阅读说明：本技术 扩增曲线基线确定方法、装置以及电子设备 (Amplification curve baseline determination method and device and electronic equipment ) 是由 李冬 杨智 贺贤汉 于 2020-12-30 设计创作，主要内容包括：本申请提供了一种扩增曲线基线确定方法、装置以及电子设备,涉及数据检测技术领域,包括：获取未知样本扩增数据,利用聚类分析法从未知样本扩增数据中确定明显扩增样本和非明显扩增样本,利用线性拟合方法确定明显扩增样本的扩增曲线基线以及最短基线期,基于最短基线期确定非明显扩增样本的扩增曲线基线,以缓解了目前的核酸定量方法无法获得真实的扩增曲线技术问题。(The application provides an amplification curve baseline determination method, an amplification curve baseline determination device and electronic equipment, which relate to the technical field of data detection and comprise the following steps: acquiring unknown sample amplification data, determining an obvious amplification sample and an unobvious amplification sample from the unknown sample amplification data by using a cluster analysis method, determining an amplification curve baseline and a shortest baseline period of the obvious amplification sample by using a linear fitting method, and determining an amplification curve baseline of the unobvious amplification sample based on the shortest baseline period, so as to relieve the technical problem that a real amplification curve cannot be obtained by using the conventional nucleic acid quantitative method.)

1. A method for baseline determination of an amplification curve, the method comprising:

acquiring unknown sample amplification data, and determining an obvious amplification sample and a non-obvious amplification sample from the unknown sample amplification data by using a cluster analysis method;

determining an amplification curve baseline and a shortest baseline period of the obviously amplified sample by using a linear fitting method;

determining an amplification curve baseline for the non-significantly amplified sample based on the shortest baseline period.

2. The method for baseline determination of an amplification curve of claim 1, wherein said step of obtaining amplification data from an unknown sample comprises:

collecting PCR amplification data of unknown samples.

3. The method for determining an amplification curve baseline according to claim 2, wherein the step of determining the clearly amplified sample and the non-clearly amplified sample from the unknown sample amplification data by using a cluster analysis method comprises:

and determining obvious amplification samples and non-obvious amplification samples from the PCR amplification data by utilizing a Savitzky-Golay derivation method and a clustering analysis method.

4. The method for determining the baseline curve of claim 3, wherein the step of determining the significant amplified samples and the non-significant amplified samples from the PCR amplification data by using Savitzky-Golay derivation method and cluster analysis method comprises:

determining a derivative curve of the PCR amplification data by utilizing a Savitzky-Golay derivation method, and searching a maximum value point of the derivative curve;

and determining an obvious amplification sample and a non-obvious amplification sample from the PCR amplification data by utilizing a cluster evaluation index based on the maximum value point, and determining the position of the maximum first derivative corresponding to the obvious amplification sample.

5. The method for determining an amplification curve baseline according to claim 4, wherein the step of determining the amplification curve baseline and the shortest baseline period of the significantly amplified sample by using a linear fitting method comprises:

searching a first slope minimum region of the apparently amplified sample before the position of the maximum first derivative by using a linear fitting method;

searching a first amplification region with fitting degree reaching a first preset value and a first baseline corresponding to the first amplification region in a mode of expanding from the first slope minimum region to two ends;

subtracting the original amplification curve from the first baseline to obtain a first amplification curve with the baseline removed;

combining said first amplification curves of all said apparently amplified samples to determine a shortest baseline period.

6. The method for determining an amplification curve baseline according to claim 1, wherein the step of determining an amplification curve baseline of the non-significantly amplified sample based on the shortest baseline period comprises:

and determining the amplification curve baseline of the non-obviously amplified sample by utilizing a linear fitting method based on the shortest baseline period.

7. The method for determining an amplification curve baseline according to claim 6, wherein the step of determining the amplification curve baseline of the non-significantly amplified sample by using a linear fitting method based on the shortest baseline period comprises:

determining a second slope minimum region of the non-significantly amplified sample using a linear fitting method based on the shortest baseline period;

searching a second amplification region with the fitting degree reaching a second preset value and a second baseline corresponding to the second amplification region in a mode of expanding from the second slope minimum region to two ends;

and subtracting the second baseline from the original amplification curve to obtain a second amplification curve with the baseline removed.

