CN115545123B - Melting curve optimization method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a melting curve optimization method, a device, electronic equipment and a storage medium, and relates to the technical field of PCR detection.
Description
Technical Field
The present invention relates to the field of PCR detection technologies, and in particular, to a method and apparatus for optimizing a melting curve, an electronic device, and a storage medium.
Background
After the PCR (polymerase chain reaction ) amplification reaction is completed, in order to examine the specificity of the amplified product, the negative derivative value of the fluorescence intensity, i.e., the melting curve, is usually obtained by gradually increasing the temperature and degrading the amplified product. In the heating process, when the temperature reaches the melting half temperature, the fluorescence intensity is rapidly reduced, so that a high peak point is formed on the melting curve, the temperature corresponding to the peak point is the Tm value (namely the melting temperature), and the number and the positions of the Tm values are the important points of investigation.
The melting curve analysis method commonly used at present comprises a direct search method, a hierarchical clustering method, a high-order derivative method, a Levenberg-Marquardt-based curve fitting method, a continuous wavelet transformation method and the like. When the amplitude characteristics of each peak point of the melting curve are not obvious enough, the Tm value determined by the existing melting curve analysis method is easily affected by the clutter, so that the problems of identifying the clutter and eliminating the clutter corresponding to the clutter are all the problems to be faced.
Disclosure of Invention
The invention aims to provide a melting curve optimization method, a melting curve optimization device, electronic equipment and a storage medium, so as to effectively remove a miscellaneous peak in a melting curve.
In a first aspect, an embodiment of the present invention provides a method for optimizing a melting curve, including:
acquiring an initial melting curve and an initial Tm value corresponding to fluorescence intensity data to be processed; wherein the initial melting curve comprises a first melting curve with an initial Tm value, a second melting curve without an initial Tm value and with a maximum point, and an initial negative melting curve without an initial Tm value and without a maximum point;
based on a preset rule, carrying out cluster analysis on the initial Tm value of the first melting curve and the maximum point of the second melting curve to obtain a target negative melting curve and a candidate melting curve with a peak to be removed; wherein the preset rule relates to a melting curve definition;
And removing the impurity peak of the candidate melting curve based on the similarity between the candidate melting curve and the target negative melting curve to obtain an optimized target melting curve.
Further, the clustering analysis is performed on the initial Tm value of the first melting curve and the maximum point of the second melting curve based on a preset rule, to obtain a target negative melting curve and a candidate melting curve from which a hetero peak is to be removed, including:
according to the preset rule, a Tm value corresponding to a hybrid peak is screened from the initial Tm values of the first melting curve;
performing clustering analysis based on the contour coefficients on the clustering set to obtain a clustering result; the clustering set comprises the amplitude of an initial Tm value except the Tm value corresponding to the impurity peak in the first melting curve and the amplitude of a maximum point in the second melting curve;
and obtaining a target negative melting curve and a candidate melting curve of the impurity peak to be removed according to the clustering result.
Further, the step of screening Tm values corresponding to the hetero peaks from the initial Tm values of the first melting curve according to the preset rule includes:
and determining an initial Tm value in the first melting curve, which does not satisfy the occurrence of a melting peak in a fluorescence intensity-decreasing region, as a Tm value corresponding to a hetero peak.
Further, according to the clustering result, obtaining a target negative melting curve and a candidate melting curve from which the impurity peak is to be removed, including:
screening out a target Tm value, a candidate Tm value and a target maximum value point from the initial Tm value and the maximum value point corresponding to the clustering set according to the clustering result; the target Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient larger than a set threshold value, the candidate Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient smaller than or equal to the set threshold value, and the target maximum value point is a maximum value point corresponding to an amplitude value with a profile coefficient larger than the set threshold value;
determining a second melting curve and the initial negative melting curve, wherein all maximum points are the target maximum points, as target negative melting curves;
and determining a first melting curve containing the Tm value corresponding to the impurity peak or the candidate Tm value as a candidate melting curve for removing the impurity peak.
Further, the removing the impurity peak from the candidate melting curve based on the similarity with the target negative melting curve to obtain an optimized target melting curve includes:
determining a target correlation coefficient and a correlation negative melting curve corresponding to the candidate melting curve; the target correlation coefficient is the maximum value of correlation coefficients between a fluorescence intensity curve corresponding to the candidate melting curve and a fluorescence intensity curve corresponding to each target negative melting curve, and the correlation negative melting curve is a target negative melting curve corresponding to the target correlation coefficient;
Determining a target miscellaneous peak in the candidate melting curve according to a threshold interval to which the target correlation coefficient belongs and a correlation negative melting curve corresponding to the candidate melting curve;
and carrying out smoothing treatment on the target hybrid peaks on the candidate melting curve by adopting a preset filtering algorithm to obtain an optimized target melting curve.
