A real-time fluorescence quantitative PCR data processing method and device

Abstract

The present invention provides a real-time fluorescence quantitative PCR data processing method and device, the method comprising: obtaining the measured fluorescence data corresponding to each cycle node in the collected target sample, correcting the measured fluorescence data by a preset crosstalk correction model, and obtaining denoised fluorescence data; performing linear fitting processing on the denoised fluorescence data to obtain a target linear mathematical model, determining a slope model, and performing second-order derivative to obtain a second-order derivative expression, and determining the cycle node corresponding to the end point of the baseline period; obtaining a baseline correction model according to the end point of the baseline period, and performing baseline correction on the denoised fluorescence data according to the baseline correction model to obtain target fluorescence data. Through the above-mentioned real-time fluorescence quantitative PCR data processing method, the real-time fluorescence quantitative PCR data processing efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of molecular biology, and in particular to a real-time fluorescence quantitative PCR data processing method and device. Background Art

[0002] Real-time fluorescence quantitative polymerase chain reaction (Real-Time PCR) is a molecular biology experimental technique based on polymerase chain reaction (PCR). It monitors the amplification of the target DNA sequence in real time during the PCR process. It has the advantages of accuracy, high sensitivity, strong specificity, simplicity, rapidity and ease of automation. It is widely used in nucleic acid molecular detection in clinical and life science fields, such as gene expression research, detection of infectious diseases and cancer gene abnormalities, microbial detection related to food safety, detection of plant pathogens, quantification and genotyping of clinical viral infections, etc. In the DNA sequence amplification reaction, the real-time fluorescence quantitative polymerase chain reaction uses fluorescent chemicals to detect the total amount of products after each polymerase chain reaction cycle. Since there is a linear relationship between the Ct value of the DNA sequence and the starting copy number of the DNA sequence in the exponential period of polymerase chain reaction amplification, it becomes the basis for quantification. The DNA sequence in the sample to be tested is quantitatively analyzed by the internal reference method or the external reference method. After the fluorescent probe used for labeling combines with the corresponding molecular chain, a corresponding fluorescent signal will be generated. Different fluorescent signals correspond to a specific band, and the sensor detecting this band can display the maximum brightness value.

[0003] The inventors have found that in practical applications, it is usually necessary to simultaneously detect two or more targets (amplification targets) in a sample, and therefore it is necessary to use different fluorescent groups (probes) (which emit fluorescence in a specific band after being excited) to mark different targets. Since the spectrum of fluorescence is continuous, there is a partial intersection between different fluorescences, and the fluorescence intensity detected in the same band may be a superposition of several fluorescences, which is the phenomenon of fluorescence crosstalk. This crosstalk phenomenon will greatly interfere with the negative-positive judgment of the reaction chamber in different observation channels. In addition, the reactions of different targets in the same reaction chamber will form competition, thereby affecting the reaction efficiency of a single target, and then affecting the endpoint observation of the fluorescent group marking the target, resulting in errors in negative-positive judgments.

[0004] The baseline part of actual PCR amplification data may have problems such as tilt and jitter. The baseline recognition and correction algorithms of existing instruments cannot accurately find the end point of the baseline when processing some linear data with large deviations, so as to perform subsequent corrections and calculations.

[0005] In view of this, there is an urgent need for a real-time fluorescence quantitative PCR data processing method that can accurately find the endpoint of the baseline for precise correction and calculation. Summary of the invention

[0006] In view of this, the present invention provides a real-time fluorescence quantitative PCR data processing method and device to solve the technical problem of relatively low efficiency of real-time fluorescence quantitative PCR data processing in the prior art.

[0007] In a first aspect, a real-time fluorescence quantitative PCR data processing method provided according to an embodiment of the present invention comprises:

[0008] Acquire the measured fluorescence data corresponding to each cycle node in the collected target sample, perform fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model, and obtain the denoised fluorescence data corresponding to each cycle node in the target sample;

[0009] Performing linear fitting processing on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain a target linear mathematical model, determining a slope model of the target linear mathematical model at each cycle node, performing second-order derivative on the slope model to obtain a second-order derivative expression, and determining the cycle node corresponding to the end point of the baseline period according to the extreme value of the second-order derivative expression, wherein the cycle node corresponding to the end point of the baseline period is located before the maximum point of the second-order derivative expression, and the cycle node corresponding to the end point of the baseline period is the minimum point among the minimum points that is closest to the maximum point;

[0010] According to the cycle node corresponding to the end point of the baseline period, a baseline node set is selected from the cycle nodes of the target sample, and the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model are combined to obtain a baseline correction model. According to the baseline correction model, the denoised fluorescence data corresponding to each cycle node in the target sample are baseline corrected to obtain the target fluorescence data corresponding to each cycle node in the target sample.

[0011] In one embodiment, the step of acquiring the measured fluorescence data corresponding to each cycle node in the collected target sample, and performing fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model to obtain the denoised fluorescence data corresponding to each cycle node in the target sample includes:

[0012] According to the measured fluorescence data corresponding to each cycle node in the target sample, the corresponding target crosstalk correction coefficient, target uniformity correction coefficient, and target background fluorescence data in the preset crosstalk correction model are determined;

[0013] According to the target crosstalk correction coefficient and the target background fluorescence data, a fluorescence crosstalk correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample through a preset crosstalk correction model;

[0014] According to the target uniformity correction coefficient, a uniformity correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample after the fluorescence crosstalk correction process through a preset crosstalk correction model, and denoised fluorescence data corresponding to each cycle node in the target sample is obtained;

[0015] Among them, the measured fluorescence data corresponding to each cycle node in the target sample carries the identification information of the corresponding target sample, and the identification information includes the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample; the target crosstalk correction coefficient is adapted to the sampling channel corresponding to the target sample, the target uniformity correction coefficient is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample, and the target background fluorescence data is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample.