8. An amplification curve baseline determination apparatus, comprising:

the acquisition module is used for acquiring unknown sample amplification data and determining an obvious amplification sample and a non-obvious amplification sample from the unknown sample amplification data by using a cluster analysis method;

a first determination module for determining an amplification curve baseline and a shortest baseline period of the apparently amplified sample by using a linear fitting method;

a second determination module for determining an amplification curve baseline for the non-significantly amplified sample based on the shortest baseline period.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and wherein the processor implements the steps of the method of any of claims 1 to 7 when executing the computer program.

10. A computer readable storage medium having stored thereon computer executable instructions which, when invoked and executed by a processor, cause the processor to execute the method of any of claims 1 to 7.

Technical Field

The present disclosure relates to the field of data detection technologies, and in particular, to a method and an apparatus for determining an amplification curve baseline, and an electronic device.

Background

At present, most of nucleic acid quantitative methods for diagnosing infectious disease standards adopt fluorescence real-time quantitative PCR, can quantify initial values of sample templates, and are often used in gene analysis expression, transgenic food detection and cancer detection.

However, the current actual PCR amplification curves are various, even in the same amplification experiment, the amplification curves of each well site are greatly different, and the existing methods cannot eliminate the influence of the baseline, i.e. the fluorescence background intensity, and are difficult to determine the baseline of each unknown sample. Therefore, the current methods cannot obtain amplification curves with higher accuracy.

Disclosure of Invention

The invention aims to provide an amplification curve baseline determination method, an amplification curve baseline determination device and electronic equipment so as to solve the technical problem that a higher-precision amplification curve cannot be obtained at present.

In a first aspect, an embodiment of the present application provides a method for determining an amplification curve baseline, the method including:

acquiring unknown sample amplification data, and determining an obvious amplification sample and a non-obvious amplification sample from the unknown sample amplification data by using a cluster analysis method;

determining an amplification curve baseline and a shortest baseline period of the obviously amplified sample by using a linear fitting method;

determining an amplification curve baseline for the non-significantly amplified sample based on the shortest baseline period.

With reference to the first aspect, the present invention provides a first possible implementation manner of the first aspect, wherein the step of obtaining amplification data of the unknown sample includes:

collecting PCR amplification data of unknown samples.

With reference to the first aspect, the present invention provides a second possible implementation manner of the first aspect, wherein the step of determining an apparently amplified sample and a non-apparently amplified sample from the unknown sample amplification data by using a cluster analysis method includes:

and determining obvious amplification samples and non-obvious amplification samples from the PCR amplification data by utilizing a Savitzky-Golay derivation method and a clustering analysis method.

In combination with the first aspect, the present invention provides a third possible implementation manner of the first aspect, wherein the step of determining the significant amplified samples and the non-significant amplified samples from the PCR amplification data by using the Savitzky-Golay derivation method and the cluster analysis method includes:

determining a derivative curve of the PCR amplification data by utilizing a Savitzky-Golay derivation method, and searching a maximum value point of the derivative curve;

and determining an obvious amplification sample and a non-obvious amplification sample from the PCR amplification data by utilizing a cluster evaluation index based on the maximum value point, and determining the position of the maximum first derivative corresponding to the obvious amplification sample.

With reference to the first aspect, the present embodiments provide a fourth possible implementation manner of the first aspect, where the step of determining the amplification curve baseline and the shortest baseline period of the significantly amplified sample by using a linear fitting method includes:

searching a first slope minimum region of the apparently amplified sample before the position of the maximum first derivative by using a linear fitting method;

searching a first amplification region with fitting degree reaching a first preset value and a first baseline corresponding to the first amplification region in a mode of expanding from the first slope minimum region to two ends;

subtracting the original amplification curve from the first baseline to obtain a first amplification curve with the baseline removed;

combining said first amplification curves of all said apparently amplified samples to determine a shortest baseline period.

With reference to the first aspect, the present embodiments provide a fifth possible implementation manner of the first aspect, wherein the step of determining the amplification curve baseline of the non-significantly amplified sample based on the shortest baseline period includes:

and determining the amplification curve baseline of the non-obviously amplified sample by utilizing a linear fitting method based on the shortest baseline period.

With reference to the first aspect, the present embodiments provide a sixth possible implementation manner of the first aspect, wherein the step of determining the amplification curve baseline of the non-significantly amplified sample by using a linear fitting method based on the shortest baseline period includes:

determining a second slope minimum region of the non-significantly amplified sample using a linear fitting method based on the shortest baseline period;

searching a second amplification region with the fitting degree reaching a second preset value and a second baseline corresponding to the second amplification region in a mode of expanding from the second slope minimum region to two ends;

and subtracting the second baseline from the original amplification curve to obtain a second amplification curve with the baseline removed.

