Method for determining Ct value of PCR amplification curve

Abstract

The present invention discloses a method for calculating the Ct value of a PCR amplification curve, which includes identifying the fluctuation points in the original PCR amplification curve; when the number of fluctuation points in the original PCR amplification curve is less than the first threshold, the original fluorescence data of the fluctuation points and the subsequent points are corrected, and the corrected fluorescence data is fitted by a six-parameter model to obtain a corrected PCR amplification curve, and the logarithmic phase and the baseline phase of the corrected fluorescence data are identified; a threshold line is determined with 10 times the standard deviation of the corrected fluorescence data in the baseline phase to determine the Ct value. When the number of fluctuation points in the original PCR amplification curve is greater than or equal to the first threshold, the logarithmic phase and the baseline phase of the original PCR amplification curve are identified; a threshold line is determined with 10 times the standard deviation of the original fluorescence data in the baseline phase to determine the Ct value. The advantages of the present invention are that it can identify and process the abnormal fluctuations in the fluorescence data curve during the PCR reaction, accurately identify the logarithmic phase and the baseline phase in the PCR reaction, more precisely obtain the background fluorescence data through the baseline phase, accurately determine the Ct threshold, and improve the anti-interference ability of the Ct value.

Description

Technical Field

[0001] The present invention relates to the field of polymerase chain reaction, and particularly to a method for determining the Ct value of a PCR amplification curve. Background Art

[0002] Polymerase chain reaction (PCR) is a molecular biology technique used to amplify specific DNA / RNA fragments. It can be regarded as nucleic acid replication in vitro. By adding a fluorescent group to the PCR reaction system, the entire PCR process can be monitored using the fluorescence signal. According to the characteristics of the PCR reaction, the nucleic acid substance to be detected will grow exponentially. Considering the influence of the fluorescence background, the fluorescence data curve should be an S-shaped curve. Usually, the cycle number-fluorescence data curve is fitted, and then the Ct value is calculated based on the fitted curve and the threshold line.

[0003] In the actual PCR reaction process, there are situations such as cliffs, mutation points, and a large number of fluctuation points in the fluorescence data curve. At this time, if the cycle number-fluorescence data curve is directly fitted, it will seriously affect the accuracy of the Ct value and even lead to false negatives and false positives. The current methods for determining the Ct value often lack the recognition and processing of situations such as cliffs, mutation points, and a large number of fluctuation points in the fluorescence data curve, seriously affecting the accuracy of the Ct value. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for determining the Ct value of a PCR amplification curve.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] The method for determining the Ct value of a PCR amplification curve according to the present invention includes the following steps:

[0007] S1, identifying the fluctuation points in the original PCR amplification curve;

[0008] S2, when the number of the fluctuation points in the original PCR amplification curve is less than the first threshold, correcting the original fluorescence data of the fluctuation points and the subsequent points, and merging them with the uncorrected original fluorescence data to form corrected fluorescence data; fitting the corrected fluorescence data using a six-parameter model to obtain a corrected PCR amplification curve, and identifying the logarithmic phase and the baseline phase of the corrected fluorescence data;

[0009] When the number of the fluctuation points in the original PCR amplification curve is greater than or equal to the first threshold, identifying the logarithmic phase and the baseline phase of the original PCR amplification curve, and fitting the original fluorescence data within the logarithmic phase and the baseline phase using a six-parameter model to obtain a corrected PCR amplification curve;

[0010] S3. Subtract the background fluorescence data from the corrected fluorescence data corresponding to each cycle number in the corrected PCR amplification curve to obtain a normalized curve; take the cycle number corresponding to the intersection point of the threshold line and the normalized curve as the Ct value.

[0011] The present invention adds the recognition and processing of the abnormal fluctuation of the original fluorescence data in the PCR amplification curve. Based on the number of fluctuation points, select to fit and determine the logarithmic phase and the baseline phase after correcting the original fluorescence data, or select the original fluorescence data of the local logarithmic phase and the baseline phase for fitting, obtain the background fluorescence data through the baseline phase, and then determine the Ct threshold line.