Further, the determining the target hetero-peak in the candidate melting curve according to the threshold interval to which the target correlation coefficient belongs and the correlation negative melting curve corresponding to the candidate melting curve includes:
when the target correlation coefficient belongs to a first threshold interval, determining melting peak average corresponding to all initial Tm values in the candidate melting curve as a target miscellaneous peak;
when the target correlation coefficient belongs to a second threshold interval, sequentially carrying out peak inspection on candidate Tm values in the candidate melting curve according to the sequence from the large amplitude to the small amplitude to obtain a target peak in the candidate melting curve; wherein, any value in the second threshold interval is smaller than any value in the first threshold interval, the candidate Tm value is an initial Tm value that is not yet determined whether it belongs to a hybrid peak, the target hybrid peak includes a melting peak corresponding to the candidate Tm value that does not meet a preset melting peak requirement, and the melting peak requirement is related to the determined target Tm value set;
When the target correlation coefficient belongs to a third threshold value interval, determining a target hetero-peak in the candidate melting curve based on the magnitude relation between the maximum amplitude of the candidate Tm value in the candidate melting curve and the amplitude of the corresponding position of the correlation negative melting curve; wherein any value within the third threshold interval is less than any value within the second threshold interval;
when the target correlation coefficient belongs to a fourth threshold interval, determining that a target hetero-peak of the candidate melting curve is empty; wherein any value within the fourth threshold interval is less than any value within the third threshold interval.
Further, the melting peak requirement includes that, in the determined set of target Tm values, there are at least a preset number of correlated Tm values that lie within a preset range of the candidate Tm values, that are greater than the magnitude of the candidate Tm values, and that the candidate Tm values are greater than half the minimum magnitude of the correlated Tm values;
the determining the target hetero-peak in the candidate melting curve based on the magnitude relation between the maximum amplitude of the candidate Tm value in the candidate melting curve and the amplitude of the corresponding position of the relevant negative melting curve comprises the following steps:
When the maximum amplitude of the candidate Tm value in the candidate melting curve is smaller than or equal to the amplitude of the corresponding position of the relevant negative melting curve, carrying out mixed peak investigation on the candidate Tm value in the candidate melting curve in sequence from large to small according to the amplitude, and obtaining a target mixed peak in the candidate melting curve;
and when the maximum amplitude of the candidate Tm value in the candidate melting curve is larger than the amplitude of the corresponding position of the relevant negative melting curve, determining that the target hetero-peak of the candidate melting curve is empty.
In a second aspect, an embodiment of the present invention further provides a melting curve optimization apparatus, including:
the acquisition module is used for acquiring an initial melting curve and an initial Tm value corresponding to the fluorescence intensity data to be processed; wherein the initial melting curve comprises a first melting curve with an initial Tm value, a second melting curve without an initial Tm value and with a maximum point, and an initial negative melting curve without an initial Tm value and without a maximum point;
the analysis module is used for carrying out cluster analysis on the initial Tm value of the first melting curve and the maximum point of the second melting curve based on a preset rule to obtain a target negative melting curve and a candidate melting curve with a peak to be removed; wherein the preset rule relates to a melting curve definition;
And the optimization module is used for removing the impurity peak of the candidate melting curve based on the similarity between the candidate melting curve and the target negative melting curve to obtain an optimized target melting curve.
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 that can run on the processor, and the processor implements the melting curve optimization method of the first aspect when executing the computer program.
In a fourth aspect, embodiments of the present invention also provide a storage medium having stored thereon a computer program which, when executed by a processor, performs the melting curve optimization method of the first aspect.
According to the melting curve optimization method, the device, the electronic equipment and the storage medium, on the basis of the initial melting curve obtained based on the existing method, the initial melting curve is divided into the target negative melting curve and the candidate melting curve with the impurity peak to be removed based on the preset rule, and then the impurity peak of the candidate melting curve is removed in a targeted manner based on the similarity between the target negative melting curve and the target negative melting curve, so that the effective removal of the impurity peak in the melting curve is realized, and the method is easy to understand and easy to realize.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for optimizing a melting curve according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another method for optimizing a melting curve according to an embodiment of the present invention;
FIG. 3 shows melting curves and corresponding Tm values before removing the impurity peak;
FIG. 4 shows melting curves after removing the impurity peaks and corresponding Tm values;
FIG. 5 is a schematic diagram of a melting curve optimizing apparatus according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Based on the fact that the Tm value determined by the existing melting curve analysis method is easily affected by clutter, the melting curve optimization method, the melting curve optimization device, the electronic equipment and the storage medium provided by the embodiment of the invention can better remove the impurity peak in the melting curve by comprehensively adopting preset rules and similarities, and obtain a smooth melting curve, and are easy to understand and realize.
For the convenience of understanding the present embodiment, a detailed description will be given of a method for optimizing a melting curve disclosed in the embodiment of the present invention.
The embodiment of the invention provides a melting curve optimization method for removing a melting curve peak based on preset rules and similarity, which can be executed by electronic equipment with data processing capability. Referring to a schematic flow chart of a melting curve optimization method shown in fig. 1, the method mainly includes the following steps S102 to S106:
step S102, obtaining an initial melting curve and an initial Tm value corresponding to fluorescence intensity data to be processed; the initial melting curve includes a first melting curve having an initial Tm value, a second melting curve having no initial Tm value and having a maximum point, and an initial negative melting curve having no initial Tm value and no maximum point.