In a second aspect, embodiments of the present invention provide an amplification curve baseline determination apparatus, including:

the acquisition module is used for acquiring unknown sample amplification data and determining an obvious amplification sample and a non-obvious amplification sample from the unknown sample amplification data by using a cluster analysis method;

a first determination module for determining an amplification curve baseline and a shortest baseline period of the apparently amplified sample by using a linear fitting method;

a second determination module for determining an amplification curve baseline for the non-significantly amplified sample based on the shortest baseline period.

In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, where the memory stores a computer program operable on the processor, and the processor implements the steps of the method according to the first aspect when executing the computer program.

In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to execute the method according to the first aspect.

The embodiment of the application brings the following beneficial effects:

an amplification curve baseline determination method, an amplification curve baseline determination device and electronic equipment provided by the embodiment of the application comprise: firstly, unknown sample amplification data is obtained, an obvious amplification sample and an unobvious amplification sample are determined from the unknown sample amplification data by using a cluster analysis method, then an amplification curve baseline and a shortest baseline period of the obvious amplification sample are determined by using a linear fitting method, and then an amplification curve baseline of the unobvious amplification sample is determined based on the shortest baseline period.

Drawings

In order to more clearly illustrate the detailed description of the present application or the technical solutions in the prior art, the drawings needed to be used in the detailed description of the present application or the prior art description will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a schematic flow chart of a method for determining a baseline amplification curve according to an embodiment of the present disclosure;

FIG. 2 is a schematic flow chart of another method for determining a baseline amplification curve according to an embodiment of the present disclosure;

FIGS. 3(a) and 3(b) are schematic diagrams of raw amplification data of 5 well sites of a PCR detection system in an amplification curve baseline determination method according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a derivative curve of a portion of hole site amplification data in a PCR detection system in a method for determining a baseline of an amplification curve according to an embodiment of the present application;

FIGS. 5(a) and 5(b) are schematic diagrams illustrating analysis results of 5 well sites in a PCR detection system in an amplification curve baseline determination method according to an embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of an augmented curve baseline determination apparatus according to an embodiment of the present application;

fig. 7 is a schematic structural diagram illustrating an electronic device provided in an embodiment of the present application.

Detailed Description

To make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the present application will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

At present, the nucleic acid quantitative method for diagnosing infectious disease standard still mostly adopts fluorescence real-time quantitative PCR, which can quantify the initial value of a sample template and is often used in gene analysis expression, transgenic food detection and cancer detection. In order to determine the Ct value of a sample, in the conventional method, a threshold corresponding to 10 times of standard deviation of a fluorescence signal of 3-15 cycles is generally used as a Ct value determination basis, or fitting is performed by using a sigmoid curve model, Richards curve model and other curve models based on an LM method (Levenberg-Marquardt method), an Akima interpolation method and other methods to obtain a fitting parameter. However, in any case, there is a significant problem of how to eliminate the influence of the baseline, i.e. the fluorescence background intensity, i.e. to determine the baseline of each unknown sample. Only in case the baseline is removed, a true amplification curve can be obtained.

The actual PCR amplification curve is very strange, and even in the same amplification experiment, the amplification curves of all the pore sites are greatly different. But in general, can be divided into two categories: with and without significant amplification. If the same method is used to perform baseline analysis on all unknown samples, it is difficult to avoid the embarrassment of being too general or having slow analysis speed. On the other hand, for an amplification curve without significant amplification characteristics, when the standard is determined with a 10-fold standard deviation as a threshold line, if the baseline period is slightly deviated, it is easy to make the curve with amplification heads eliminated, or to regard the "heads up" within the error range as true amplification.

Based on this, the embodiments of the present application provide an amplification curve baseline determination method, an amplification curve baseline determination device, and an electronic device, which can alleviate the technical problem that the current nucleic acid quantification method cannot obtain a true amplification curve. Firstly, dividing all unknown sample amplification curves into obvious amplification samples and non-obvious amplification samples by using a cluster analysis method, secondly, determining the base line of the obvious amplification samples and the shortest base line period, and finally, determining the base lines of other unknown samples according to the shortest base line period.