[0016] In one embodiment, the fluorescence crosstalk correction processing is performed on the measured fluorescence data corresponding to each cycle node in the target sample by a preset crosstalk correction model according to the target crosstalk correction coefficient and the target background fluorescence data, including:

[0017] Calculate the difference between the measured fluorescence data corresponding to each cycle node in the target sample and the target background fluorescence data to obtain the fluorescence data corresponding to each cycle node in the target sample with background noise removed;

[0018] According to the target crosstalk correction coefficient, fluorescence crosstalk correction processing is performed on the fluorescence data corresponding to each cycle node in the target sample from which background noise is removed, so as to obtain crosstalk-corrected fluorescence data corresponding to each cycle node in the target sample.

[0019] In one implementation, the preset crosstalk correction model is:

[0020] f i =M nm -1 ×[O i -A mn ]

[0021] Y i =X mn ×f i

[0022] Among them, f i is the crosstalk-corrected fluorescence data obtained by correcting the fluorescence crosstalk after removing the background noise corresponding to the i-th cycle node; M nm -1 is the crosstalk correction coefficient of the target sample corresponding to n sampling holes and m sampling channels; i is the measured fluorescence data corresponding to the i-th cycle node; Amn Y is the background fluorescence data corresponding to the target sample’s m sampling channel and n sampling hole; i is the denoised fluorescence data corresponding to the i-th cycle node; X mn is the uniformity correction coefficient corresponding to the m sampling channels and n sampling holes of the target sample.

[0023] In one embodiment, performing a second-order derivative on the slope model to obtain a second-order derivative expression includes:

[0024] Taking a first-order derivative of the slope model to obtain a first-order derivative expression;

[0025] The first-order derivative expression is smoothed, and the first-order derivative expression after the smoothing is first-order differentiated to obtain a second-order derivative expression.

[0026] In one embodiment, according to the cycle node corresponding to the end point of the baseline period, a baseline node set is selected from the cycle nodes of the target sample, and a baseline correction model is obtained by combining the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model. According to the baseline correction model, the denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected to obtain the target fluorescence data corresponding to each cycle node in the target sample, including:

[0027] According to a preset baseline period starting point determination rule, a cycle node corresponding to the baseline period starting point is determined from the cycle nodes of the target sample, and nodes from the cycle node corresponding to the baseline period starting point to the cycle node corresponding to the baseline period end point are selected from the cycle nodes of the target sample as a baseline node set;

[0028] Determining slope data of all loop nodes in the slope model corresponding to the baseline node set, and determining slope parameters of the baseline correction model according to the slope data of all loop nodes;

[0029] Determining correction parameters of the baseline correction model according to the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period;

[0030] According to the baseline correction model after determining the slope parameter and the correction parameter, baseline correction is performed on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain the target fluorescence data corresponding to each cycle node in the target sample;

[0031] The baseline correction model is:

[0032] J i =Y i -(a×ib)

[0033] Among them, i is the i-th loop node, Yi is the denoised fluorescence data corresponding to the i-th cycle node; a is the slope parameter, b is the correction parameter, J i is the target fluorescence data obtained by baseline correction of the denoised fluorescence data corresponding to the i-th cycle node.

[0034] In one embodiment, before obtaining the measured fluorescence data corresponding to each cycle node in the collected target sample, the method further includes:

[0035] Acquire the collected first fluorescence data of each sampling channel corresponding to each sampling well in the first sample plate, and obtain the background fluorescence data of each sampling channel corresponding to each sampling well, wherein the first sample plate is a water preparation sample plate;

[0036] Acquire the collected second fluorescence data of each sampling channel corresponding to each sampling well in the second sample plate, determine the sampling channel corresponding to the unit coefficient for each sampling well, and determine the crosstalk correction coefficient of each sampling channel corresponding to each sampling well, wherein the second sample plate is a sample plate prepared with a pure color fluorescent dye;

[0037] Obtain the collected third fluorescence data of each sampling channel corresponding to each sampling well in the third sample plate, determine the sampling well corresponding to the unit coefficient for each sampling channel, and determine the uniform correction coefficient of each sampling well corresponding to each sampling channel, wherein the third sample plate is a sample plate prepared with a full-spectrum mixed-color fluorescent dye.

[0038] In a second aspect, a real-time fluorescence quantitative PCR data processing device provided according to an embodiment of the present invention comprises:

[0039] A denoising module is used to obtain the measured fluorescence data corresponding to each cycle node in the collected target sample, and perform fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model to obtain denoised fluorescence data corresponding to each cycle node in the target sample;

[0040] A fixed-point module, used for performing linear fitting processing on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain a target linear mathematical model, determining a slope model of the target linear mathematical model at each cycle node, and performing a second-order derivative on the slope model to obtain a second-order derivative expression, and determining the cycle node corresponding to the end point of the baseline period according to the extreme value of the second-order derivative expression, wherein the cycle node corresponding to the end point of the baseline period is located before the maximum point of the second-order derivative expression, and the cycle node corresponding to the end point of the baseline period is the minimum point closest to the maximum point;

[0041] A base correction module is used to select a baseline node set from the cycle nodes of the target sample according to the cycle node corresponding to the end point of the baseline period, combine the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model to obtain a baseline correction model, and perform baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline correction model to obtain target fluorescence data corresponding to each cycle node in the target sample.

[0042] In a third aspect, a computer device is provided according to an embodiment of the present invention, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor implements the real-time fluorescence quantitative PCR data processing method described in any one of the first aspects by executing the computer instructions.

[0043] In a fourth aspect, a non-transitory computer-readable storage medium is provided according to an embodiment of the present invention, wherein the non-transitory computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the real-time fluorescence quantitative PCR data processing method described in any one of the first aspects is implemented.