The initial melting curve and the initial Tm value corresponding to the fluorescence intensity data to be processed may be obtained by an existing method. The existing method may include a melting curve Tm value determining method (hierarchical clustering method) based on hierarchical clustering, a separation method of overlapping peaks of a melting curve, a direct search method, a curve fitting method, a high-order derivative method, a continuous wavelet transform method, a neural network method, and the like, which is not limited in this embodiment.
If a certain melting curve has no Tm value, the melting curve is initially determined to be a negative melting curve, further, if no maximum point exists, the melting curve can be determined to be a negative melting curve, if the maximum point exists, the maximum points can be gathered, and the available negative melting curve can be further screened out through subsequent processing. Based on this, the initial melting curve can be divided into three categories: a first melting curve having an initial Tm value, a second melting curve having no initial Tm value and having a maximum point, and an initial negative melting curve having no initial Tm value and no maximum point. Wherein, the negative melting curve refers to a melting curve in which the target product (no Tm value) is not present. In this embodiment, the impurity peak is selected and removed from the melting peak corresponding to the initial Tm value in the first melting curve.
Step S104, based on a preset rule, carrying out cluster analysis on the initial Tm value of the first melting curve and the maximum point of the second melting curve to obtain a target negative melting curve and a candidate melting curve with a peak to be removed.
Wherein the preset rule relates to a melting curve definition.
Rules may be determined based on a biological model generated from the melting curve. Specifically, according to the definition of the melting curve, "when the temperature reaches the melting half temperature during the temperature rising process, the fluorescence intensity is rapidly reduced to form a high peak point on the melting curve", and it is known that for a melting curve peak with a distinct characteristic, particularly, a peak corresponding to the maximum amplitude of the melting curve should occur in a region where the fluorescence intensity is reduced, and the amplitude is larger, whereas the peak amplitude of the negative melting curve is smaller. The preset rule may therefore be that the peak corresponding to the maximum amplitude of the melting curve should occur in the fluorescence intensity decreasing region and the amplitude is larger than the peak of the negative melting curve.
In some possible embodiments, the step S104 may be implemented by the following substeps:
and 1.1, screening Tm values corresponding to the impurity peaks from the initial Tm values of the first melting curve according to a preset rule.
The initial Tm value of the first melting curve, which does not satisfy the occurrence of the melting peak in the fluorescence intensity-decreasing region, may be determined as the Tm value corresponding to the impurity peak. The Tm value corresponding to the hetero peak may be put into the hetero peak set.
Sub-step 1.2, performing cluster analysis based on the contour coefficients on the cluster set to obtain a cluster result; the clustering set comprises the amplitude of an initial Tm value except for the Tm value corresponding to the impurity peak in the first melting curve and the amplitude of a maximum point in the second melting curve.
A cluster analysis based on profile coefficients (such as Kmeans cluster analysis) may be performed on the cluster set. The contour coefficient is an evaluation mode of good and bad clustering effect, and the larger the value of the contour coefficient is, the better the clustering effect is.
And 1.3, obtaining a target negative melting curve and a candidate melting curve of the impurity peak to be removed according to the clustering result.
According to the contour coefficient corresponding to each sample (each element in the clustering set) in the clustering result, screening out a candidate melting curve with obvious characteristics and a candidate melting curve with a peak to be removed from the first melting curve, screening out a negative melting curve from the second melting curve, and then carrying out set with the initial negative melting curve to obtain a comprehensive negative melting curve, namely a target negative melting curve.
The substep 1.3 may be realized by the following procedure: screening out a target Tm value, a candidate Tm value and a target maximum value point from initial Tm values and maximum value points corresponding to a clustering set according to a clustering result; the target Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient larger than a set threshold value, the candidate Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient smaller than or equal to the set threshold value, and the target maximum value point is a maximum value point corresponding to an amplitude value with a profile coefficient larger than the set threshold value; determining a second melting curve and an initial negative melting curve, wherein all maximum points are target maximum points, as target negative melting curves; and determining the first melting curve containing the Tm value or the candidate Tm value corresponding to the impurity peak as a candidate melting curve from which the impurity peak is to be removed.
Wherein, the candidate Tm value may also have a Tm value corresponding to a hetero peak; the target Tm value may be put into a target Tm value set, which may be used in a subsequent similarity-based hetero-peak screening process, and a melting curve having only the target Tm value may be referred to as a characteristic-apparent melting curve. The set threshold may be set according to actual requirements, and is not limited herein, and the set threshold is, for example, 0.95.
And S106, removing the impurity peak of the candidate melting curve based on the similarity with the target negative melting curve to obtain an optimized target melting curve.
In some possible embodiments, the step S106 may be implemented by the following substeps:
step 2.1, determining a target correlation coefficient and a correlation negative melting curve corresponding to the candidate melting curve; the target correlation coefficient is the maximum value of correlation coefficients between a fluorescence intensity curve corresponding to the candidate melting curve and a fluorescence intensity curve corresponding to each target negative melting curve, and the correlation negative melting curve is a target negative melting curve corresponding to the target correlation coefficient.
The correlation coefficient between the corresponding fluorescence intensity curve and the fluorescence intensity curve corresponding to each target negative melting curve can be calculated for each candidate melting curve, the maximum value in the correlation coefficients is selected as the target correlation coefficient, and the corresponding target negative melting curve is selected as the correlation negative melting curve.