[0012] Further, the recognition of the fluctuation points in step S1 includes:

[0013] S1.1. Calculate the value of the original fluorescence data or the last corrected fluorescence data;

[0014] S1.2. When the value is greater than the preset fluctuation upper limit or less than the preset fluctuation lower limit, then the point corresponding to the i-th cycle number in the original PCR amplification curve is the fluctuation point.

[0015] Further, the correction of the original fluorescence data of the fluctuation points in step S2 includes:

[0016] S2.1. Take the first-order difference mean of the original fluorescence data or the corrected fluorescence data of the N cycle numbers before the first fluctuation point as the reasonable difference of the first fluctuation point;

[0017] S2.2. Calculate the difference between the original fluorescence data of the first fluctuation point and the original fluorescence data or the corrected fluorescence data corresponding to its previous adjacent cycle number;

[0018] S2.3. Subtract the difference from the original fluorescence data or the corrected fluorescence data of the first fluctuation point and all subsequent points, and then add the reasonable difference as the corrected fluorescence data of the first fluctuation point and all subsequent points;

[0019] S2.4. Repeat step S1 to identify the fluctuation points;

[0020] S2.5. Repeat steps S2.1 to S2.4 until the fluctuation points disappear or the number of repetitions reaches the preset requirement.

[0021] Further, the six-parameter model is:

[0022] ,

[0023] where y is the corrected fluorescence data, x is the cycle number, and a, b, c, d, e, and k are parameters.

[0024] Further, the logarithmic phase identification step is as follows:

[0025] In the first step, calculate the value of the original fluorescence data or the corrected fluorescence data;

[0026] In the second step, sequentially judge that when the second threshold and the second threshold holds, record the point corresponding to the i-th cycle number as the starting point and the ending point of the logarithmic phase; the second threshold and the second threshold holds, then update the point corresponding to the i-th cycle number as the ending point of the logarithmic phase; until the second threshold and the second threshold, determine the point corresponding to the i-th cycle number as the ending point of the logarithmic phase;

[0027] In the third step, the number of logarithmic phase cycle numbers is: the ending point of the logarithmic phase - the starting point of the logarithmic phase + 1. If the number of logarithmic phase cycle numbers is greater than the preset value, record the section from the starting point of the logarithmic phase to the ending point of the logarithmic phase as a logarithmic phase section;

[0028] In the fourth step, re-execute the second step until all value judgments are completed, and several logarithmic phase sections are obtained;

[0029] In the fifth step, select the logarithmic phase section with the largest number of logarithmic phase cycle numbers as the initial logarithmic phase;

[0030] In the sixth step, sequentially calculate the sum and value of the original fluorescence data or the corrected fluorescence data at the starting point and the ending point of the initial logarithmic phase;

[0031] In the seventh step, sequentially judge that when the third threshold or the third threshold holds, add the point corresponding to the (i - 1)-th cycle number or the point corresponding to the (j + 1)-th cycle number to the initial logarithmic phase until the third threshold or the third threshold holds, and determine the logarithmic phase.

[0032] Further, the baseline period identification step is as follows:

[0033] In the first step, calculate the value of the original fluorescence data or the corrected fluorescence data;

[0034] In the second step, sequentially judge that when the fourth threshold and the fifth threshold are first satisfied, record the point corresponding to the i-th cycle number as the starting point of the base period until the first occurrence of the fourth threshold or When reaching the fifth threshold, record the point corresponding to the i-th cycle number as the end point of the base period;

[0035] In the third step, repeatedly execute the second step until it is determined up to the start point of the logarithmic phase, obtaining a number of alternative baseline periods;

[0036] In the fourth step, use the alternative baseline period adjacent to the logarithmic phase as the baseline period.

[0037] Further, the background fluorescence data includes the mean or minimum value of the corrected fluorescence data in the baseline period.

[0038] Further, the threshold line includes 10 times the standard deviation of the corrected fluorescence data in the baseline period.

