KR20180135986A - Detecting abnormal signals in a data set - Google Patents

Abstract

The present invention relates to a method of detecting abnormal signals in a data set, particularly a data set for a target analyte. According to the present invention, not only can the normal score be used to accurately determine the cycle number (s) representing an abnormal signal in the data set, but if it is determined that the candidate cycle number is indicative of an abnormal signal, And can provide a corrected data set that has been replaced with a normal signal value.

Description

Detecting abnormal signals in a data set

The present invention relates to the detection of abnormal signals in a data set, particularly a data set for a target analyte.

As a method for detecting a target nucleic acid sequence through nucleic acid amplification, a real-time PCR (real time PCR) technique for measuring amplification of a target nucleic acid sequence in real-time is widely used. Real-time PCR techniques use signal-generating means that emit a detectable fluorescent signal in proportion to the amount of target nucleic acid sequence in a PCR reaction to detect a particular target nucleic acid sequence. The emission of a detectable fluorescent signal can be detected by using an oligonucleotide containing both a reporter molecule and a quencher molecule which inhibits its fluorescence emission, for example, using an intercalator that emits a fluorescence signal when bound to double helix DNA .

Real-time PCR measures fluorescence signals proportional to the amount of target nucleic acid in each cycle and generates data including a plurality of data points having a pair of a cycle number and a coordinate value of the intensity (signal value) of the fluorescence signal in the cycle number And generates a set (data set). The data set may be represented by an amplification curve (also referred to as an amplification profile curve or growth curve) plotted against the cycle number of fluorescence intensity values for ease of data analysis. The data set representing the amplification curve can then be analyzed to determine the presence or absence of the target nucleic acid sequence in the sample. For example, if there is a cycle with a fluorescence signal that exceeds the threshold applied to the data set representing the amplification curve, it can be determined that the target nucleic acid sequence is present in the sample.

In order to detect a target nucleic acid sequence, it is essential to obtain an accurate and reliable data set. However, no matter how precisely the experiment is carried out, the resulting data set is subject to abnormal signal (error or noise) due to changes in the annealing temperature, the creation of air bubbles in the reaction tube, )). Examples of such abnormal signals include a sudden increase (jump, spike, step) of the fluorescence signal or a sudden decrease (also called dip). Such abnormal signals can lead to misinterpretation in the qualitative and quantitative analysis of the data, which may reduce the accuracy and reliability of the analysis.

 There have been many attempts to prevent the occurrence of abnormal signals, but the exact cause has yet to be revealed. Even if the exact cause is revealed, it is not easy to prevent it in advance. Thus, before determining the presence or absence of a target nucleic acid sequence from a data set, it may be more practical to analyze the data set to determine if an abnormal signal has occurred and, if necessary, correct or nullify it.

In this regard, several analytical methods for identifying abnormal signals have been reported.

U.S. Patent No. 8,560,247 discloses a technique for distinguishing non-amplified data, i.e., errors such as noise and jumps, by receiving a set of data points, calculating a linear function approximating the set of data points Determining whether the slope of the linear function exceeds a maximum amplification slope by analyzing the linear function, and if the slope exceeds the maximum amplification slope, dividing the excess slope segment into a non-amplification interval of the curve . However, considering that normal signals also represent amplification data that exceeds the maximum amplification slope depending on the reaction conditions, the method is likely to determine a significant number of normal signals as errors.

In addition, U.S. Patent Application Publication No. 2015/0186598 discloses a method for determining two consecutive cycles having different signs from a second derivative of a data set to detect a jump error. However, the method uses a threshold that is not so strict to determine a jump error, and the application of the threshold is complex.

Throughout this specification, various patents and publications are referred to and cited in parentheses. These patents and publications are hereby incorporated by reference in their entirety to more fully describe the present invention and the level of skill in which the invention pertains.

The present inventors have sought to improve the conventional method of detecting abnormal signals that may be found in the data set for the target analyte. As a result, we have established a "normality-representing value " which is a parameter indicative of the steady state of the signal value in the cycle number for the data set, and the normal- A new method of changing the signal value in the candidate cycle number (s), comparing the normal-display value after the change in the candidate cycle with the normal-display value before the change, and detecting an abnormal signal .

It is therefore an object of the present invention to provide a method for detecting abnormal signals in a data set.

It is another object of the present invention to provide a computer-readable recording medium that includes instructions for implementing a processor to perform a method of detecting anomalous signals in a data set.

It is yet another object of the present invention to provide an apparatus for detecting abnormal signals in a data set.

It is yet another object of the present invention to provide a computer program stored on a computer readable recording medium embodying a processor for executing a method of detecting abnormal signals in a data set.

Other objects and advantages of the present invention will become more apparent from the following embodiments, claims and drawings.

I. Detection of Abnormal Signals in Data Sets

According to one aspect of the present invention, the present invention provides a method for detecting an abnormal signal in a data set, comprising the steps of:

(a) obtaining a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;

(b) providing a normality-representing value in each cycle number of the data set using the signal value, wherein the normal-indication value is a value indicating a normal degree of the signal value in the cycle number ;

(c) selecting a candidate cycle number (s) for an abnormal signal by the normal-indication value, wherein the normal-indication value in the candidate cycle number (s) Value;

(d) modifying the signal value in the candidate cycle number (s) and further providing a normal-indication value in the candidate cycle number (s) using the modified signal value, wherein the candidate cycle number (S) further provided corresponds to the normal-indicating value after the change;

(e) comparing the normal-display value after the change in the candidate cycle number (s) with the normal-display value before the change; And

(f) determining that the candidate cycle number (s) represents an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.