The above-mentioned correlation coefficient may be a pearson correlation coefficient, whose expression is as follows:
wherein,,X n for the fluorescence intensity curve corresponding to the candidate melting curve to be examined, Y n The fluorescence intensity curve corresponding to the target negative melting curve for comparison is composed of fluorescence intensity data.
And 2.2, determining a target miscellaneous peak in the candidate melting curve according to the threshold interval to which the target correlation coefficient belongs and the correlation negative melting curve corresponding to the candidate melting curve.
All or part of the impurity peaks on the candidate melting curve can be determined based on the threshold interval of the given correlation coefficient and the comparison result between the candidate melting curve and the peak value of the corresponding correlation negative melting curve (the peak value of the melting peak, i.e., the amplitude of the Tm value).
Alternatively, sub-step 2.2 may be implemented by the following four cases:
(1) When the target correlation coefficient belongs to the first threshold value interval, the candidate melting curve is quite similar to the correlation negative melting curve, so that melting peaks corresponding to all initial Tm values in the candidate melting curve are determined to be target hetero peaks.
The first threshold interval may be set according to practical situations, for example [0.9999,1].
(2) When the target correlation coefficient belongs to the second threshold value interval, the candidate melting curve is similar to the correlation negative melting curve, so that the candidate Tm values in the candidate melting curve are sequentially subjected to the peak inspection according to the sequence from the large amplitude to the small amplitude, and the target peak in the candidate melting curve is obtained.
Wherein, any value in the second threshold interval is smaller than any value in the first threshold interval, and the second threshold interval can be set according to the situation, for example [0.999,0.9999); the candidate Tm value is an initial Tm value for which whether or not it belongs to a hetero peak has not been determined; the target hetero-peak comprises a melting peak corresponding to a candidate Tm value which does not meet the preset melting peak requirement, and can also comprise the hetero-peak determined in the previous process; the melting peak requirement is related to the set of determined target Tm values. In the investigation process, if the melting peak corresponding to the current candidate Tm value is judged to be a hetero peak, determining that the melting peak corresponding to the candidate Tm value with smaller amplitude is the hetero peak, and exiting the cycle.
Alternatively, considering that whether the melting peak corresponding to the candidate Tm value is a hybrid peak cannot be determined through the foregoing clustering process, it is explained that the candidate Tm value is smaller in amplitude than the target Tm value near the corresponding position in the characteristic obvious melting curve, and if the candidate Tm value is actually the target Tm value, it is explained that it is to satisfy the requirement of larger amplitude, based on which the melting peak requirement may include that, in the determined set of target Tm values, there are at least a preset number of relevant Tm values located within the preset range of the candidate Tm value and larger than the amplitude of the candidate Tm value, and the candidate Tm value is larger than half of the minimum amplitude in the relevant Tm values. The preset number and the preset range can be set according to actual requirements, for example, the preset number is 2, and the preset range is positive and negative 1 ℃ of the candidate Tm value.
(3) When the target correlation coefficient belongs to the third threshold value interval, the candidate melting curve is not similar to the correlation negative melting curve, so that the target hetero-peak in the candidate melting curve is determined based on the magnitude relation between the maximum amplitude of the candidate Tm value in the candidate melting curve and the amplitude of the corresponding position of the correlation negative melting curve.
Wherein any value within the third threshold interval is less than any value within the second threshold interval; the third threshold interval may be set according to circumstances, for example, [0.95,0.999 ]. When the maximum amplitude of the candidate Tm value in the candidate melting curve is smaller than or equal to the amplitude of the corresponding position of the relevant negative melting curve, the candidate melting curve is indicated that a hybrid peak still possibly exists, and further investigation can be performed according to the condition (2), namely, the candidate Tm value in the candidate melting curve is subjected to the hybrid peak investigation in sequence from the large amplitude to the small amplitude, so that a target hybrid peak in the candidate melting curve is obtained; when the maximum amplitude of the candidate Tm value in the candidate melting curve is larger than the amplitude of the corresponding position of the relevant negative melting curve, the fact that the candidate melting curve has no impurity peak basically is indicated, and the fact that the target impurity peak of the candidate melting curve is empty can be determined.
(4) When the target correlation coefficient belongs to the fourth threshold value interval, the candidate melting curve is not similar to the correlation negative melting curve, so that the target peak of the candidate melting curve is determined to be empty.
Wherein, any value in the fourth threshold interval is smaller than any value in the third threshold interval, and the fourth threshold interval can be set according to the situation, for example, is smaller than 0.95.
For ease of understanding, for a certain candidate melting curve, the target phase relationship is denoted as r, and one possible threshold setting method is as follows (it should be noted that, for different initial melting curve calculation methods, experimental conditions, and data conditions, other threshold settings may also be performed):
1) When r is more than or equal to 0.9999, the candidate melting curve is a negative melting curve, and melting peaks (namely, all hetero peaks) corresponding to all initial Tm values are removed.
