset multiple, an appropriate value can be set based on the amplification performance of the instrument. If the amplification performance of the instrument is less sensitive, the value of the third preset multiple can be set relatively large. If the amplification performance of the instrument is more sensitive, the value of the third preset multiple can be set relatively small.

[0204] Specifically, in Embodiment 3 of the present application, the preset deviation threshold can be set to a value between 1.5 times the variance and 2 times the variance.

[0205] Step 706: Determine whether the deviation calculated for the previous current background period is not greater than the preset deviation threshold.

[0206] If it is not greater than the preset deviation threshold, execute step 707.

[0207] If it is greater than the preset deviation threshold, execute step 708.

[0208] Step 707: If the deviation calculated for the current background period is greater than the preset deviation threshold, and the deviation calculated for the previous current background period is not greater than the preset deviation threshold, it means that the last cycle of the current background period is exactly the first cycle from the background period to the exponential growth period. Therefore, it can be determined that the previous current background period is the background period of the qPCR curve.

[0209] Step 708. If the deviation calculated for the current background period is greater than the preset deviation threshold, and the deviation calculated for the previous current background period is greater than the preset deviation threshold, it indicates that the last cycle of the current background period is still within the exponential growth period range. Therefore, remove the last background period cycle from the multiple background period cycles included in the current background period to obtain the updated current background period, and return to execute the above Step 702 to continue determining whether the updated current background period meets the conditions for being a background period.

[0210] For example, if the multiple cycles included in the current background period are the 3rd - 15th cycles, then remove the 15th cycle, and the multiple cycles included in the updated current background period change to the 3rd - 14th cycles.

[0211] 709. Determine whether the deviation calculated for the previous current background period is not greater than the preset deviation threshold.

[0212] If it is not greater than the preset deviation threshold, execute Step 710.

[0213] If it is greater than the preset deviation threshold, execute Step 711.

[0214] Step 710. If the deviation calculated for the current background period is not greater than the preset deviation threshold, and the deviation calculated for the previous current background period is greater than the preset deviation threshold, it indicates that the last cycle of the current background period is exactly the last cycle of the background period. Therefore, determine that the current background period is the background period of the qPCR curve.

[0215] Step 711. If the deviation calculated for the current background period is not greater than the preset deviation threshold, and the deviation calculated for the previous current background period is not greater than the preset deviation threshold, it indicates that the last cycle of the current background period may not yet be at the junction of the background period and the exponential growth period. Therefore, add the next cycle to the multiple background period cycles included in the current background period to obtain the updated current background period, and return to execute the above Step 702 to continue determining whether the updated current background period meets the conditions for being a background period.

[0216] For example, if the multiple cycles included in the current background period are the 3rd - 15th cycles, then add the next cycle, that is, the 16th cycle, and the multiple cycles included in the updated current background period change to the 3rd - 16th cycles.

[0217] The above Figure 7The process shown is essentially to find a cycle from multiple cycles included in the qPCR curve to be detected, such that the deviation calculated for this cycle is not greater than a preset deviation threshold, and the deviation calculated for the next cycle of this cycle is greater than the preset deviation threshold. That is, this cycle is taken as the last cycle among the multiple cycles included in the background period, thereby determining the background period of the qPCR curve.

[0218] Using the above-mentioned Figure 7 qPCR curve background period detection method provided in Embodiment 3 of the present application, the preset deviation judgment criterion uses a preset deviation threshold, and this preset deviation threshold is related to the variance of the fluorescence values of multiple background period cycles included in the current background period, and is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve. Therefore, it is possible to accurately find a cycle located at the junction of the background period and the exponential growth period from multiple cycles as the last cycle of the background period of the qPCR curve to be detected. Compared with the prior art, a more accurate background period can be detected, and moreover, automatic detection of the background period can be achieved, improving the detection efficiency.