[0044] The real-time fluorescence quantitative PCR data processing method and device provided by the embodiments of the present invention have at least the following beneficial effects:

[0045] The real-time fluorescence quantitative PCR data processing method and device provided by the embodiment of the present invention can obtain the measured fluorescence data corresponding to each cycle node in the collected target sample, and use the preset crosstalk correction model to perform fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data to obtain the denoised fluorescence data corresponding to each cycle node in the target sample. Then, the crosstalk influence of the collected measured fluorescence data is eliminated, the validity of the collected data is ensured, the crosstalk interference of the fluorescence data is reduced, and the accuracy of negative and positive judgments is improved. By using the preset crosstalk correction model, the measured fluorescence data of different sampling holes and different sampling channels can be crosstalk corrected and uniformity corrected, ensuring the applicability of real-time fluorescence quantitative PCR data processing. It is ensured that the measured fluorescence data collected from the sampling holes in different areas of the entire sample plate can be processed, which improves the efficiency of real-time fluorescence quantitative PCR data processing.

[0046] By performing linear fitting processing on the corresponding denoised fluorescence data, the target linear mathematical model is obtained, the slope model of the target linear mathematical model at each cycle node is determined, and the slope model is second-order derivation is performed on the slope model to obtain the second-order derivative expression, and the cycle node corresponding to the baseline period end point is determined according to the extreme value of the second-order derivative expression. And according to the cycle node corresponding to the baseline period end point, a baseline node set is selected from the cycle nodes of the target sample, and the baseline correction model is obtained by combining the denoised fluorescence data and the slope model corresponding to the cycle node corresponding to the baseline period end point. The denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected according to the baseline correction model to obtain the target fluorescence data corresponding to each cycle node in the target sample. By performing linear fitting processing on the denoised fluorescence data and determining the corresponding slope model, the cycle node corresponding to the baseline period end point is determined by second-order derivation, so as to accurately find the baseline period end point for subsequent data processing.

[0047] By performing baseline correction on the denoised fluorescence data, the corresponding target fluorescence data is obtained, thereby reducing the problems of tilt and jitter of the baseline part of the denoised fluorescence data on the basis of the denoised fluorescence data, further ensuring the validity of the target fluorescence data and improving the data processing efficiency of real-time fluorescence quantitative PCR. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 This is a flowchart of a specific example of the real-time fluorescence quantitative PCR data processing method in Example 1 of the present invention;

[0050] Figure 2 This is a schematic diagram of the structure of a sample plate of the real-time fluorescence quantitative PCR data processing method in Example 1 of the present invention;

[0051] Figure 3 A fluorescence distribution diagram corresponding to a sample plate of the real-time fluorescence quantitative PCR data processing method in Example 1 of the present invention;

[0052] Figure 4 This is a schematic diagram of data before baseline correction processing of the real-time fluorescence quantitative PCR data processing method in Example 1 of the present invention;

[0053] Figure 5This is a schematic diagram of data after baseline correction processing of the real-time fluorescence quantitative PCR data processing method in Example 1 of the present invention;

[0054] Figure 6 is a principle block diagram of a specific example of the real-time fluorescence quantitative PCR data processing device in Example 2 of the present invention;

[0055] Figure 7 This is a schematic diagram of a specific example of a computer device in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0056] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0058] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can also be the internal connection of two components, it can be a wireless connection, or it can be a wired connection. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0059] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0060] Although the processes described below include multiple operations that appear in a specific order, it should be clearly understood that these processes may also include more or fewer operations, and these operations may be performed sequentially or in parallel.

[0061] Example 1

[0062] This embodiment provides a real-time fluorescence quantitative PCR data processing method, see Figure 1 As shown, the following steps are included:

[0063] Step S101, obtaining the measured fluorescence data corresponding to each cycle node in the collected target sample, performing fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model, and obtaining the denoised fluorescence data corresponding to each cycle node in the target sample;

[0064] Step S102, performing linear fitting processing on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain a target linear mathematical model, determining a slope model of the target linear mathematical model at each cycle node, and performing second-order derivative of the slope model to obtain a second-order derivative expression, and determining the cycle node corresponding to the end point of the baseline period according to the extreme value of the second-order derivative expression, wherein the cycle node corresponding to the end point of the baseline period is located before the maximum point of the second-order derivative expression, and the cycle node corresponding to the end point of the baseline period is the minimum point closest to the maximum point;

[0065] Step S103, according to the cycle node corresponding to the end point of the baseline period, select a baseline node set from the cycle nodes of the target sample, combine the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model to obtain a baseline correction model, and perform baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline correction model to obtain target fluorescence data corresponding to each cycle node in the target sample.

[0066] In the above embodiment, specifically, the measured fluorescence data corresponding to each cycle node in the target sample is the fluorescence data obtained by collecting the fluorescent dye machine in the target sampling hole through the target sampling channel. The obtained measured fluorescence data carries the identification information of the target sampling hole and the identification information of the target sampling channel. In the preset crosstalk correction model, correction parameter data corresponding to each sampling channel of each sampling hole is pre-stored. When the obtained measured fluorescence data is subjected to fluorescence crosstalk correction and uniformity correction, the target correction parameter corresponding to the identification information of the target sampling hole and the identification information of the target sampling channel is selected from the pre-stored correction parameter data, and then according to the preset crosstalk correction model after determining the target parameter, the measured fluorescence data is subjected to fluorescence crosstalk correction and uniformity correction, and the denoised fluorescence data corresponding to each cycle node in the target sample is obtained. Through the preset crosstalk correction model, the corresponding correction coefficient is selected, and then the crosstalk correction and uniformity correction are performed on each sampling channel corresponding to each sampling hole, so as to reduce the influence of fluorescence crosstalk on the collected fluorescence data. At the same time, since the degree of crosstalk and uniformity of each sampling hole corresponding to each sampling channel is different, by selecting the corresponding correction coefficient, each sampling hole corresponding to each sampling channel can be accurately corrected. The denoised fluorescence data corresponding to each cycle node in the target sample is obtained, and the influence of background fluorescence noise is eliminated when performing crosstalk correction and uniformity correction.