[0039] Further, the calculation method of the value is:

[0040] ,

[0041] wherein, is the standard deviation of the original fluorescence data or the corrected fluorescence data, is the original fluorescence data or the corrected fluorescence data, i is the cycle number, is the original fluorescence data or the corrected fluorescence data corresponding to the i-th cycle number.

[0042] The advantages of the present invention are that it can identify and process abnormal fluctuations in the fluorescence data curve during the PCR reaction, correct the fluorescence data at the fluctuation points, and propose a method for accurately identifying the logarithmic phase and the baseline phase in the PCR reaction, which can obtain the background fluorescence data more precisely through the baseline period, thereby accurately determining the Ct threshold line and improving the anti-interference ability of the Ct value. Description of the Drawings

[0043] Figure 1 is the flowchart of the method of the present invention.

[0044] Figure 2 is the schematic diagram of the original PCR amplification curve in Example 1 of the present invention.

[0045] Figure 3 is the flowchart of the identification and correction of the fluctuation points of the method of the present invention.

[0046] <y Figure 4 is the schematic diagram after the correction of the fluctuation points in the original PCR amplification curve in Example 1 of the present invention.

[0047] Figure 5 is the schematic diagram of the six-parameter fitting in Example 1 of the present invention.

[0048] Figure 6It is the flowchart for determining the initial logarithmic phase in the method of the present invention.

[0049] Figure 7 It is the flowchart for finally determining the logarithmic phase in the method of the present invention.

[0050] Figure 8 It is the flowchart for determining the base period in the method of the present invention.

[0051] Figure 9 It is the schematic diagram of the normalized curve and the threshold line in Example 1 of the present invention.

[0052] Figure 10 It is the schematic diagram of the original PCR amplification curve in Example 2 of the present invention.

[0053] Figure 11 It is the schematic diagram of the normalized curve and the threshold line in Example 2 of the present invention. Detailed implementation manners

[0054] Next, the technical solutions in the embodiments of the present invention will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0055] The method for determining the Ct value of the PCR amplification curve described in the present invention includes the method for determining the Ct value when there are few cliffs, mutation points, and fluctuation points in the PCR amplification curve, and the method for determining the Ct value when there are many cliffs, mutation points, and fluctuation points in the PCR amplification curve.

[0056] As Figure 1 shown, it is the schematic flowchart of the method for determining the Ct value of the PCR amplification curve described in the present invention. The following will separately describe how the present invention determines the Ct value when there are few cliffs, mutation points, and fluctuation points in the PCR amplification curve, and how the present invention determines the Ct value when there are many cliffs, mutation points, and fluctuation points in the PCR amplification curve.

[0057] Example 1 details the method steps for determining the Ct value when there are few cliffs, mutation points, and fluctuation points in the PCR amplification curve.

[0058] As Figure 2 shown, there are few cliffs, mutation points, and fluctuation points in the original PCR amplification curve. The method steps for calculating the Ct value of the data collected this time are as follows:

[0059] S1. Identify the fluctuation points in the original PCR amplification curve; calculate the value of each original fluorescence data in sequence; wherein, the calculation method of the

[0060] ,

[0061] is the standard deviation of the original fluorescence data, is the original fluorescence data, i is the number of cycles, is the original fluorescence data corresponding to the i-th cycle number, is for the i-th cycle number value.

[0062] When the value is greater than the preset upper fluctuation limit or less than the preset lower fluctuation limit, then the point corresponding to the i-th cycle number in the original PCR amplification curve is the said fluctuation point, and the number and position of the fluctuation points in the original PCR amplification curve are recorded. For Figure 2 the data shown, through the calculation in step S1, it can be identified that the 8th cycle and the 21st cycle are the fluctuation points, and the number is only 2, which is less than the first threshold. Among them, the first threshold represents the maximum number of preset fluctuation points. Then execute the relevant steps when the number of fluctuation points in step S2 is less than the first threshold.