[0219] Based on the same inventive concept, according to the qPCR curve background period detection method provided in the above embodiments of the present application, correspondingly, another embodiment of the present application further provides a qPCR curve background period detection device, and its structural schematic diagram is as Figure 8 shown, specifically including:

[0220] A data acquisition module 801, configured to acquire curve data of the qPCR curve to be detected, where the curve data includes multiple consecutive cycles included in the qPCR curve and the fluorescence value of each cycle;

[0221] An average value calculation module 802, configured to calculate the average value of the fluorescence values of multiple background period cycles included in the background period of the qPCR curve;

[0222] A fluorescence value adjustment module 803, configured to calculate, for each cycle among the multiple cycles, the difference between the fluorescence value of this cycle and the average value as the adjusted fluorescence value of this cycle;

[0223] A logarithm calculation module 804, configured to calculate, for each cycle among the multiple cycles, the natural logarithm of the adjusted fluorescence value of this cycle as the fluorescence logarithm value of this cycle. Wherein, if the adjusted fluorescence value of a cycle is not greater than 0, the fluorescence logarithm value of this cycle does not exist. The multiple cycles and the fluorescence logarithm values of the multiple cycles represent the logarithmic curve corresponding to the qPCR curve;

[0224] The logarithmic curve analysis module 805 is configured to analyze the logarithmic curve based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve, and obtain multiple exponential growth period cycles included in the exponential growth period of the qPCR curve;

[0225] The fluorescence threshold calculation module 806 is configured to calculate the fluorescence threshold of the qPCR curve based on the fluorescence logarithmic values of the multiple exponential growth period cycles in the logarithmic curve.

[0226] Further, as Figure 9 shown, it further includes:

[0227] The Ct value calculation module 807 is configured to calculate the Ct value of the qPCR curve based on the adjusted fluorescence value and fluorescence threshold of the qPCR curve.

[0228] Further, the logarithmic curve analysis module 805 is specifically configured to find the initial growth stage from the logarithmic curve. The initial growth stage is the longest continuous cycle stage starting from the first cycle after the background period of the qPCR curve. Each cycle included in the longest continuous cycle stage has a fluorescence logarithmic value, and the fluorescence logarithmic values are all greater than 0, and the previous cycle and the next cycle of the longest continuous cycle stage do not have a fluorescence logarithmic value or the fluorescence logarithmic value is not greater than 0;

[0229] Based on the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage, the stages corresponding to the linear growth period and the plateau period of the qPCR curve are removed from the initial growth stage to obtain the initial exponential growth stage;

[0230] By optimizing the initial exponential growth stage, the exponential growth stage is determined therefrom. The multiple cycles included in the exponential growth stage are the multiple exponential growth period cycles included in the exponential growth period of the qPCR curve.

[0231] Further, the logarithmic curve analysis module 805 is specifically configured to calculate the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage; starting from the first cycle included in the initial growth stage, when the growth rate of the fluorescence logarithmic values of a continuous preset number of cycles is less than the preset growth rate threshold, the continuous preset number of cycles and the cycles after them are removed from the initial growth stage.

[0232] Further, the logarithmic curve analysis module 805 is specifically configured to start from the first cycle included in the initial exponential growth stage, and for each cycle in turn, determine whether the logarithm value of the fluorescence of this cycle is not greater than the logarithm value of the fluorescence of the next cycle. If it is not greater, it indicates that this cycle and its next cycle are in the same growth trend stage. If it is less, it indicates that the growth trend stage ends at this cycle;

[0233] Determine the number of cycles included in the longest growth trend stage from each growth trend stage included in the initial exponential growth stage;

[0234] If this number is not less than the preset stage value threshold, determine this number as the longest growth trend stage value. Otherwise, determine the preset stage value threshold as the longest growth trend stage value;

[0235] For multiple stage values included in the range from the preset stage value threshold to the longest growth trend stage value, determine the stage value corresponding to the growth stage with the smallest fluctuation from the growth stages represented by these multiple stage values as the optimal longest rising interval length;

[0236] Based on the optimal longest rising period stage represented by the optimal longest rising interval length, determine the exponential growth stage. The optimal longest rising period stage is the stage represented by the optimal longest rising interval length plus 1 cycle starting from the first cycle after the background period.