2) When r is more than or equal to 0.999 and less than or equal to 0.9999, the melting peaks corresponding to the initial Tm values in the candidate melting curve are respectively inspected according to the magnitude sequence. For example, if the melting peak A is compared with a peak having a characteristic apparent melting curve in the vicinity of the Tm value (positive or negative 1 ℃ C.), and if there are 2 or more than 2 melting peak sets larger than the peak other than the peak, and the melting peak A is larger in amplitude than half of the smallest peak of the melting peak set, the melting peak is not a hetero peak, otherwise the melting peak is a hetero peak. Melting peaks corresponding to all other initial Tm values of the candidate melting curve are examined in a similar manner. In the investigation process, if the mixed peak is judged, the rest melting peaks with smaller amplitude are mixed peaks, and the circulation is exited.
3) When r is more than or equal to 0.95 and less than or equal to 0.999, if the maximum peak value of the candidate melting curve is less than or equal to the amplitude value of the corresponding position of the relevant negative melting curve, entering the step 2) for further investigation; if the maximum peak value is greater than the amplitude value of the corresponding position of the relevant negative melting curve, the cycle is exited, and all melting peaks corresponding to the initial Tm values are not miscellaneous peaks.
4) When r <0.95, the melting peaks corresponding to all the initial Tm values in the candidate melting curve are not hetero peaks.
And 2.3, carrying out smoothing treatment on the target hybrid peaks of the candidate melting curve by adopting a preset filtering algorithm to obtain an optimized target melting curve.
From the candidate melting curves, finding out a specific melting curve with reduced Tm value compared with the initial melting curve, namely finding out a specific melting curve with a miscellaneous peak; a filtering algorithm is used to smooth the specific melting curve until the impurity peak is no longer apparent. The filtering algorithm may be, for example, a classical Savitzky-Golay smoothing method, a wavelet filtering method, a classical butterworth low-pass filtering method, etc. Taking a Savitzky-Golay smoothing method as an example, setting the size of a data window as 5 sampling points (note: according to the Savitzky-Golay fitting principle, the window size is odd), and smoothing a specific melting curve for multiple times under the polynomial order of 1 degree until the miscellaneous peaks are no longer in the maximum position.
According to the melting curve optimization method provided by the embodiment of the invention, on the basis of the initial melting curve obtained based on the existing method, the initial melting curve is divided into the target negative melting curve and the candidate melting curve with the impurity peak to be removed based on the preset rule, and then the impurity peak of the candidate melting curve is removed in a targeted manner based on the similarity with the target negative melting curve, so that the effective removal of the impurity peak in the melting curve is realized, the understanding is easy, and the realization is easy.
For ease of understanding, referring to the flow diagram of another melt curve optimization method shown in fig. 2, an exemplary flow of the melt curve optimization method is as follows:
1. acquiring data: an initial melting curve is obtained by the existing method, and an initial negative melting curve (i.e., an initial melting curve in which no initial Tm value exists and no maximum point exists) is obtained by the extremum method.
2. Classification: and determining classification rules (namely preset rules) and performing cluster analysis.
3. And (3) determining a hybrid peak: and calculating a correlation coefficient, and determining a Tm value corresponding to the mixed peak.
4. Smoothing: and (5) finding out a melting curve with reduced Tm values, and performing self-adaptive smoothing.
On the basis of obtaining an initial melting curve based on the existing method, dividing the initial melting curve into a characteristic obvious melting curve and a negative melting curve based on a preset rule, then determining a miscellaneous peak based on the similarity with the negative melting curve, and on the basis, performing self-adaptive smoothing on the corresponding melting curve to remove the miscellaneous peak in a targeted manner. The method has the advantages that through comprehensively adopting preset rules and similarity, the impurity peaks in the melting curve are better removed, the smooth melting curve is obtained, and the method is easy to understand and realize.
In order to test the effectiveness of the melting curve optimization method, a PCR amplification-melting experiment is carried out on a plurality of reagents by using a fluorescence quantitative PCR detection system, and fluorescence intensity data acquired by a melting section is analyzed by using a melting curve Tm value determination method based on hierarchical clustering, so that an initial melting curve is obtained. Taking one example of the data, FIG. 3 is a melting curve diagram of the whole reaction plate before removing the impurity peak and the corresponding Tm value position (note: small solid dots show Tm value position), and the impurity peak is still more visible; FIG. 4 shows melting curves after removing the impurity peaks and corresponding Tm values, and the effect is obvious from FIG. 4, wherein the impurity peaks are removed, and the melting peaks are clearly distinguishable.
Corresponding to the melting curve optimization method, the embodiment of the invention also provides a melting curve optimization device. Referring to fig. 5, a schematic diagram of a melting curve optimizing apparatus is shown, which includes:
the acquisition module 501 is configured to acquire an initial melting curve and an initial Tm value corresponding to fluorescence intensity data to be processed; wherein the initial melting curve comprises a first melting curve with an initial Tm value, a second melting curve without an initial Tm value and with a maximum point, and an initial negative melting curve without an initial Tm value and without a maximum point;
The analysis module 502 is configured to perform cluster analysis on the initial Tm value of the first melting curve and the maximum point of the second melting curve based on a preset rule, so as to obtain a target negative melting curve and a candidate melting curve from which a hybrid peak is to be removed; wherein the preset rule is related to the definition of the melting curve;
and an optimization module 503, configured to perform peak removal on the candidate melting curve based on the similarity with the target negative melting curve, so as to obtain an optimized target melting curve.