[0063] S2. When the number of fluctuation points in the original PCR amplification curve is less than the first threshold, then correct the original fluorescence data of the fluctuation point and each point after the fluctuation point, and use the six-parameter model to fit all the corrected fluorescence data and the uncorrected original fluorescence data to obtain the corrected PCR amplification curve, and identify the logarithmic phase and the baseline phase of the corrected fluorescence data.

[0064] S2.1. First, take the first-order difference mean of the original fluorescence data of the first N points before the first fluctuation point (i.e., at the 8th cycle number) in the order of the cycle number as the reasonable difference of the first fluctuation point; N is a user-defined value, and in this embodiment, N is selected as 3, that is, select the first-order difference mean of the original fluorescence data at the 5th, 6th, and 7th cycle numbers as the reasonable difference between the fluorescence data at the 8th cycle number and the fluorescence data at the 7th cycle number.

[0065] S2.2. Then calculate the difference between the original fluorescence data of the first fluctuation point and the original fluorescence data corresponding to its previous adjacent cycle number; that is, the difference is equal to the original fluorescence data at the 8th cycle number minus the original fluorescence data at the 7th cycle number.

[0066] S2.3. After subtracting the difference from the original fluorescence data of the first fluctuation point and each point after it, and then adding the reasonable difference, it is used as the corrected fluorescence data of the first fluctuation point and each point after it. That is, the original fluorescence data at the 8th and subsequent cycle numbers from 9 to 45 minus the difference, and then adding the reasonable difference determined in step S2.1, is the corrected fluorescence data at the 8th and subsequent cycle numbers from 9 to 45.

[0067] S2.4. Since new cliffs, mutation points, and fluctuation points may occur in the corrected fluorescence data after correcting the original fluorescence data at a fluctuation point and subsequent points, it is necessary to repeat step S1 to re-identify the fluctuation points.

[0068] S2.5. Then repeat steps S2.1 to S2.4 until the fluctuation points disappear or the number of repetitions reaches the preset requirement. At the same time, when repeating step S2.1 to calculate the value, the standard deviation and corrected fluorescence data of the corrected fluorescence data from the previous round need to be used.

[0069] As Figure 3 shown, the process of identifying and correcting fluctuation points is demonstrated using a flow chart.

[0070] For Figure 2 the data shown, after correcting the original fluorescence data at the 8th cycle number and subsequent cycle numbers, when repeating step S1 again, the 21st cycle can be re-identified as a fluctuation point, and then steps S2.1 to S2.4 in S2 are executed until no new fluctuation points are identified after executing step S1 (i.e., the number of fluctuation points is 0), or the repetition has reached the preset value and then stop. As Figure 4 shown, the result after correcting the fluctuation points is presented.

[0071] After that, a six-parameter model is used to fit all the fluorescence data to obtain a corrected PCR amplification curve, where all the fluorescence data includes both the corrected fluorescence data and the uncorrected original fluorescence data. The six-parameter model is:

[0072] ,

[0073] where y is the corrected fluorescence data, x is the cycle number, and a, b, c, d, e, k are parameters. As Figure 5 shown, it is the fitting effect diagram of the six-parameter model.

[0074] Then identify the logarithmic phase and baseline phase of the corrected fluorescence data;

[0075] The steps for identifying the logarithmic phase are:

[0076] First step, calculate the value of the corrected fluorescence data;

[0077] Second step, sequentially judge the second threshold and the second threshold, and record the point corresponding to the i-th cycle number as the starting point and ending point of the logarithmic phase; the second threshold and the second threshold, then update the point corresponding to the i-th cycle number as the ending point of the logarithmic phase; until the second threshold and At the second threshold, determine the point corresponding to the i-th cycle number as the end point of the logarithmic phase;

[0078] In the third step, the number of cycle numbers in the logarithmic phase is: end point of the logarithmic phase - start point of the logarithmic phase + 1; if the number of cycle numbers in the logarithmic phase is greater than the preset value, record the section between the start point and the end point of the logarithmic phase as a logarithmic phase section;