[0067] In the above embodiment, specifically, linear fitting processing is performed based on the denoised fluorescence data to obtain a target linear mathematical model, and a slope model of the target linear mathematical model at each cycle node is determined. A second-order derivative expression is obtained by performing a second-order derivative on the slope model, and the cycle node corresponding to the baseline period endpoint is determined based on the extreme value of the second-order derivative expression. By determining the corresponding baseline period endpoint based on the denoised fluorescence data, rather than determining the corresponding baseline period endpoint based on the measured fluorescence data, the baseline period endpoint can be accurately found, thereby facilitating subsequent correction and calculation.

[0068] In the above embodiment, specifically, after determining the cycle node corresponding to the end point of the baseline period, a baseline node set is selected from the cycle nodes of the target sample, that is, the cycle node from the baseline period start point to the cycle node corresponding to the baseline period end point is selected. Among them, the baseline period start point can be determined according to the corresponding actual needs, for example, the baseline period start point is set to a fixed value (3 to 6). Combined with the denoised fluorescence data corresponding to the cycle node corresponding to the baseline period end point, the baseline correction model is obtained, and the denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected according to the baseline correction model to obtain the target fluorescence data corresponding to each cycle node in the target sample. The slope parameter corresponding to the baseline correction model is obtained by the slope model, for example, the average slope corresponding to the baseline node set is determined as the corresponding slope parameter, that is, the slope values ​​of all nodes in the corresponding baseline node set in the slope model are determined, and the average value is obtained as the slope parameter corresponding to the baseline correction model. And the corresponding correction parameter is determined according to the denoised fluorescence data corresponding to the baseline period end point to determine the corresponding correction baseline, and the denoised fluorescence data is baseline corrected to obtain the corresponding target fluorescence data, so as to solve the tilt and jitter problems in the baseline part of the denoised fluorescence data.

[0069] In the above-mentioned embodiment, by obtaining the measured fluorescence data corresponding to each cycle node in the collected target sample, the measured fluorescence data is subjected to fluorescence crosstalk correction and uniformity correction using a preset crosstalk correction model, and the denoised fluorescence data corresponding to each cycle node in the target sample is obtained. The crosstalk influence of the collected measured fluorescence data is then eliminated, the validity of the collected data is ensured, the crosstalk interference of the fluorescence data is reduced, and the accuracy of negative-positive judgment is improved. By using a preset crosstalk correction model, crosstalk correction and uniformity correction can be performed on the measured fluorescence data of different sampling holes and different sampling channels, ensuring the applicability of real-time fluorescence quantitative PCR data processing. It is ensured that the measured fluorescence data collected from the sampling holes in different areas of the entire sample plate can be processed, thereby improving the efficiency of real-time fluorescence quantitative PCR data processing.

[0070] By performing linear fitting processing on the corresponding denoised fluorescence data, the target linear mathematical model is obtained, the slope model of the target linear mathematical model at each cycle node is determined, and the slope model is second-order derivation is performed on the slope model to obtain the second-order derivative expression, and the cycle node corresponding to the baseline period end point is determined according to the extreme value of the second-order derivative expression. And according to the cycle node corresponding to the baseline period end point, a baseline node set is selected from the cycle nodes of the target sample, and the baseline correction model is obtained by combining the denoised fluorescence data and the slope model corresponding to the cycle node corresponding to the baseline period end point. The denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected according to the baseline correction model to obtain the target fluorescence data corresponding to each cycle node in the target sample. By performing linear fitting processing on the denoised fluorescence data and determining the corresponding slope model, the cycle node corresponding to the baseline period end point is determined by second-order derivation, so as to accurately find the baseline period end point for subsequent data processing.

[0071] By performing baseline correction on the denoised fluorescence data, the corresponding target fluorescence data is obtained, thereby reducing the problems of tilt and jitter of the baseline part of the denoised fluorescence data on the basis of the denoised fluorescence data, further ensuring the validity of the target fluorescence data and improving the data processing efficiency of real-time fluorescence quantitative PCR.

[0072] In one embodiment, the step of acquiring the measured fluorescence data corresponding to each cycle node in the collected target sample, and performing fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model to obtain the denoised fluorescence data corresponding to each cycle node in the target sample includes:

[0073] According to the measured fluorescence data corresponding to each cycle node in the target sample, the corresponding target crosstalk correction coefficient, target uniformity correction coefficient, and target background fluorescence data in the preset crosstalk correction model are determined;

[0074] According to the target crosstalk correction coefficient and the target background fluorescence data, a fluorescence crosstalk correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample through a preset crosstalk correction model;

[0075] According to the target uniformity correction coefficient, a uniformity correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample after the fluorescence crosstalk correction process through a preset crosstalk correction model, and denoised fluorescence data corresponding to each cycle node in the target sample is obtained;

[0076] Among them, the measured fluorescence data corresponding to each cycle node in the target sample carries the identification information of the corresponding target sample, and the identification information includes the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample; the target crosstalk correction coefficient is adapted to the sampling channel corresponding to the target sample, the target uniformity correction coefficient is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample, and the target background fluorescence data is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample.

[0077] In the above embodiment, specifically, according to the target crosstalk correction coefficient and the target background fluorescence data corresponding to the measured fluorescence data, the fluorescence data after the background noise is removed is obtained through the measured fluorescence data and the target background fluorescence data, and then the fluorescence data after the background noise is removed is subjected to crosstalk correction processing according to the corresponding target crosstalk correction coefficient. The interference of background noise on the measured fluorescence data is reduced, and the crosstalk correction processing is performed using the determined corresponding crosstalk coefficient to eliminate the fluorescence crosstalk interference. This ensures the accuracy of subsequent data processing.