The first embodiment is as follows:

fig. 1 is a schematic flow chart of a method for determining a baseline of an amplification curve according to an embodiment of the present disclosure. As shown in fig. 1, the method includes:

and step S110, acquiring amplification data of the unknown sample, and determining an obvious amplification sample and a non-obvious amplification sample from the amplification data of the unknown sample by using a cluster analysis method.

And step S120, determining the amplification curve baseline and the shortest baseline period of the obviously amplified sample by using a linear fitting method.

And step S130, determining the amplification curve baseline of the non-obvious amplification sample based on the shortest baseline period.

By dividing all unknown sample amplification curves into obvious amplification samples and non-obvious amplification samples by using a cluster analysis method, the base lines of the obvious amplification samples and the shortest base line period can be determined, and the base lines of the amplification curves of other non-obvious amplification samples are determined according to the shortest base line period, so that the base lines of the amplification curves with higher precision of the amplification data of the unknown samples can be determined finally, and the technical problem that the amplification curves with higher precision cannot be obtained at present is solved.

In some embodiments, the step of obtaining amplification data of the unknown sample in step S110 specifically includes: step a), collecting PCR amplification data of an unknown sample.

By collecting PCR amplification data of unknown samples, as shown in FIG. 2, all amplification curves of unknown samples can be divided into obvious amplification samples and non-obvious amplification samples.

In some embodiments, the step of determining the significant amplified samples and the non-significant amplified samples from the unknown sample amplification data by using cluster analysis in step S110 includes:

and b), determining an obvious amplification sample and a non-obvious amplification sample from the PCR amplification data by using a Savitzky-Golay derivation method and a cluster analysis method.

It should be noted that the Savitzky-Golay fitting is a smoothing method for realizing least square fitting in a sliding window by using a polynomial, and after obtaining a polynomial coefficient matrix by using the Savitzky-Golay fitting, the corresponding derivative matrix is solved, so that the derivative data of the amplification curve with a smoothing effect can be obtained. Compared with a direct differential method, the Savitzky-Golay derivation method is very suitable for processing amplification curve data with low resolution filtering and few sampling points.

After the derivative data of the amplification curve is obtained, when the derivative value of a certain cycle position is larger than the derivative values corresponding to the cycles on two sides, the derivative value is the maximum value point, and all the maximum value points are found.

Fitting can be carried out by utilizing a Savitzky-Golay derivation method and a clustering analysis method to obtain fitting parameters, and obvious amplification samples and corresponding maximum first-order derivative positions are determined, so that a foundation is laid for determining other amplification curve indexes in the next step, and the method is easy to understand, easy to implement and high in precision.

In some embodiments, the amplification curve baseline determination method, the step b) includes:

step c), determining a derivative curve of the PCR amplification data by using a Savitzky-Golay derivation method, and searching a maximum value point of the derivative curve;

and d), determining an obvious amplification sample and a non-obvious amplification sample from the PCR amplification data by utilizing the clustering evaluation index based on the maximum value point, and determining the position of the maximum first derivative corresponding to the obvious amplification sample.

The maximum value of the derivative is used as one class, the other maximum value points are used as another class, and the clustering is performed by using the clustering evaluation index, i.e., the contour coefficient, and if the overall contour coefficient of the two classes reaches a given threshold (generally set to a value close to 1, for example, 0.99), the two classes are established, and the amplification curve cycle position corresponding to the maximum value is the maximum first derivative position, as shown in fig. 2.

By utilizing a Savitzky-Golay derivation method, a derivative curve of PCR amplification data is determined, a maximum point of the derivative curve is searched, an amplification curve with obvious amplification characteristics can be prevented from having slight deviation in a base line period when a standard deviation of 10 times is used as a standard for determining a threshold line, so that the curve with amplification head-up is eliminated, or the head-up within an error range is regarded as real amplification, and a foundation is laid for ensuring other amplification curve indexes.

In some embodiments, the step S120 specifically includes the following steps:

step e), searching a first slope minimum region of the obviously amplified sample before the position of the maximum first derivative by using a linear fitting method;

step f), searching a first amplification region with the fitting degree reaching a first preset value and a first baseline corresponding to the first amplification region in a mode of expanding from the first slope minimum region to two ends;

step g), subtracting the original amplification curve from the first base line to obtain a first amplification curve with the base line removed;

and h), integrating the first amplification curves of all the obviously amplified samples, and determining the shortest baseline period.