[0079] In the fourth step, re-execute the second step until all value judgments are completed, and several logarithmic phase sections are obtained;

[0080] In the fifth step, select the section with the largest number of cycle numbers as the initial logarithmic phase; as Figure 6 shown is the flowchart for determining the initial logarithmic phase

[0081] In the sixth step, calculate the and values of the corrected fluorescence data at the start and end points of the initial logarithmic phase;

[0082] In the seventh step, judge the third threshold or the third threshold, add the point corresponding to the (i - 1)-th cycle number or the point corresponding to the (j + 1)-th cycle number to the initial logarithmic phase until the third threshold or the third threshold, and determine the logarithmic phase. As Figure 7 shown is the flowchart for finally determining the logarithmic phase.

[0083] That is, first calculate the value of the corrected fluorescence data at the start point of the initial logarithmic phase; judge in sequence when the third threshold holds, add the point corresponding to the (i - 1)-th cycle number to the initial logarithmic phase until the first occurrence of the third threshold holds and terminate the judgment. Similarly, calculate the value of the corrected fluorescence data at the end point of the initial logarithmic phase, judge in sequence when the third threshold holds, add the point corresponding to the (j + 1)-th cycle number to the initial logarithmic phase until the first occurrence of the third threshold holds and terminate the judgment to determine the final logarithmic phase. Among them, the second threshold is greater than the third threshold. The logarithmic phase in the PCR amplification process can be accurately identified through the second threshold, and the data that should belong to the start and end segments of the logarithmic phase in the PCR amplification process can be included in the logarithmic phase through the third threshold, making the finally determined logarithmic phase more in line with the actual situation and avoiding omission of relevant data.

[0084] As Figure 8 shown, the steps for identifying the baseline phase are:

[0085] In the first step, calculate the Value;

[0086] In the second step, sequentially determine that when the fourth threshold is first satisfied The fifth threshold, record the point corresponding to the i-th cycle number as the starting point of the base period until The fourth threshold or The fifth threshold, record the point corresponding to the i-th cycle number as the end point of the base period;

[0087] In the third step, loop and execute the second step until the judgment point is the starting point of the final logarithmic phase, obtaining several alternative baseline periods;

[0088] In the fourth step, use the baseline period adjacent to the logarithmic phase as the baseline period.

[0089] The fourth threshold represents the preset lower limit of the baseline period limit, and the fifth threshold represents the preset upper limit of the baseline period limit. The fourth threshold is less than the fifth threshold. According to the baseline period identification steps, sequentially judge the Value, when it first appears The value is within the range of the fourth threshold and the fifth threshold, the point corresponding to the i-th cycle number is the starting point of the base period; when it first appears The value is outside the range of the fourth threshold and the fifth threshold, the point corresponding to the i-th cycle number is the end point of the base period; there is 1 baseline period between two cycle numbers. Continue to loop and execute until the final logarithmic phase starting point is judged. Several baseline periods can be obtained in this process. Use the baseline period adjacent to the logarithmic phase as the baseline period.

[0090] Then execute step S3.

[0091] S3. Subtract the background fluorescence data from the corrected fluorescence data corresponding to each cycle number in the corrected PCR amplification curve to obtain a normalized curve; use the cycle number corresponding to the intersection point of the threshold line and the normalized curve as the Ct value. The background fluorescence data includes the mean or minimum value of the corrected fluorescence data in the baseline period. The threshold line includes 10 times the standard deviation of the corrected fluorescence data in the baseline period.

[0092] For Figure 2 The data shown, determine that the final baseline period is from the 1st cycle number to the 39th cycle number, and the logarithmic phase is from the 40th cycle number to the 45th cycle number. Further determine that the normalized curve is as Figure 9 The curve shown; the value of the threshold line is 10 times the standard deviation of the corrected fluorescence data in the baseline period, as Figure 9 The straight line shown, which is 161.24, and determine that the Ct value is 41.79.

[0093] Example 2 details the method steps for determining the Ct value when there are many cliffs, mutation points, and fluctuation points in the PCR amplification curve.