[0078] Since the fluorescence data collected from the sampling wells in different areas of the sample plate are not consistent, see Figure 2 As shown, Figure 2 In the sample well plate shown, area 1 corresponds to the middle area, and area 2 corresponds to the edge area. The fluorescence data collected by each sampling well in area 1 is inconsistent with that collected by each sampling well in area 2. Therefore, uniformity correction is performed using a uniformity correction coefficient to reduce the differences between the corresponding sampling wells. The fluorescence distribution diagram of each collection well in the sample well plate after uniformity correction is shown in Figure 1. Figure 3 As shown. According to the actual measured fluorescence data, the corresponding target crosstalk correction coefficient, target uniformity correction coefficient, and target background fluorescence data in the preset crosstalk correction model are determined; according to the target crosstalk correction coefficient and the target background fluorescence data, the measured fluorescence data is subjected to fluorescence crosstalk correction processing through the preset crosstalk correction model; according to the target uniformity correction coefficient, the measured fluorescence data after the fluorescence crosstalk correction processing is subjected to uniformity correction processing, and the corresponding denoised fluorescence data is obtained. In this way, the background noise influence, fluorescence crosstalk interference, uniformity difference and other inaccurate factors existing in the measured fluorescence data are reduced, the accuracy of the denoised fluorescence data obtained after processing is ensured, and it is convenient to use it as the original data for subsequent data processing, thereby ensuring the efficiency of real-time fluorescence quantitative PCR data processing and improving the accuracy of fluorescence quantitative PCR judgment.

[0079] In one embodiment, the fluorescence crosstalk correction processing is performed on the measured fluorescence data corresponding to each cycle node in the target sample by a preset crosstalk correction model according to the target crosstalk correction coefficient and the target background fluorescence data, including:

[0080] Calculate the difference between the measured fluorescence data corresponding to each cycle node in the target sample and the target background fluorescence data to obtain the fluorescence data corresponding to each cycle node in the target sample with background noise removed;

[0081] According to the target crosstalk correction coefficient, fluorescence crosstalk correction processing is performed on the fluorescence data corresponding to each cycle node in the target sample from which background noise is removed, so as to obtain crosstalk-corrected fluorescence data corresponding to each cycle node in the target sample.

[0082] In the above embodiment, specifically, the background noise of the measured fluorescence data is removed by calculating the difference between the measured fluorescence data and the background fluorescence data, and the fluorescence crosstalk correction process is performed after the background noise is removed. Before the fluorescence crosstalk correction process, the step of removing the background noise is considered to reduce the interference of the background fluorescence noise on the measured fluorescence data, thereby ensuring the accuracy of the fluorescence quantitative PCR data processing and further improving the accuracy of the fluorescence quantitative PCR judgment.

[0083] In one implementation, the preset crosstalk correction model is:

[0084] f i =M nm -1 ×[O i -A mn ]

[0085] Y i =X mn ×f i

[0086] Among them, f i is the crosstalk-corrected fluorescence data obtained by correcting the fluorescence crosstalk after removing the background noise corresponding to the i-th cycle node; M nm -1 is the crosstalk correction coefficient of the target sample corresponding to n sampling holes and m sampling channels; i is the measured fluorescence data corresponding to the i-th cycle node; A mn Y is the background fluorescence data corresponding to the target sample’s m sampling channel and n sampling hole; i is the denoised fluorescence data corresponding to the i-th cycle node; X mn is the uniformity correction coefficient corresponding to the m sampling channels and n sampling holes of the target sample.

[0087] In the above embodiment, specifically, through the above preset crosstalk correction model, it can be applied to the correction processing of the measured fluorescence data of each sampling channel corresponding to each sampling hole, thereby improving the efficiency and accuracy of fluorescence quantitative PCR data processing, and further improving the accuracy of fluorescence quantitative PCR judgment.

[0088] In one embodiment, performing a second-order derivative on the slope model to obtain a second-order derivative expression includes:

[0089] Taking a first-order derivative of the slope model to obtain a first-order derivative expression;

[0090] The first-order derivative expression is smoothed, and the first-order derivative expression after the smoothing is first-order differentiated to obtain a second-order derivative expression.

[0091] In the above embodiment, specifically, after the slope model is firstly derivatized to obtain the first-order derivative expression, the first-order derivative expression is firstly smoothed and then derivatized. This reduces the noise of the first-order derivative expression data, thereby further improving the accuracy of the node corresponding to the end point of the baseline period. This further improves the efficiency and accuracy of the fluorescence quantitative PCR data processing, thereby further improving the accuracy of the fluorescence quantitative PCR judgment.

[0092] In one embodiment, according to the cycle node corresponding to the end point of the baseline period, a baseline node set is selected from the cycle nodes of the target sample, and a baseline correction model is obtained by combining the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model. According to the baseline correction model, the denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected to obtain the target fluorescence data corresponding to each cycle node in the target sample, including:

[0093] According to a preset baseline period starting point determination rule, a cycle node corresponding to the baseline period starting point is determined from the cycle nodes of the target sample, and nodes from the cycle node corresponding to the baseline period starting point to the cycle node corresponding to the baseline period end point are selected from the cycle nodes of the target sample as a baseline node set;

[0094] Determining slope data of all loop nodes in the slope model corresponding to the baseline node set, and determining slope parameters of the baseline correction model according to the slope data of all loop nodes;

[0095] Determining correction parameters of the baseline correction model according to the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period;

[0096] According to the baseline correction model after determining the slope parameter and the correction parameter, baseline correction is performed on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain the target fluorescence data corresponding to each cycle node in the target sample;

[0097] The baseline correction model is:

[0098] J i =Y i-(a×ib)

[0099] Among them, i is the i-th loop node, Y i is the denoised fluorescence data corresponding to the i-th cycle node; a is the slope parameter, b is the correction parameter, J i is the target fluorescence data obtained by baseline correction of the denoised fluorescence data corresponding to the i-th cycle node.

[0100] In the above embodiment, specifically, according to the preset baseline period starting point determination rule, the cycle node corresponding to the baseline period starting point is determined from the cycle nodes of the target sample, for example, the baseline period starting point is set to a fixed value 3, that is, cycle node 3. The nodes from the cycle node 3 corresponding to the baseline period starting point to the cycle node e corresponding to the baseline period end point are selected from the cycle nodes of the target sample as the baseline node set. The slope data K corresponding to the cycle node 3 to the cycle node e in the slope model is determined. i , (3≤i≤e), and determine the slope parameter of the baseline correction model. Exemplarily, determine K3 to K e The average slope is the slope parameter of the baseline correction model. According to the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period, the correction parameters of the baseline correction model are determined; for example, after determining the slope parameters, the cycle node e and the corresponding denoised fluorescence data are brought in to determine the corresponding correction parameters and the corresponding baseline correction model. Then, the denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected to obtain the target fluorescence data corresponding to each cycle node in the target sample.