[0237] Further, the logarithmic curve analysis module 805 is specifically configured to, for each stage value among the multiple stage values included in the range from the preset stage value threshold to the longest growth trend stage value, calculate the average fluorescence value of each cycle in the continuous number of cycles equal to this stage value starting from the first cycle after the background period of the qPCR curve within this stage value range, and obtain the first average value curve corresponding to this stage value;

[0238] Among them, the following formula is used to calculate the average fluorescence value of the i-th cycle within this stage value range:

[0239] Sum(i) = FA_A(i) + FA_A(i + 1) + … + FA_A(i + len - 1);

[0240] FA_A_AVG(i) = Sum(k) / len;

[0241] Among them, FA_A(i) is the adjusted fluorescence value of the i-th cycle in the continuous number of cycles equal to this stage value, len is this stage value, and FA_A_AVG(i) is the average fluorescence value of the i-th cycle within this stage value range;

[0242] Calculate the first derivative curve of the first mean curve corresponding to the value of this stage as the second mean curve corresponding to the value of this stage;

[0243] Calculate the second derivative curve of the first mean curve corresponding to the value of this stage as the third mean curve corresponding to the value of this stage;

[0244] Calculate the volatilities of the first mean curve, the second mean curve, and the third mean curve corresponding to the value of this stage;

[0245] Based on the volatilities of the first mean curve, the second mean curve, and the third mean curve corresponding to each stage value among the multiple stage values, determine the stage value corresponding to the curve with the smallest volatility as the optimal longest rising interval length.

[0246] Further, the logarithmic curve analysis module 805 is specifically configured to calculate a preset percentage of the difference between the adjusted fluorescence values of the last cycle and the first cycle of the optimal longest rising period stage represented by the optimal longest rising interval length as the preset growth threshold, where the optimal longest rising period stage is from the first cycle after the background period of the qPCR curve to the optimal longest rising interval length plus 1 cycle;

[0247] Among the cycles included in the optimal longest rising period stage, find the cycle with the last growth rate greater than the preset growth threshold as the first cycle of the exponential growth stage, and the optimal longest rising interval length plus 1 cycle starting from this first cycle as the last cycle of the exponential growth stage.

[0248] Further, the fluorescence threshold calculation module 806 is specifically configured to calculate the fluorescence threshold of the qPCR curve using the following formula:

[0249] Ln(mean) = [Ln(iOptStart) + Ln(iOptStart + optimalLen)] * d;

[0250] Threshold = e Ln(mean) ;

[0251] where Ln(iOptStart) is the logarithm of the fluorescence value of the first cycle among the multiple exponential growth period cycles, Ln(iOptStart + optimalLen) is the logarithm of the fluorescence value of the last cycle among the multiple exponential growth period cycles, the value range of d is [0.4, 0.6], and Threshold is the fluorescence threshold of the qPCR curve.

[0252] Further, the Ct value calculation module 807 is specifically configured to calculate the Ct value of the qPCR curve by using a method of simulating an exponential growth phase curve of the qPCR curve based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve.

[0253] Further, the average value calculation module 802 is further configured to calculate the average value of the fluorescence values of multiple background period cycles included in the current background period of the qPCR curve in a loop, and the multiple background period cycles included in the initial background period are preset;

[0254] As Figure 9 shown, it further includes:

[0255] The deviation calculation module 808 is configured to calculate the deviation of the fluorescence value of the last background period cycle of the current background period based on the average value;

[0256] The deviation judgment module 809 is configured to determine whether the deviation meets a preset deviation judgment criterion, and the deviation judgment criterion is determined based on the curve characteristics of the background period and the exponential growth period of the standard qPCR curve;

[0257] The background period adjustment module 810 is configured to, if the deviation meets the preset deviation judgment criterion, determine the background period of the qPCR curve based on the current background period; if the deviation does not meet the preset deviation judgment criterion, adjust the current background period to obtain an updated current background period, and return to trigger the average value calculation module 802 to execute the step of calculating the average value of the fluorescence values of multiple background period cycles included in the current background period of the qPCR curve.