[0094] As Figure 10 shown, it can be seen that there are situations where the original fluorescence data in the original PCR amplification curve suddenly drops, rises, or mutates significantly. The method steps for calculating the Ct value from the data collected this time are as follows:

[0095] S1. Identify the fluctuation points in the original PCR amplification curve; calculate the value of each original fluorescence data in sequence; where the value calculation method is:

[0096] ,

[0097] is the standard deviation of the original fluorescence data, is the original fluorescence data, i is the cycle number, is the original fluorescence data corresponding to the i-th cycle number, is the value of the i-th cycle number.

[0098] When the value is greater than the preset fluctuation upper limit or less than the preset fluctuation lower limit, then the point corresponding to the i-th cycle number in the original PCR amplification curve is the said fluctuation point, and record the number and position of the fluctuation points in the original PCR amplification curve. As Figure 9 shown, through the calculation in step S1, a total of 6 fluctuation points can be identified at the 9th, 10th, 27th, 28th, 29th, and 31st cycle numbers. This number is greater than the first threshold, and it is necessary to execute the relevant steps in S2 when the number of fluctuation points is greater than or equal to the first threshold.

[0099] S2. When the number of fluctuation points in the original PCR amplification curve is greater than or equal to the first threshold, then identify the logarithmic phase and the baseline phase of the original PCR amplification curve, and use a six-parameter model to fit the original fluorescence data in the logarithmic phase and the baseline phase to obtain a corrected PCR amplification curve;

[0100] First, identify the logarithmic phase and the baseline phase of the original PCR amplification curve;

[0101] The steps for identifying the logarithmic phase are:

[0102] The first step is to calculate the value of the original fluorescence data;

[0103] The second step is to sequentially judge the second threshold and the second threshold, and record the point corresponding to the i-th cycle number as the starting point and the ending point of the logarithmic phase; the second threshold and the second threshold, then update the point corresponding to the i-th cycle number as the ending point of the logarithmic phase; until the second threshold and When the second threshold is reached, determine the point corresponding to the i-th cycle number as the end point of the logarithmic phase;

[0104] Thirdly, the number of cycle numbers in the logarithmic phase is: end point of the logarithmic phase - start point of the logarithmic phase + 1; if the number of cycle numbers in the logarithmic phase is greater than the preset value, record the section between the start point and the end point of the logarithmic phase as a logarithmic phase section;

[0105] Fourthly, re-execute the second step until the judgment of all values is completed, and several logarithmic phase sections are obtained;

[0106] Fifthly, select the section with the largest number of cycle numbers as the initial logarithmic phase;

[0107] Sixthly, calculate the sum value of the corrected fluorescence data at the start point and the end point of the initial logarithmic phase in sequence;

[0108] Seventhly, judge the third threshold or when the third threshold is reached, add the point corresponding to the (i - 1)-th cycle number or the point corresponding to the (j + 1)-th cycle number to the initial logarithmic phase until the third threshold or the third threshold is reached, and determine the final logarithmic phase.

[0109] That is, first calculate the value of the original fluorescence data at the start point of the initial logarithmic phase; judge in sequence, when the third threshold holds, add the point corresponding to the (i - 1)-th cycle number to the initial logarithmic phase until the first occurrence of the third threshold holds and terminate the judgment. Similarly, calculate the value of the original fluorescence data at the end point of the initial logarithmic phase, judge in sequence, when the third threshold holds, add the point corresponding to the (j + 1)-th cycle number to the initial logarithmic phase until the first occurrence of the third threshold holds and terminate the judgment, and determine the final logarithmic phase. Among them, the second threshold is greater than the third threshold. The logarithmic phase in the PCR amplification process can be accurately identified through the second threshold, and the data that should belong to the start and end segments of the logarithmic phase in the PCR amplification process can be included in the logarithmic phase through the third threshold, making the finally determined logarithmic phase more in line with the actual situation and avoiding missing relevant data.