[0101] In the above embodiment, specifically, by determining the corresponding baseline node set, according to the baseline node set and the slope model, the slope parameter corresponding to the baseline correction model is obtained, and according to the denoised fluorescence data corresponding to the end point of the baseline period, the correction parameter corresponding to the baseline correction model is determined, thereby performing baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample, and obtaining the target fluorescence data corresponding to each cycle node in the target sample. Exemplarily, the data before baseline correction processing is as follows Figure 4 The data after baseline correction is shown in Figure 5 As shown in the figure, on the basis of eliminating the noise of the fluorescence data, the problems of the tilt and jitter of the baseline part of the fluorescence data are reduced, which further ensures the validity of the target fluorescence data and improves the data processing efficiency of the real-time fluorescence quantitative PCR.

[0102] In one embodiment, before obtaining the measured fluorescence data corresponding to each cycle node in the collected target sample, the method further includes:

[0103] a), acquiring the first fluorescence data of each sampling channel corresponding to each sampling well in the first sample plate, and obtaining the background fluorescence data of each sampling channel corresponding to each sampling well, wherein the first sample plate is a water preparation sample plate;

[0104] b) acquiring the collected second fluorescence data of each sampling channel corresponding to each sampling well in the second sample plate, determining the sampling channel corresponding to the unit coefficient for each sampling well, and determining the crosstalk correction coefficient of each sampling channel corresponding to each sampling well, wherein the second sample plate is a sample plate prepared with a pure color fluorescent dye;

[0105] c) Obtain the collected third fluorescence data of each sampling channel corresponding to each sampling well in the third sample plate, determine the sampling well corresponding to the unit coefficient for each sampling channel, and determine the uniform correction coefficient of each sampling well corresponding to each sampling channel, wherein the third sample plate is a sample plate prepared with a full-spectrum mixed-color fluorescent dye.

[0106] In the above embodiment, specifically, different pure color fluorescent dyes are selected to prepare the sample plate, and step b is repeated to obtain the crosstalk correction coefficient of each sampling hole corresponding to each sampling channel of any dye. Through the above steps a, b, and c, the background fluorescence data of each sampling hole corresponding to each sampling channel, the crosstalk correction coefficient of each sampling hole corresponding to each sampling channel of any dye, and the uniform correction coefficient of each sampling hole corresponding to each sampling channel are stored in the preset crosstalk correction model. Through the above preprocessing steps, the data processing efficiency of real-time fluorescence quantitative PCR is further improved, and the effectiveness of the target fluorescence data processing is guaranteed.

[0107] Example 2

[0108] This embodiment provides a real-time fluorescence quantitative PCR data processing device. This embodiment is described by applying the real-time fluorescence quantitative PCR data processing device to the real-time fluorescence quantitative PCR data processing method described in the above embodiment 1. The real-time fluorescence quantitative PCR data processing device, such as Figure 6 As shown, it includes at least the following modules:

[0109] A denoising module 61 is used to obtain the measured fluorescence data corresponding to each cycle node in the collected target sample, and perform fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model to obtain denoised fluorescence data corresponding to each cycle node in the target sample;

[0110] The fixed-point module 62 is used to perform linear fitting processing on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain a target linear mathematical model, determine the slope model of the target linear mathematical model at each cycle node, and perform second-order derivative of the slope model to obtain a second-order derivative expression, and determine the cycle node corresponding to the end point of the baseline period according to the extreme value of the second-order derivative expression, wherein the cycle node corresponding to the end point of the baseline period is located before the maximum point of the second-order derivative expression, and the cycle node corresponding to the end point of the baseline period is the minimum point closest to the maximum point;

[0111] The base correction module 63 is used to select a baseline node set from the cycle nodes of the target sample according to the cycle node corresponding to the end point of the baseline period, combine the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model to obtain a baseline correction model, and perform baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline correction model to obtain the target fluorescence data corresponding to each cycle node in the target sample.

[0112] The real-time fluorescence quantitative PCR data processing device provided in the embodiment of the present application can be used for the real-time fluorescence quantitative PCR data processing method performed in the above embodiment 1. For relevant details, refer to the above method embodiment. The implementation principle and technical effect are similar and will not be repeated here.

[0113] It should be noted that: the real-time fluorescence quantitative PCR data processing device provided in the above embodiment only uses the division of the above functional modules as an example when performing real-time fluorescence quantitative PCR data processing. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the real-time fluorescence quantitative PCR data processing device is divided into different functional modules to complete all or part of the functions described above. In addition, the real-time fluorescence quantitative PCR data processing device provided in the above embodiment and the real-time fluorescence quantitative PCR data processing method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0114] Example 3

[0115] See also Figure 7 As shown, the embodiment of the present invention further provides a computer device, which can be a desktop computer, a laptop computer, a palm computer, a cloud server, etc. The computer device may include, but is not limited to, a processor and a memory, wherein the processor and the memory may be connected via a bus or other means.

[0116] The processor may be a central processing unit (CPU) or other general-purpose processors, a digital signal processor (DSP), a graphics processor (GPU), an embedded neural network processor (NPU) or other dedicated deep learning coprocessors, application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components and other chips, or a combination of the above chips.

[0117] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the method in the above method implementation. The processor executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory, that is, implementing the method in the above method implementation.

[0118] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required by at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The one or more modules are stored in the memory, and when executed by the processor, the method in the above-mentioned method implementation is executed.