[0258] Further, the deviation calculation module 808 is specifically configured to calculate the absolute value of the difference between the fluorescence value of the last background period cycle of the current background period and the average value as the deviation of the fluorescence value of the last background period cycle of the current background period.

[0259] Further, the deviation judgment module 809 is specifically configured to determine whether the deviation is within a preset deviation threshold range; if it is within the preset deviation threshold range, determine that the deviation meets the preset deviation judgment criterion; if it is not within the preset deviation threshold range, determine that the deviation does not meet the preset deviation judgment criterion.

[0260] Further, the average value calculation module 802 is further configured to calculate the variance of the fluorescence values of the multiple background period cycles included in the current background period according to the multiple background period cycles included in the current background period; the preset deviation threshold range is the variance of the first preset multiple to the variance of the second preset multiple, and the first preset multiple is less than the second preset multiple.

[0261] Further, the background period adjustment module 810 is specifically configured to, if the deviation meets the preset deviation judgment criterion, determine the current background period as the background period of the qPCR curve; if the deviation is greater than the variance of the second preset multiple, remove the last background period cycle from the multiple background period cycles included in the current background period to obtain an updated current background period; if the deviation is less than the variance of the first preset multiple, add the next cycle to the multiple background period cycles included in the current background period to obtain an updated current background period.

[0262] Further, the deviation judgment module 809 is specifically configured to determine whether the deviation is not greater than the preset deviation threshold.

[0263] The background period adjustment module 810 is specifically configured to, if the deviation is greater than the preset deviation threshold and the deviation calculated for the previous current background period is not greater than the preset deviation threshold, determine the previous current background period as the background period of the qPCR curve; if the deviation is greater than the preset deviation threshold and the deviation calculated for the previous current background period is greater than the preset deviation threshold, remove the last background period cycle from the multiple background period cycles included in the current background period to obtain an updated current background period; if the deviation is not greater than the preset deviation threshold and the deviation calculated for the previous current background period is greater than the preset deviation threshold, determine the current background period as the background period of the qPCR curve; if the deviation is not greater than the preset deviation threshold and the deviation calculated for the previous current background period is not greater than the preset deviation threshold, add the next cycle to the multiple background period cycles included in the current background period to obtain an updated current background period.

[0264] Further, the average value calculation module 802 is further configured to calculate the variance of the fluorescence values of the multiple background period cycles included in the current background period according to the multiple background period cycles included in the current background period; the preset deviation threshold is the variance of the third preset multiple.

[0265] Further, the third preset multiple is a value between 1.5 times and 2 times.

[0266] The functions of the above modules can correspond to Figures 2 to 7 the corresponding processing steps in the shown process, which will not be elaborated here.

[0267] The qPCR curve background period detection device provided by the embodiments of the present application can be implemented through a computer program. Those skilled in the art should be able to understand that the above module division method is only one of many module division methods. If it is divided into other modules or not divided into modules, as long as the qPCR curve background period detection device has the above functions, it should be within the protection scope of the present application.

[0268] The embodiments of the present application also provide an electronic device, as Figure 10 shown, including a processor 101 and a machine-readable storage medium 102. The machine-readable storage medium 102 stores machine-executable instructions that can be executed by the processor 101. The processor 101 is prompted by the machine-executable instructions to implement any one of the above-mentioned qPCR curve fluorescence threshold detection methods.

[0269] The embodiments of the present application also provide a computer-readable storage medium. The computer program stored in the computer-readable storage medium implements any one of the above-mentioned qPCR curve fluorescence threshold detection methods when executed by a processor.