For step e), before the position of the maximum first derivative, an iterative search is performed by using the linear fitting method and using the decision coefficient as an index, as shown in fig. 2, to find the slope minimum region satisfying the minimum region requirement (i.e. the shortest baseline period, such as 5 cycles).

And f), expanding the two ends of the region with the minimum slope, searching an amplification region with the optimal fitting degree and a corresponding base line, namely, respectively extending and fitting the two ends of the region with the minimum slope, and finding out the amplification region with the maximum decision coefficient, namely the region with the optimal fitting degree. If the starting point of the region is base _ begin and the ending point is base _ end, the base period is [ base _ begin, base _ end ]]. Here, the coefficient R is determined²The method comprises the following steps:

wherein, X_nRepresents the actual value of the fluorescence intensity,the values of the fit are expressed as,representing the average value of the actual values, and setting the slope corresponding to the optimal linear fitting as k and the intercept as b, the base line is: yn ═ k × n + b, where yn represents the baseline value of fluorescence intensity for the nth cycle.

For the above step h), an intersection is taken for the linear intervals corresponding to the baseline of each amplification obvious amplification curve, as shown in fig. 2, so that the shortest baseline period can be obtained, and the endpoint of the baseline period is set as min _ base _ interval.

The amplification curve base line and the shortest base line period of the obvious amplification samples are determined by utilizing a linear fitting method, the base line can be subtracted from the original amplification curve to obtain a real amplification curve after the base line is removed, and the amplification curve base lines of all the obvious amplification samples are synthesized to determine the shortest base line period.

In some embodiments, the step S130 may specifically include the following steps:

and i), determining the amplification curve baseline of the non-obvious amplification sample by using a linear fitting method based on the shortest baseline period.

In this step, the region with the minimum slope of the other unknown samples can be determined. And determining the amplification curve baseline of the non-obvious amplification sample through the shortest baseline period, and determining the region with the minimum slope of other unknown samples by using a short baseline period and a linear fitting method.

In some embodiments, the step i) may specifically include the following steps:

step j), based on the shortest baseline period, determining a second slope minimum region of the non-obvious amplification sample by using a linear fitting method;

step k), searching a second amplification region with the fitting degree reaching a second preset value and a second baseline corresponding to the second amplification region in a mode of expanding from the second slope minimum region to two ends;

and step l), subtracting the original amplification curve from the second baseline to obtain the second amplification curve with the baseline removed.

For the above step j), before the end of the shortest baseline period, performing iterative search on other unknown samples by using a linear fitting method and using the decision coefficient as an index, as shown in fig. 2, to find out a sample satisfying the minimum region requirement (note: i.e., shortest baseline period, such as 5 cycles).

The steps k) and l) can be realized according to the specific procedures of the steps f) and g). Illustratively, the two ends are expanded by the region with the minimum slope, the amplification region with the optimal fitting degree and the corresponding base line are searched, and the base line is subtracted on the basis of the original amplification curve to obtain the real amplification curve with the base line removed.

The amplification curve baseline of the unobvious amplification sample is determined by utilizing a linear fitting method, the two ends of the amplification curve baseline can be expanded by using the region with the minimum slope, the amplification region with the optimal fitting degree and the corresponding baseline are searched, and the baseline is subtracted on the basis of the original amplification curve to obtain the real amplification curve with the baseline removed.

In the embodiment of the application, a fluorescence quantitative PCR detection system can be used for carrying out multiple PCR amplification experiments, and the collected amplification original data can be analyzed. The following is a description taking representative hole site data of one channel portion of one experiment at a time as an example.

As shown in FIG. 3(a), the original amplification data for 5 well sites were selected, and 5 curves from top to bottom were distinguished by wells 1-5. As shown in FIG. 3(b), amplification data of well sites No. 2 to 5 in which the amplification heights were small are shown. For the data base parameters, the number of cycles was 40 and the shortest baseline period was 5 cycles.

As can be seen from FIG. 3(a), well 1 had a significant amplification, well 2 had a slight amplification, and well 3-5 had no significant amplification, and as can be seen from FIG. 3(b), well 3-5 was divided into two echelons, with well 3 having a slight amplification and well 4-5 having no significant amplification.