According to the melting curve optimizing device provided by the embodiment of the invention, on the basis of the initial melting curve obtained based on the existing method, the initial melting curve is divided into the target negative melting curve and the candidate melting curve with the impurity peak to be removed based on the preset rule, and then the impurity peak of the candidate melting curve is removed in a targeted manner based on the similarity between the target negative melting curve and the candidate melting curve, so that the effective removal of the impurity peak in the melting curve is realized, and the device is easy to understand and realize.
Optionally, the analysis module 502 is specifically configured to: according to a preset rule, selecting a Tm value corresponding to a hetero peak from the initial Tm values of the first melting curve; performing clustering analysis based on the contour coefficients on the clustering set to obtain a clustering result; the clustering set comprises the amplitude of an initial Tm value except for a Tm value corresponding to a impurity peak in the first melting curve and the amplitude of a maximum point in the second melting curve; and obtaining a target negative melting curve and a candidate melting curve of the impurity peak to be removed according to the clustering result.
Optionally, the analysis module 502 is further configured to: the initial Tm value in the first melting curve, which does not satisfy the occurrence of the melting peak in the fluorescence intensity-decreasing region, is determined as the Tm value corresponding to the impurity peak.
Optionally, the analysis module 502 is further configured to: screening out a target Tm value, a candidate Tm value and a target maximum value point from initial Tm values and maximum value points corresponding to a clustering set according to a clustering result; the target Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient larger than a set threshold value, the candidate Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient smaller than or equal to the set threshold value, and the target maximum value point is a maximum value point corresponding to an amplitude value with a profile coefficient larger than the set threshold value; determining a second melting curve and an initial negative melting curve, wherein all maximum points are target maximum points, as target negative melting curves; and determining the first melting curve containing the Tm value or the candidate Tm value corresponding to the impurity peak as a candidate melting curve from which the impurity peak is to be removed.
Optionally, the optimization module 503 is specifically configured to: determining a target correlation coefficient and a correlation negative melting curve corresponding to the candidate melting curve; the target correlation coefficient is the maximum value of correlation coefficients between a fluorescence intensity curve corresponding to the candidate melting curve and a fluorescence intensity curve corresponding to each target negative melting curve, and the correlation negative melting curve is a target negative melting curve corresponding to the target correlation coefficient; determining a target miscellaneous peak in the candidate melting curve according to a threshold interval to which the target correlation coefficient belongs and a correlation negative melting curve corresponding to the candidate melting curve; and carrying out smoothing treatment on the target impurity peaks of the candidate melting curve by adopting a preset filtering algorithm to obtain an optimized target melting curve.
Optionally, the optimizing module 503 is further configured to:
when the target correlation coefficient belongs to a first threshold interval, determining melting peak average corresponding to all initial Tm values in the candidate melting curve as a target miscellaneous peak;
when the target correlation coefficient belongs to the second threshold interval, sequentially carrying out peak investigation on candidate Tm values in the candidate melting curve according to the sequence from the large amplitude to the small amplitude to obtain a target peak in the candidate melting curve; wherein, any value in the second threshold interval is smaller than any value in the first threshold interval, the candidate Tm value is an initial Tm value which does not yet determine whether the candidate Tm value belongs to a hybrid peak, the target hybrid peak comprises a melting peak corresponding to the candidate Tm value which does not meet the preset melting peak requirement, and the melting peak requirement is related to the determined target Tm value set;
when the target correlation coefficient belongs to a third threshold value interval, determining a target miscellaneous peak in the candidate melting curve based on the magnitude relation between the maximum amplitude of the candidate Tm value in the candidate melting curve and the amplitude of the corresponding position of the relevant negative melting curve; wherein any value within the third threshold interval is less than any value within the second threshold interval;
when the target correlation coefficient belongs to a fourth threshold value interval, determining that a target hetero-peak of the candidate melting curve is empty; wherein any value within the fourth threshold interval is less than any value within the third threshold interval.
Alternatively, the melting peak is required to be included in the set of determined target Tm values, there are at least a preset number of correlated Tm values lying within a preset range of the candidate Tm values, which are larger than the magnitudes of the candidate Tm values, and the candidate Tm values are larger than half the minimum magnitudes among the correlated Tm values.
Optionally, the optimizing module 503 is further configured to: when the maximum amplitude of the candidate Tm value in the candidate melting curve is smaller than or equal to the amplitude of the corresponding position of the relevant negative melting curve, sequentially carrying out mixed peak investigation on the candidate Tm value in the candidate melting curve according to the sequence from the large amplitude to the small amplitude to obtain a target mixed peak in the candidate melting curve; and when the maximum amplitude of the candidate Tm value in the candidate melting curve is larger than the amplitude of the corresponding position of the relevant negative melting curve, determining that the target hetero-peak of the candidate melting curve is empty.