[0110] The steps for identifying the baseline phase are as follows:

[0111] First step, calculate the value of the original fluorescence data;

[0112] Second step, judge When reaching the fifth threshold, record the point corresponding to the i-th cycle number as the starting point of the base period until the fourth threshold or the fifth threshold is reached, and record the point corresponding to the i-th cycle number as the ending point of the base period;

[0113] In the third step, repeatedly execute the second step until the judgment point is the starting point of the final logarithmic phase, obtaining several baseline periods;

[0114] In the fourth step, use the baseline period adjacent to the logarithmic phase as the final baseline period.

[0115] The fourth threshold represents the preset lower limit of the baseline period limit, and the fifth threshold represents the preset upper limit of the baseline period limit. The fourth threshold is less than the fifth threshold. According to the baseline period identification steps, sequentially judge the value of the original fluorescence data. When the value first appears within the range of the fourth threshold and the fifth threshold, the point corresponding to the i-th cycle number is the starting point of the base period; when the value first appears outside the range of the fourth threshold and the fifth threshold, the point corresponding to the i-th cycle number is the ending point of the base period; there is 1 baseline period between two cycle numbers. Continue to execute the loop until the judgment reaches the starting point of the final logarithmic phase. Several baseline periods can be obtained through this process. Use the baseline period adjacent to the logarithmic phase as the final baseline period.

[0116] After that, use a six-parameter model to fit all the fluorescence data of the baseline period and the logarithmic phase to obtain a corrected PCR amplification curve. The six-parameter model is:

[0117] ,

[0118] where y is the original fluorescence data, x is the cycle number, and a, b, c, d, e, k are parameters. As Figure 3 shown, it is the fitting effect diagram of the six-parameter model.

[0119] Then execute step S3.

[0120] S3. Subtract the background fluorescence data from the corrected fluorescence data corresponding to each cycle number in the corrected PCR amplification curve to obtain a normalized curve; use the cycle number corresponding to the intersection point of the threshold line and the normalized curve as the Ct value. The background fluorescence data includes the mean or minimum value of the corrected fluorescence data in the baseline period. The threshold line includes 10 times the standard deviation of the original fluorescence data in the baseline period.

[0121] For the Figure 10 data shown, determine that the final baseline period is from the 12th cycle number to the 25th cycle number, and the logarithmic phase is from the 35th cycle number to the 45th cycle number. Further determine that the normalized curve is as Figure 11The curve shown; the value of the threshold line is 10 times the standard deviation of the original fluorescence data in the baseline period, which is 31.73, as Figure 11 the straight line shown, and the Ct value is determined to be 33.46.