[0270] The embodiments of the present application also provide a computer program product containing instructions. When it runs on a computer, it causes the computer to execute any one of the above-mentioned qPCR curve fluorescence threshold detection methods.

[0271] The machine-readable storage medium in the above electronic device may include a random access memory (Random Access Memory, RAM), or may also include a non-volatile memory (Non-Volatile Memory, NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0272] The above-mentioned processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; it may also be a digital signal processor (Digital Signal Processing, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0273] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are mainly described. In particular, for the embodiments of devices, electronic devices, computer-readable storage media, and computer program products, since they are basically similar to the method embodiments, the description is relatively simple, and reference can be made to the corresponding parts of the method embodiments for the relevant content.

[0274] It should be noted that, in this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0275] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more of the flows Figure 1 or one or more of the blocks.

[0276] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that realizes the functions specified in Figure 1 one or more of the flows Figure 1 or one or more of the blocks.

[0277] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are executed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the steps specified in one process or a plurality of processes and / or blocks Figure 1 one process or a plurality of processes and / or blocks Figure 1 in one block or a plurality of blocks.

[0278] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations therein.

Claims

1. A method for detecting the fluorescence threshold of a qPCR curve, characterized in that, Including: Obtain the curve data of the qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle; Calculate the average value of the fluorescence values of the multiple background period cycles included in the background period of the qPCR curve; For each cycle in the multiple cycles, calculate the difference between the fluorescence value of this cycle and the average value as the adjusted fluorescence value of this cycle; For each cycle in the multiple cycles, calculate the natural logarithm of the adjusted fluorescence value of this cycle as the logarithm value of the fluorescence of this cycle. If the adjusted fluorescence value of a cycle is not greater than 0, then the logarithm value of the fluorescence of this cycle does not exist. The multiple cycles and the logarithm values of the fluorescence of the multiple cycles represent the logarithmic curve corresponding to the qPCR curve; Based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve, analyze the logarithmic curve to obtain multiple exponential growth period cycles included in the exponential growth period of the qPCR curve; Based on the logarithm values of the fluorescence of the multiple exponential growth period cycles in the logarithmic curve, calculate the fluorescence threshold of the qPCR curve.

2. The method according to claim 1, characterized in that Also including: Based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve, calculate the Ct value of the qPCR curve.

3. The method according to claim 1, characterized in that, The analyzing the logarithmic curve based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve includes: Search for the initial growth stage from the logarithmic curve. The initial growth stage is the longest continuous cycle stage starting from the first cycle after the background period of the qPCR curve. Each cycle included in the longest continuous cycle stage has a logarithm value of the fluorescence, and the logarithm values of the fluorescence are all greater than 0, and the previous cycle and the next cycle of the longest continuous cycle stage do not have a logarithm value of the fluorescence or the logarithm value of the fluorescence is not greater than 0; Based on the growth rate of the logarithm values of the fluorescence of each cycle included in the initial growth stage, exclude the stages corresponding to the linear growth period and the plateau period of the qPCR curve from the initial growth stage to obtain the initial exponential growth stage; By optimizing the initial exponential growth stage, determine the exponential growth stage from it. The multiple cycles included in the exponential growth stage are the multiple exponential growth period cycles included in the exponential growth period of the qPCR curve.

4. The method according to claim 3, wherein The excluding the stages corresponding to the linear growth period and the plateau period of the qPCR curve from the initial growth stage based on the growth rate of the logarithm values of the fluorescence of each cycle included in the initial growth stage includes: Calculate the growth rate of the logarithm values of the fluorescence of each cycle included in the initial growth stage; Starting from the first cycle included in the initial growth stage, when the growth rate of the logarithm values of the fluorescence of a continuous preset number of cycles is less than the preset growth rate threshold, exclude this continuous preset number of cycles and the cycles after them from the initial growth stage.