[0119] The embodiment of the present invention also provides a non-transitory computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions can execute the method in the above method implementation. Among them, the non-transitory computer-readable storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (HDD) or a solid-state drive (SSD), etc.; the non-transitory computer-readable storage medium can also include a combination of the above-mentioned types of memory.

[0120] Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, apparatuses, computer devices or non-transitory computer-readable storage media, all of which may relate to or include computer program products.

[0121] Therefore, the present invention can be implemented in full hardware, full software, or in the form of a combination of software and hardware. Moreover, the present invention can be implemented in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0122] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0123] Obviously, the above-mentioned embodiments only express several embodiments of the present application, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, other different forms of changes or modifications can be made on the basis of the above description without departing from the concept of the present application. It is not necessary and impossible to list all the embodiments here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention. Therefore, the scope of protection of the patent of this application shall be based on the attached claims.

Claims

1. A real-time fluorescence quantitative PCR data processing method, characterized in that: include: Acquire the measured fluorescence data corresponding to each cycle node in the collected target sample, perform fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model, and obtain the denoised fluorescence data corresponding to each cycle node in the target sample; Performing linear fitting processing on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain a target linear mathematical model, determining a slope model of the target linear mathematical model at each cycle node, performing second-order derivative on the slope model to obtain a second-order derivative expression, and determining the cycle node corresponding to the end point of the baseline period according to the extreme value of the second-order derivative expression, wherein the cycle node corresponding to the end point of the baseline period is located before the maximum point of the second-order derivative expression, and the cycle node corresponding to the end point of the baseline period is the minimum point closest to the maximum point; According to the cycle node corresponding to the end point of the baseline period, a baseline node set is selected from the cycle nodes of the target sample, and a baseline correction model is obtained by combining the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model. According to the baseline correction model, the denoised fluorescence data corresponding to each cycle node in the target sample is baseline corrected to obtain target fluorescence data corresponding to each cycle node in the target sample; The step of acquiring the measured fluorescence data corresponding to each cycle node in the collected target sample, and performing fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model to obtain the denoised fluorescence data corresponding to each cycle node in the target sample includes: According to the measured fluorescence data corresponding to each cycle node in the target sample, the corresponding target crosstalk correction coefficient, target uniformity correction coefficient, and target background fluorescence data in the preset crosstalk correction model are determined; According to the target crosstalk correction coefficient and the target background fluorescence data, a fluorescence crosstalk correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample through a preset crosstalk correction model; According to the target uniformity correction coefficient, a uniformity correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample after the fluorescence crosstalk correction process through a preset crosstalk correction model, and denoised fluorescence data corresponding to each cycle node in the target sample is obtained; The measured fluorescence data corresponding to each cycle node in the target sample carries identification information of the corresponding target sample, and the identification information includes the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample; the target crosstalk correction coefficient is adapted to the sampling channel corresponding to the target sample, the target uniformity correction coefficient is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample, and the target background fluorescence data is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample; The method of performing fluorescence crosstalk correction processing on the measured fluorescence data corresponding to each cycle node in the target sample by using a preset crosstalk correction model according to the target crosstalk correction coefficient and the target background fluorescence data includes: Calculate the difference between the measured fluorescence data corresponding to each cycle node in the target sample and the target background fluorescence data to obtain the fluorescence data corresponding to each cycle node in the target sample with background noise removed; According to the target crosstalk correction coefficient, the fluorescence data corresponding to each cycle node in the target sample and from which background noise has been removed are subjected to fluorescence crosstalk correction processing to obtain crosstalk-corrected fluorescence data corresponding to each cycle node in the target sample; The preset crosstalk correction model is: f i =M nm -1 ×[O i -A mn ] AND i =X mn ×f i Among them, f i is the crosstalk-corrected fluorescence data obtained by correcting the fluorescence crosstalk after removing the background noise corresponding to the i-th cycle node; M nm -1 is the crosstalk correction coefficient of the target sample corresponding to n sampling holes and m sampling channels; i is the measured fluorescence data corresponding to the i-th cycle node; A mn Y is the background fluorescence data corresponding to the target sample’s m sampling channel and n sampling hole; i is the denoised fluorescence data corresponding to the i-th cycle node; X mn is the uniformity correction coefficient corresponding to the m sampling channels and n sampling holes corresponding to the target sample; The method comprises: selecting a baseline node set from the cycle nodes of the target sample according to the cycle nodes corresponding to the baseline period endpoint, combining the denoised fluorescence data corresponding to the cycle nodes corresponding to the baseline period endpoint and the slope model to obtain a baseline correction model; performing baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline correction model to obtain target fluorescence data corresponding to each cycle node in the target sample, including: According to a preset baseline period starting point determination rule, a cycle node corresponding to the baseline period starting point is determined from the cycle nodes of the target sample, and nodes from the cycle node corresponding to the baseline period starting point to the cycle node corresponding to the baseline period end point are selected from the cycle nodes of the target sample as a baseline node set; Determining slope data of all loop nodes in the slope model corresponding to the baseline node set, and determining slope parameters of the baseline correction model according to the slope data of all loop nodes; Determine the correction parameters of the baseline correction model according to the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period; perform baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline correction model after the slope parameter and the correction parameter are determined, and obtain the target fluorescence data corresponding to each cycle node in the target sample; The baseline correction model is: J i =Y i -(a×i-b) Among them, i is the i-th loop node, Y i is the denoised fluorescence data corresponding to the i-th cycle node; a is the slope parameter, b is the correction parameter, J i is the target fluorescence data obtained by baseline correction of the denoised fluorescence data corresponding to the i-th cycle node.

2. The real-time fluorescence quantitative PCR data processing method according to claim 1, characterized in that: The second-order derivative expression obtained by performing a second-order derivative on the slope model includes: Taking a first-order derivative of the slope model to obtain a first-order derivative expression; The first-order derivative expression is smoothed, and the first-order derivative expression after the smoothing is first-order differentiated to obtain a second-order derivative expression.