The melting curve optimizing device provided in this embodiment has the same implementation principle and technical effects as those of the melting curve optimizing method embodiment, and for the sake of brief description, reference may be made to corresponding contents in the melting curve optimizing method embodiment where the melting curve optimizing device embodiment is not mentioned.
As shown in fig. 6, an electronic device 600 provided in an embodiment of the present invention includes: the melting curve optimization method comprises a processor 601, a memory 602 and a bus, wherein the memory 602 stores a computer program capable of running on the processor 601, and when the electronic device 600 runs, the processor 601 and the memory 602 communicate through the bus, and the processor 601 executes the computer program to realize the melting curve optimization method.
Specifically, the memory 602 and the processor 601 can be general-purpose memories and processors, which are not particularly limited herein.
The embodiment of the invention also provides a storage medium, and a computer program is stored on the storage medium, and the computer program is executed by a processor to execute the melting curve optimization method in the previous method embodiment. The storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a RAM, a magnetic disk, or an optical disk, etc., which can store program codes.
Any particular values in all examples shown and described herein are to be construed as merely illustrative and not a limitation, and thus other examples of exemplary embodiments may have different values.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. 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.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (7)
1. A method of optimizing a melting curve, comprising:
acquiring an initial melting curve and an initial Tm value corresponding to fluorescence intensity data to be processed; wherein the initial melting curve comprises a first melting curve with an initial Tm value, a second melting curve without an initial Tm value and with a maximum point, and an initial negative melting curve without an initial Tm value and without a maximum point;
based on a preset rule, carrying out cluster analysis on the initial Tm value of the first melting curve and the maximum point of the second melting curve to obtain a target negative melting curve and a candidate melting curve with a peak to be removed; wherein, the preset rule is related to the definition of the melting curve, and the preset rule is that the peak corresponding to the maximum amplitude of the melting curve should occur in the fluorescence intensity decreasing area, and the amplitude is larger compared with the peak of the negative melting curve;
Removing the impurity peak of the candidate melting curve based on the similarity between the candidate melting curve and the target negative melting curve to obtain an optimized target melting curve;
the clustering analysis is performed on the initial Tm value of the first melting curve and the maximum point of the second melting curve based on a preset rule, so as to obtain a target negative melting curve and a candidate melting curve from which a hetero peak is to be removed, including:
according to the preset rule, a Tm value corresponding to a hybrid peak is screened from the initial Tm values of the first melting curve;
performing clustering analysis based on the contour coefficients on the clustering set to obtain a clustering result; the clustering set comprises the amplitude of an initial Tm value except the Tm value corresponding to the impurity peak in the first melting curve and the amplitude of a maximum point in the second melting curve;
obtaining a target negative melting curve and a candidate melting curve of a peak to be removed according to the clustering result;
obtaining a target negative melting curve and a candidate melting curve with a peak to be removed according to the clustering result, wherein the candidate melting curve comprises the following steps:
screening out a target Tm value, a candidate Tm value and a target maximum value point from the initial Tm value and the maximum value point corresponding to the clustering set according to the clustering result; the target Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient larger than a set threshold value, the candidate Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient smaller than or equal to the set threshold value, and the target maximum value point is a maximum value point corresponding to an amplitude value with a profile coefficient larger than the set threshold value;
Determining a second melting curve and the initial negative melting curve, wherein all maximum points are the target maximum points, as target negative melting curves;
determining a first melting curve containing the Tm value corresponding to the impurity peak or the candidate Tm value as a candidate melting curve from which the impurity peak is to be removed;
removing the impurity peak of the candidate melting curve based on the similarity with the target negative melting curve to obtain an optimized target melting curve, wherein the method comprises the following steps:
determining a target correlation coefficient and a correlation negative melting curve corresponding to the candidate melting curve; the target correlation coefficient is the maximum value of correlation coefficients between a fluorescence intensity curve corresponding to the candidate melting curve and a fluorescence intensity curve corresponding to each target negative melting curve, and the correlation negative melting curve is a target negative melting curve corresponding to the target correlation coefficient;
determining a target miscellaneous peak in the candidate melting curve according to a threshold interval to which the target correlation coefficient belongs and a correlation negative melting curve corresponding to the candidate melting curve;
and carrying out smoothing treatment on the target hybrid peaks on the candidate melting curve by adopting a preset filtering algorithm to obtain an optimized target melting curve.
2. The method of optimizing a melting curve according to claim 1, wherein the step of screening Tm values corresponding to the hetero-peaks from the initial Tm values of the first melting curve according to the preset rule includes:
and determining an initial Tm value in the first melting curve, which does not satisfy the occurrence of a melting peak in a fluorescence intensity-decreasing region, as a Tm value corresponding to a hetero peak.