5. The method according to claim 3, wherein The determining the exponential growth stage from it by optimizing the initial exponential growth stage includes: Starting from the first cycle included in the initial exponential growth phase, for each cycle in sequence, determine whether the logarithm value of the fluorescence of this cycle is not greater than the logarithm value of the fluorescence of the next cycle. If it is not greater, it indicates that this cycle and its next cycle are in the same growth trend phase. If it is less, it indicates that the growth trend phase ends at this cycle; Determine the number of cycles included in the longest growth trend phase from each growth trend phase included in the initial exponential growth phase; If this number is not less than the preset phase value threshold, determine this number as the longest growth trend phase value. Otherwise, determine the preset phase value threshold as the longest growth trend phase value; For multiple phase values included in the range from the preset phase value threshold to the longest growth trend phase value, determine the phase value corresponding to the growth phase with the smallest fluctuation from the growth phases represented by these multiple phase values as the optimal longest rising interval length; Based on the optimal longest rising period phase represented by the optimal longest rising interval length, determine the exponential growth phase. The optimal longest rising period phase is the phase represented by the optimal longest rising interval length plus 1 cycle starting from the first cycle after the background period; 6. The method according to claim 5, characterized in that The determining the phase value corresponding to the growth phase with the smallest fluctuation from the growth phases represented by these multiple phase values for multiple phase values included in the range from the preset phase value threshold to the longest growth trend phase value includes: For each phase value among the multiple phase values included in the range from the preset phase value threshold to the longest growth trend phase value, calculate the mean fluorescence value of each cycle within the range of this phase value for a consecutive number of cycles equal to this phase value starting from the first cycle after the background period of the qPCR curve, to obtain the first mean curve corresponding to this phase value; Among them, the following formula is used to calculate the mean fluorescence value of the i-th cycle within the range of this phase value: Sum(i) = FA_A(i) + FA_A(i + 1) + … + FA_A(i + len - 1); FA_A_AVG(i) = Sum(k) / len; Among them, FA_A(i) is the adjusted fluorescence value of the i-th cycle among a consecutive number of cycles equal to this phase value, len is this phase value, and FA_A_AVG(i) is the mean fluorescence value of the i-th cycle within the range of this phase value; Calculate the first derivative curve of the first mean curve corresponding to this phase value as the second mean curve corresponding to this phase value; Calculate the second derivative curve of the first mean curve corresponding to this phase value as the third mean curve corresponding to this phase value; Calculate the volatility of the first mean curve, the second mean curve, and the third mean curve corresponding to this phase value; Based on the volatility of the first mean curve, the second mean curve, and the third mean curve corresponding to each phase value among these multiple phase values, determine the phase value corresponding to the curve with the smallest volatility among them as the optimal longest rising interval length.

7. The method according to claim 5, characterized in that, The determining the exponential growth phase based on the optimal longest rising period phase represented by the optimal longest rising interval length includes: Calculate a preset percentage of the difference between the adjusted fluorescence values of the last cycle and the first cycle of the optimal longest rising period stage represented by the optimal longest rising interval length as a preset growth threshold, where the optimal longest rising period stage is from the first cycle after the background period of the qPCR curve to the cycle with the optimal longest rising interval length plus 1 cycle; Among the cycles included in the optimal longest rising period stage, find the last cycle with a growth rate greater than the preset growth threshold as the first cycle of the exponential growth stage, and the cycle with the optimal longest rising interval length plus 1 cycle starting from this first cycle as the last cycle of the exponential growth stage.

8. The method according to claim 1, characterized in that, The calculating the fluorescence threshold of the qPCR curve based on the fluorescence logarithmic values of the multiple exponential growth period cycles in the logarithmic curve includes: Calculate the fluorescence threshold of the qPCR curve using the following formula: Ln(mean) = [Ln(iOptStart) + Ln(iOptStart + 0ptimalLen)] * d; Threshold=e Ln(mean) ; Wherein, Ln(iOptStart) is the fluorescence logarithmic value of the first cycle among the multiple exponential growth period cycles, Ln(iOptStart + optimalLen) is the fluorescence logarithmic value of the last cycle among the multiple exponential growth period cycles, the value range of d is [0.4, 0.6], and Threshold is the fluorescence threshold of the qPCR curve.