For the calculation result, according to the foregoing steps, Savitzky-Golay derivation is performed first, and for wells 1 and 2, an amplification data derivative curve can be obtained, as shown in fig. 4 (other wells are reasonably available). Clustering analysis is carried out by taking the maximum value point of the derivative curve as class 1 and other maximum value points as another class, so as to obtain the profile coefficient corresponding to each hole, and the following table shows that:

	1	2	3	4	5
						coefficient of contour	0.9999	0.9846	0.9819	0.9897	0.9592

It can be seen that when 0.99 is used as the evaluation threshold, the hole 1 can be divided, the holes 2-5 cannot be divided, the cycle position corresponding to the maximum first derivative of the hole 1 is the 30 th cycle, and before the cycle, the region which meets the requirement of the shortest baseline period and has the smallest slope is: 8-16 cycles, and the interval with the best fit can be obtained by expanding the region to two ends: 0-21 cycles. The corresponding slope k is 9.414, and the intercept b is 9653.266, on the basis of the original amplification curve, the fitting baseline is subtracted, so that the real amplification curve with the baseline removed can be obtained, similar calculation is performed on other hole sites with obvious amplification in the channel of the experiment in the same way, and the shortest baseline period can be obtained as follows: 0-21. Based on the shortest baseline period, linear fitting is carried out on the amplification hole positions without obvious amplification holes in the same way, and a corresponding baseline and a real amplification curve after the baseline is removed can be found. The amplification curves of the respective wells finally obtained are shown in FIGS. 5(a) and 5(b), in which FIG. 5(a) is an overall amplification curve of 5 wells, and FIG. 5(b) is an enlarged view of the amplification curves of the other wells after removing the 1 well from which amplification is evident. As can be seen in fig. 5, well 1 had significant amplification and was above the threshold line, i.e. with Ct values, wells 2, 3 had slight amplification but did not meet the threshold line criteria, and wells 4, 5 had no heads up, as compared to fig. 3(a) and 3(b), and it was seen that this was true.

Example two:

fig. 6 is a schematic structural diagram of an amplification curve baseline determination apparatus according to an embodiment of the present application, and as shown in fig. 6, the amplification curve baseline determination apparatus 600 includes:

an obtaining module 601, configured to obtain amplification data of an unknown sample, and determine an obvious amplification sample and an unobvious amplification sample from the amplification data of the unknown sample by using a cluster analysis method;

a first determining module 602, configured to determine an amplification curve baseline and a shortest baseline period of the significantly amplified sample by using a linear fitting method;

a second determining module 603 for determining an amplification curve baseline for the non-significantly amplified sample based on the shortest baseline period.

The amplification curve baseline determination device provided by the embodiment of the application has the same technical characteristics as the amplification curve baseline determination method provided by the embodiment, so that the same technical problems can be solved, and the same technical effects can be achieved.

Example three:

as shown in fig. 7, an electronic device 700 provided in an embodiment of the present application includes a memory 701 and a processor 702, where the memory stores a computer program that is executable on the processor, and the processor implements the steps of the method provided in the foregoing embodiment when executing the computer program.

Referring to fig. 7, the electronic device further includes: a bus 703 and a communication interface 704, and the processor 702, the communication interface 704, and the memory 701 are connected by the bus 703; the processor 702 is configured to execute executable modules, such as computer programs, stored in the memory 701.

The Memory 701 may include a high-speed Random Access Memory (RAM), and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 704 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.

Bus 703 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 7, but this does not indicate only one bus or one type of bus.

The memory 701 is used for storing a program, the processor 702 executes the program after receiving an execution instruction, and the method performed by the apparatus defined by the process disclosed in any of the foregoing embodiments of the present application may be applied to the processor 702, or implemented by the processor 702.

The processor 702 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 702. The Processor 702 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 701, and the processor 702 reads the information in the memory 701, and completes the steps of the method in combination with the hardware thereof.

Example four:

corresponding to the amplification curve baseline determination method, the embodiment of the application also provides a computer readable storage medium, and machine executable instructions are stored in the computer readable storage medium, and when the computer executable instructions are called and executed by the processor, the computer executable instructions cause the processor to execute the steps of the amplification curve baseline determination method.

The amplification curve baseline determination device provided by the embodiment of the application can be specific hardware on the equipment or software or firmware installed on the equipment. The device provided by the embodiment of the present application has the same implementation principle and technical effect as the foregoing method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiments where no part of the device embodiments is mentioned. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the foregoing systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

For another example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the augmentation curve baseline determination method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the scope of the embodiments of the present application. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.