3. The method of optimizing a melting curve according to claim 1, wherein determining the target peak in the candidate melting curve according to the threshold interval to which the target correlation coefficient belongs and the correlation negative melting curve corresponding to the candidate melting curve comprises:
when the target correlation coefficient belongs to a first threshold interval, determining melting peak average corresponding to all initial Tm values in the candidate melting curve as a target miscellaneous peak;
when the target correlation coefficient belongs to a second threshold interval, sequentially carrying out peak inspection on candidate Tm values in the candidate melting curve according to the sequence from the large amplitude to the small amplitude to obtain a target peak in the candidate melting curve; wherein, any value in the second threshold interval is smaller than any value in the first threshold interval, the candidate Tm value is an initial Tm value that is not yet determined whether it belongs to a hybrid peak, the target hybrid peak includes a melting peak corresponding to the candidate Tm value that does not meet a preset melting peak requirement, and the melting peak requirement is related to the determined target Tm value set;
When the target correlation coefficient belongs to a third threshold value interval, determining a target hetero-peak in the candidate melting curve based on the magnitude relation between the maximum amplitude of the candidate Tm value in the candidate melting curve and the amplitude of the corresponding position of the correlation negative melting curve; wherein any value within the third threshold interval is less than any value within the second threshold interval;
when the target correlation coefficient belongs to a fourth threshold interval, determining that a target hetero-peak of the candidate melting curve is empty; wherein any value within the fourth threshold interval is less than any value within the third threshold interval.
4. The melting curve optimization method of claim 3, wherein the melting peak requirement includes that, in the determined set of target Tm values, there are at least a preset number of correlated Tm values that lie within a preset range of the candidate Tm values, that are greater than the magnitude of the candidate Tm values, and that are greater than half the minimum magnitude of the correlated Tm values;
the determining the target hetero-peak in the candidate melting curve based on the magnitude relation between the maximum amplitude of the candidate Tm value in the candidate melting curve and the amplitude of the corresponding position of the relevant negative melting curve comprises the following steps:
When the maximum amplitude of the candidate Tm value in the candidate melting curve is smaller than or equal to the amplitude of the corresponding position of the relevant negative melting curve, carrying out mixed peak investigation on the candidate Tm value in the candidate melting curve in sequence from large to small according to the amplitude, and obtaining a target mixed peak in the candidate melting curve;
and when the maximum amplitude of the candidate Tm value in the candidate melting curve is larger than the amplitude of the corresponding position of the relevant negative melting curve, determining that the target hetero-peak of the candidate melting curve is empty.
5. A melting curve optimizing apparatus, comprising:
the acquisition module is used for acquiring an initial melting curve and an initial Tm value corresponding to the fluorescence intensity data to be processed; wherein the initial melting curve comprises a first melting curve with an initial Tm value, a second melting curve without an initial Tm value and with a maximum point, and an initial negative melting curve without an initial Tm value and without a maximum point;
the analysis module is used for carrying out cluster analysis on the initial Tm value of the first melting curve and the maximum point of the second melting curve based on a preset rule to obtain a target negative melting curve and a candidate melting curve with a peak to be removed; wherein, the preset rule is related to the definition of the melting curve, and the preset rule is that the peak corresponding to the maximum amplitude of the melting curve should occur in the fluorescence intensity decreasing area, and the amplitude is larger compared with the peak of the negative melting curve;
The optimization module is used for removing the impurity peak of the candidate melting curve based on the similarity between the candidate melting curve and the target negative melting curve to obtain an optimized target melting curve;
the analysis module is specifically used for: according to the preset rule, a Tm value corresponding to a hybrid peak is screened from the initial Tm values of the first melting curve; performing clustering analysis based on the contour coefficients on the clustering set to obtain a clustering result; the clustering set comprises the amplitude of an initial Tm value except the Tm value corresponding to the impurity peak in the first melting curve and the amplitude of a maximum point in the second melting curve; obtaining a target negative melting curve and a candidate melting curve of a peak to be removed according to the clustering result;
the analysis module is also configured to: screening out a target Tm value, a candidate Tm value and a target maximum value point from the initial Tm value and the maximum value point corresponding to the clustering set according to the clustering result; the target Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient larger than a set threshold value, the candidate Tm value is an initial Tm value corresponding to an amplitude value with a profile coefficient smaller than or equal to the set threshold value, and the target maximum value point is a maximum value point corresponding to an amplitude value with a profile coefficient larger than the set threshold value; determining a second melting curve and the initial negative melting curve, wherein all maximum points are the target maximum points, as target negative melting curves; determining a first melting curve containing the Tm value corresponding to the impurity peak or the candidate Tm value as a candidate melting curve from which the impurity peak is to be removed;
The optimization module is specifically used for: determining a target correlation coefficient and a correlation negative melting curve corresponding to the candidate melting curve; the target correlation coefficient is the maximum value of correlation coefficients between a fluorescence intensity curve corresponding to the candidate melting curve and a fluorescence intensity curve corresponding to each target negative melting curve, and the correlation negative melting curve is a target negative melting curve corresponding to the target correlation coefficient; determining a target miscellaneous peak in the candidate melting curve according to a threshold interval to which the target correlation coefficient belongs and a correlation negative melting curve corresponding to the candidate melting curve; and carrying out smoothing treatment on the target hybrid peaks on the candidate melting curve by adopting a preset filtering algorithm to obtain an optimized target melting curve.
6. An electronic device comprising a memory, a processor, the memory having stored thereon a computer program executable on the processor, wherein the processor, when executing the computer program, implements the melting curve optimization method of any one of claims 1-4.
7. A storage medium having a computer program stored thereon, which, when executed by a processor, performs the melt curve optimization method of any one of claims 1-4.
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