9. The method according to claim 2, wherein The calculating the Ct value of the qPCR curve based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve includes: Based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve, calculate the Ct value of the qPCR curve by using the method of simulating the exponential growth period curve of this qPCR curve.

10. A qPCR curve background period detection device, characterized in that, Including: A data acquisition module for acquiring the curve data of the qPCR curve to be detected, where the curve data includes a plurality of consecutive cycles included in the qPCR curve and the fluorescence value of each cycle; An average value calculation module for calculating the average value of the fluorescence values of the multiple background period cycles included in the background period of the qPCR curve; A fluorescence value adjustment module for calculating, for each cycle among the multiple cycles, the difference between the fluorescence value of this cycle and the average value as the adjusted fluorescence value of this cycle; A logarithm calculation module for calculating, for each cycle among the multiple cycles, the natural logarithm of the adjusted fluorescence value of this cycle as the fluorescence logarithmic value of this cycle, where if the adjusted fluorescence value of a cycle is not greater than 0, the fluorescence logarithmic value of this cycle does not exist, and the multiple cycles and the fluorescence logarithmic values of the multiple cycles represent the logarithmic curve corresponding to the qPCR curve; A logarithmic curve analysis module for analyzing the logarithmic curve based on the curve characteristics of the background period, exponential growth period, and linear growth period of the standard qPCR curve to obtain a plurality of exponential growth period cycles included in the exponential growth period of the qPCR curve; A fluorescence threshold calculation module, which is used to calculate the fluorescence threshold of the qPCR curve based on the fluorescence logarithmic values of the multiple exponential growth period cycles in the logarithmic curve.

11. The device according to claim 10, characterized in that, It further includes: A Ct value calculation module, which is used to calculate the Ct value of the qPCR curve based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve.

12. The device according to claim 10, wherein The logarithmic curve analysis module is specifically configured to find the initial growth stage from the logarithmic curve. The initial growth stage is the longest continuous cycle stage starting from the first cycle after the background period of the qPCR curve. Each cycle included in the longest continuous cycle stage has a fluorescence logarithmic value, and the fluorescence logarithmic values are all greater than 0. Moreover, the previous cycle and the next cycle of the longest continuous cycle stage do not have a fluorescence logarithmic value or the fluorescence logarithmic value is not greater than 0. Based on the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage, the stages corresponding to the linear growth period and the plateau period of the qPCR curve are removed from the initial growth stage to obtain the initial exponential growth stage. By optimizing the initial exponential growth stage, an exponential growth stage is determined from it. The multiple cycles included in the exponential growth stage are the multiple exponential growth period cycles included in the exponential growth period of the qPCR curve.

13. The device according to claim 12, wherein The logarithmic curve analysis module is specifically configured to calculate the growth rate of the fluorescence logarithmic value of each cycle included in the initial growth stage; starting from the first cycle included in the initial growth stage, when the growth rate of the fluorescence logarithmic values of a continuous preset number of cycles is less than the preset growth rate threshold, the continuous preset number of cycles and the cycles after them are removed from the initial growth stage.