3. The real-time fluorescence quantitative PCR data processing method according to claim 2, characterized in that: Before obtaining the measured fluorescence data corresponding to each cycle node in the collected target sample, it also includes: Acquire the collected first fluorescence data of each sampling channel corresponding to each sampling well in the first sample plate, and obtain the background fluorescence data of each sampling channel corresponding to each sampling well, wherein the first sample plate is a water preparation sample plate; Acquire the collected second fluorescence data of each sampling channel corresponding to each sampling well in the second sample plate, determine the sampling channel corresponding to the unit coefficient for each sampling well, and determine the crosstalk correction coefficient of each sampling channel corresponding to each sampling well, wherein the second sample plate is a sample plate prepared with a pure color fluorescent dye; Obtain the collected third fluorescence data of each sampling channel corresponding to each sampling well in the third sample plate, determine the sampling well corresponding to the unit coefficient for each sampling channel, and determine the uniform correction coefficient of each sampling well corresponding to each sampling channel, wherein the third sample plate is a sample plate prepared with a full-spectrum mixed-color fluorescent dye.

4. A real-time fluorescence quantitative PCR data processing device, characterized in that: include: A denoising module is used to obtain the measured fluorescence data corresponding to each cycle node in the collected target sample, and perform fluorescence crosstalk correction and uniformity correction processing on the measured fluorescence data through a preset crosstalk correction model to obtain denoised fluorescence data corresponding to each cycle node in the target sample; A fixed-point module, used for performing linear fitting processing on the denoised fluorescence data corresponding to each cycle node in the target sample to obtain a target linear mathematical model, determining a slope model of the target linear mathematical model at each cycle node, and performing a second-order derivative on the slope model to obtain a second-order derivative expression, and determining the cycle node corresponding to the end point of the baseline period according to the extreme value of the second-order derivative expression, wherein the cycle node corresponding to the end point of the baseline period is located before the maximum point of the second-order derivative expression, and the cycle node corresponding to the end point of the baseline period is the minimum point closest to the maximum point; A base calibration module, for selecting a baseline node set from the cycle nodes of the target sample according to the cycle node corresponding to the end point of the baseline period, combining the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period and the slope model to obtain a baseline calibration model, and performing baseline calibration on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline calibration model to obtain target fluorescence data corresponding to each cycle node in the target sample; Wherein, the noise reduction module specifically includes: According to the measured fluorescence data corresponding to each cycle node in the target sample, the corresponding target crosstalk correction coefficient, target uniformity correction coefficient, and target background fluorescence data in the preset crosstalk correction model are determined; According to the target crosstalk correction coefficient and the target background fluorescence data, a fluorescence crosstalk correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample through a preset crosstalk correction model; According to the target uniformity correction coefficient, a uniformity correction process is performed on the measured fluorescence data corresponding to each cycle node in the target sample after the fluorescence crosstalk correction process through a preset crosstalk correction model, and denoised fluorescence data corresponding to each cycle node in the target sample is obtained; The measured fluorescence data corresponding to each cycle node in the target sample carries identification information of the corresponding target sample, and the identification information includes the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample; the target crosstalk correction coefficient is adapted to the sampling channel corresponding to the target sample, the target uniformity correction coefficient is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample, and the target background fluorescence data is adapted to the sampling hole corresponding to the target sample and the sampling channel corresponding to the target sample; The method of performing fluorescence crosstalk correction processing on the measured fluorescence data corresponding to each cycle node in the target sample by using a preset crosstalk correction model according to the target crosstalk correction coefficient and the target background fluorescence data includes: Calculate the difference between the measured fluorescence data corresponding to each cycle node in the target sample and the target background fluorescence data to obtain the fluorescence data corresponding to each cycle node in the target sample with background noise removed; According to the target crosstalk correction coefficient, the fluorescence data corresponding to each cycle node in the target sample and from which background noise has been removed are subjected to fluorescence crosstalk correction processing to obtain crosstalk-corrected fluorescence data corresponding to each cycle node in the target sample; The preset crosstalk correction model is: f i =M nm -1 ×[O i -A mn ] AND i =X mn ×f i Among them, f i is the crosstalk-corrected fluorescence data obtained by correcting the fluorescence crosstalk after removing the background noise corresponding to the i-th cycle node; M nm -1 is the crosstalk correction coefficient of the target sample corresponding to n sampling holes and m sampling channels; i is the measured fluorescence data corresponding to the i-th cycle node; A mn Y is the background fluorescence data corresponding to the target sample’s m sampling channel and n sampling hole; i is the denoised fluorescence data corresponding to the i-th cycle node; X mn is the uniformity correction coefficient corresponding to the m sampling channels and n sampling holes corresponding to the target sample; The basic calibration module specifically includes: According to a preset baseline period starting point determination rule, a cycle node corresponding to the baseline period starting point is determined from the cycle nodes of the target sample, and nodes from the cycle node corresponding to the baseline period starting point to the cycle node corresponding to the baseline period end point are selected from the cycle nodes of the target sample as a baseline node set; Determining slope data of all loop nodes in the slope model corresponding to the baseline node set, and determining slope parameters of the baseline correction model according to the slope data of all loop nodes; Determine the correction parameters of the baseline correction model according to the denoised fluorescence data corresponding to the cycle node corresponding to the end point of the baseline period; perform baseline correction on the denoised fluorescence data corresponding to each cycle node in the target sample according to the baseline correction model after the slope parameter and the correction parameter are determined, and obtain the target fluorescence data corresponding to each cycle node in the target sample; The baseline correction model is: J i =Y i -(a×i-b) Among them, i is the i-th loop node, Y i is the denoised fluorescence data corresponding to the i-th cycle node; a is the slope parameter, b is the correction parameter, J i is the target fluorescence data obtained by baseline correction of the denoised fluorescence data corresponding to the i-th cycle node.

5. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the real-time fluorescence quantitative PCR data processing method according to any one of claims 1 to 3 by executing the computer instructions.

6. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the real-time fluorescence quantitative PCR data processing method according to any one of claims 1 to 3 is implemented.

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