Claims

1. A method for determining the Ct value of a PCR amplification curve, characterized in that: including the following steps: S1. Identify the fluctuation points in the original PCR amplification curve; the identification of the fluctuation points in the original PCR amplification curve includes: S1.1, calculate the value of the original fluorescence data or the last corrected fluorescence data; S1.2, when the value is greater than the preset upper limit of fluctuation or less than the preset lower limit of fluctuation, then the point corresponding to the i-th cycle number in the original PCR amplification curve is the fluctuation point; S2. When the number of the fluctuation points in the original PCR amplification curve is less than the first threshold, correct the original fluorescence data of the fluctuation points and the subsequent points, and merge them with the uncorrected original fluorescence data to form corrected fluorescence data; use a six-parameter model to fit the corrected fluorescence data to obtain a corrected PCR amplification curve, and identify the logarithmic phase and the baseline phase of the corrected fluorescence data; When the number of the fluctuation points in the original PCR amplification curve is greater than or equal to the first threshold, identify the logarithmic phase and the baseline phase of the original PCR amplification curve, and use a six-parameter model to fit the original fluorescence data within the logarithmic phase and the baseline phase to obtain a corrected PCR amplification curve; The logarithmic phase identification step is: First, calculate the value of the original fluorescence data or the corrected fluorescence data; Step 2: successively determine that when the second threshold and the second threshold holds, record the point corresponding to the i-th cycle number as the starting point and the ending point of the logarithmic phase; the second threshold and when the second threshold holds, update the point corresponding to the i-th cycle number as the ending point of the logarithmic phase; until the second threshold and the second threshold, determine the point corresponding to the i-th cycle number as the ending point of the logarithmic phase; The third step, the number of cycles in the logarithmic phase is: the end point of the logarithmic phase - the start point of the logarithmic phase + 1. If the number of cycles in the logarithmic phase is greater than the preset value, record the start point to the end point of the logarithmic phase as a logarithmic phase segment; Step 4: Re-execute Step 2 until the judgment of all values is completed, and several of the logarithmic phase sections are obtained; The fifth step, select the logarithmic phase segment with the largest number of cycles in the logarithmic phase as the initial logarithmic phase; Step 6: Calculate the sum value of the original fluorescence data or the corrected fluorescence data at the starting point and the ending point of the initial logarithmic phase in sequence; Step 7, sequentially determine when the third threshold or the third threshold holds, add the point corresponding to the (i - 1)-th cycle number or the point corresponding to the (j + 1)-th cycle number to the initial logarithmic phase until the third threshold or the third threshold holds, and determine the logarithmic phase; S3. Subtract the background fluorescence data from the corrected fluorescence data corresponding to each cycle number in the corrected PCR amplification curve to obtain a normalized curve; use the cycle number corresponding to the intersection point of the threshold line and the normalized curve as the Ct value.

2. The method for determining the Ct value of the PCR amplification curve according to claim 1, wherein: The original fluorescence data for correcting the fluctuation points in step S2 includes: S2.

1. Take the first-order difference mean of the original fluorescence data or the corrected fluorescence data of the first N cycle numbers before the first fluctuation point as the reasonable difference of the first fluctuation point; S2.

2. Calculate the difference between the original fluorescence data of the first fluctuation point and the original fluorescence data or the corrected fluorescence data corresponding to its previous adjacent cycle number; S2.

3. Subtract the difference from the original fluorescence data or the corrected fluorescence data of the first fluctuation point and the subsequent points, and then add the reasonable difference as the corrected fluorescence data of the first fluctuation point and the subsequent points; S2.

4. Repeat step S1 to identify the fluctuation points; S2.

5. Repeat steps S2.1 to S2.4 until the fluctuation points disappear or the number of repetitions reaches the preset requirements.

3. The method for determining the Ct value of a PCR amplification curve according to claim 1, characterized in that: The six-parameter model is: ； where y is the corrected fluorescence data, x is the cycle number, and a, b, c, d, e, k are parameters.

4. The method for determining the Ct value of a PCR amplification curve according to claim 1, wherein: The baseline phase identification step is: First step, calculate the value of the original fluorescence data or the corrected fluorescence data; Step 2: Judging sequentially, when the fourth threshold is first satisfied and the fifth threshold, record the point corresponding to the i-th cycle number as the starting point of the base period until the first occurrence of the fourth threshold or the fifth threshold, record the point corresponding to the i-th cycle number as the ending point of the base period; The third step, loop and execute the second step until it is judged to reach the start point of the logarithmic phase, and obtain several alternative baseline phases; The fourth step, use the alternative baseline phase adjacent to the logarithmic phase as the baseline phase.

5. The method for determining the Ct value of a PCR amplification curve according to claim 1, characterized in that: The background fluorescence data includes the mean or the minimum value of the corrected fluorescence data in the baseline phase.

6. The method for determining the Ct value of a PCR amplification curve according to claim 1, characterized in that: The threshold line includes 10 times the standard deviation of the corrected fluorescence data in the baseline phase.

7. The method for determining the Ct value of the PCR amplification curve according to claim 1, wherein: The said value is calculated as follows: ； Among them, is the standard deviation of the original fluorescence data or the corrected fluorescence data, is the original fluorescence data or the corrected fluorescence data, and i is the number of cycles, which is the original fluorescence data or the corrected fluorescence data corresponding to the i-th cycle number.

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