14. The device according to claim 12, characterized in that, The logarithmic curve analysis module is specifically configured to start from the first cycle included in the initial exponential growth stage, and for each cycle in turn, determine whether the fluorescence logarithmic value of this cycle is not greater than the fluorescence logarithmic value of the next cycle. If it is not greater, it means that this cycle and its next cycle are in the same growth trend stage. If it is less, it means that the growth trend stage ends at this cycle. Determine the number of cycles included in the longest growth trend stage from the growth trend stages included in the initial exponential growth stage. If this number is not less than the preset stage value threshold, this number is determined as the longest growth trend stage value. Otherwise, the preset stage value threshold is determined as the longest growth trend stage value. For the multiple stage values included in the range from the preset stage value threshold to the longest growth trend stage value, determine the stage value corresponding to the growth stage with the smallest fluctuation from the growth stages represented by these multiple stage values as the optimal longest rising interval length. Based on the optimal longest rising period stage represented by the optimal longest rising interval length, an exponential growth stage is determined. The optimal longest rising period stage is the stage represented by the optimal longest rising interval length plus 1 cycle starting from the first cycle after the background period.

15. The device according to claim 14, wherein The logarithmic curve analysis module is specifically configured to calculate, for each of the multiple phase values included in the range from the preset phase value threshold to the longest growth trend phase value, the average fluorescence value of each cycle within the range of this phase value in a consecutive number of cycles equal to this phase value, starting from the first cycle after the background period of the qPCR curve, to obtain the first average value curve corresponding to this phase value; Among them, the following formula is used to calculate the average fluorescence value of the i-th cycle within the range of this phase value: Sum(i) = FA_A(i) + FA_A(i + 1) + … + FA_A(i + len - 1); FA_A_AVG(i) = Sum(k) / len; Among them, FA_A(i) is the adjusted fluorescence value of the i-th cycle in a consecutive number of cycles equal to this phase value, len is this phase value, and FA_A_AVG(i) is the average fluorescence value of the i-th cycle within the range of this phase value; Calculate the first derivative curve of the first average value curve corresponding to this phase value as the second average value curve corresponding to this phase value; Calculate the second derivative curve of the first average value curve corresponding to this phase value as the third average value curve corresponding to this phase value; Calculate the volatility of the first average value curve, the second average value curve, and the third average value curve corresponding to this phase value; Based on the volatility of the first average value curve, the second average value curve, and the third average value curve corresponding to each of the multiple phase values, determine the phase value corresponding to the curve with the smallest volatility as the optimal longest rising interval length.

16. The device according to claim 14, characterized in that, The logarithmic curve analysis module is specifically configured to calculate a preset percentage of the difference between the adjusted fluorescence values of the last cycle and the first cycle of the optimal longest rising period represented by the optimal longest rising interval length as the preset growth threshold, where the optimal longest rising period is from the first cycle after the background period of the qPCR curve to the optimal longest rising interval length plus 1 cycle; Among the cycles included in the optimal longest rising period, find the cycle where the last growth rate is greater than the preset growth threshold as the first cycle of the exponential growth phase, and the optimal longest rising interval length plus 1 cycle starting from this first cycle as the last cycle of the exponential growth phase.

17. The device according to claim 10, characterized in that, The fluorescence threshold calculation module is specifically configured to calculate the fluorescence threshold of the qPCR curve using the following formula: Ln(mean) = [Ln(iOptStart) + Ln(iOptStart + optimalLen)] * d; Threshold=e Ln(mean) ; Among them, Ln(iOptStart) is the logarithm of the fluorescence value of the first cycle among the multiple exponential growth phase cycles, Ln(iOptStart + optimalLen) is the logarithm of the fluorescence value of the last cycle among the multiple exponential growth phase cycles, the value range of d is [0.4, 0.6], and Threshold is the fluorescence threshold of the qPCR curve.

18. The device according to claim 11, characterized in that, The Ct value calculation module is specifically configured to calculate the Ct value of the qPCR curve by using a method of simulating the exponential growth phase curve of the qPCR curve based on the adjusted fluorescence value and the fluorescence threshold of the qPCR curve.

19. An electronic device, characterized in that, It includes a processor and a machine-readable storage medium. The machine-readable storage medium stores machine-executable instructions that can be executed by the processor, and the processor is prompted by the machine-executable instructions to implement the method according to any one of claims 1-9.

20. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method according to any one of claims 1-9 is implemented.

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