The present inventors have sought to improve the conventional method of detecting abnormal signals that may be found in the data set for the target analyte. As a result, we have established a "normality-representing value " which is a parameter indicative of the steady state of the signal value in the cycle number for the data set, and the normal- A new method of changing the signal value in the candidate cycle number (s), comparing the normal-display value after the change in the candidate cycle with the normal-display value before the change, and detecting an abnormal signal .

As used herein, the term "abnormal signal" refers to a signal that is not associated with an analyte (e.g., a target nucleic acid sequence), that is, a signal that is abruptly increased or decreased . The term "abnormal signal" is used interchangeably with an "error signal," an aberrant signal, and a "noise signal. &Quot; Abnormal signals herein include signals that indicate a sudden increase (e.g., jump, spike or step) or sudden decrease (e.g., dip) in the signal value in the amplification curve resulting from the signal amplification reaction. Causes of the abnormal signal include, but are not limited to, changes in the annealing temperature, generation of air bubbles in the reaction tube, and the presence of foreign substances in the sample.

The method of the present invention will now be described with reference to Figure 1:

Step (a): Obtaining a Data Set (110)

In step (a), a data set for the target analyte is obtained by a signal amplification reaction ( 110 ). The data set includes a plurality of data points having a cycle number and a signal value in the cycle number.

The term "target analyte" or "analyte" as used herein encompasses a variety of materials (e.g., biological and non-biological materials) and specifically includes biological materials, DNA and RNA), carbohydrates, lipids, amino acids, biological compounds, hormones, antibodies, antigens, metabolites and cells. Most specifically, the target analyte is a target nucleic acid molecule. The target analyte is present in the sample.

The term "sample" as used herein refers to any material that undergoes the methods of the present invention. In particular, the term "sample" refers to any material that contains or contemplates containing or suspected of containing a nucleic acid of interest or that is itself a nucleic acid that contains or is expected to contain a target nucleic acid sequence of interest. Most particularly, as used herein, the term "sample" includes biological samples (eg, cells, tissues and body fluids) and non-biological samples (eg, food, water and soil). Biological samples include, but are not limited to, viruses, bacteria, tissues, cells, blood, serum, plasma, lymph, sputum, swab, aspiration, bronchial wash, milk, urine, feces, Brain extract, spinal fluid (SCF), cecum, spleen and tonsil tissue extract, ascites and amniotic fluid. In addition, the sample may comprise naturally occurring nucleic acid molecules and synthetic nucleic acid molecules isolated from a biological source.

The term "target nucleic acid "," target nucleic acid sequence ", or "target sequence" as used herein means a nucleic acid sequence of interest for analysis, detection or quantitation. Target nucleic acid sequences include single strand as well as double stranded sequences. The target nucleic acid sequence includes sequences initially present in the sample as well as newly generated sequences in the reaction.

The target nucleic acid sequence includes arbitrary DNA (gDNA and cDNA), RNA molecules, and hybrids thereof (chimeric nucleic acid). The sequence may be in the form of a double strand or a single strand. When the nucleic acid as a starting material is a double strand, it is preferable to make the double strand into a single strand or a partial single strand form. Known methods for separating strands include, but are not limited to, heating, alkaline, formamide, urea and glycocalse treatment, enzymatic methods (eg, helicase action) and binding proteins. For example, strand separation can be achieved by heating at a temperature of 80-105 [deg.] C. A common method of such treatment is disclosed in Joseph Sambrook, et al., Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N. Y. (2001).

The target nucleic acid sequence may be any naturally occurring prokaryotic cell nucleic acid, eukaryotic cell (e. G., Protozoan and parasitic, fungi, yeast, higher plants, lower animals and higher animals including mammals and humans) Virus, HIV, influenza virus, Epstein-Barr virus, hepatitis virus, poliovirus, etc.) nucleic acid or viroid nucleic acid. The nucleic acid molecule may also be any nucleic acid molecule that can be produced or produced recombinantly, or that can be chemically synthesized or synthesized. Thus, the target nucleic acid sequence may or may not be found in nature.

The target nucleic acid sequence should not be construed as limiting the sequence to a sequence that is known at a given point in time or from a given point in time and should instead be interpreted to include a sequence that is available or known at some point in the present or future. That is, the target nucleic acid sequence may or may not be known at the time of carrying out the method of the present invention. In the case of an unknown target nucleic acid sequence, its sequence may be determined by one of the conventional sequencing methods prior to practicing the present invention.

If the target analyte is a target nucleic acid molecule, the sample may undergo a nucleic acid extraction procedure known in the art (see Sambrook, J. et al., Molecular Cloning , A Laboratory Manual , 3rd ed. Cold Spring Harbor Press (2001)). The nucleic acid extraction procedure may vary depending on the type of sample. In addition, when the extracted nucleic acid is RNA, a reverse transcription process for synthesizing cDNA can be additionally performed (see Sambrook, J. et al., Molecular Cloning , A Laboratory Manual , 3rd ed. Cold Spring Harbor Press (2001)).

According to one embodiment of the present invention, the target nucleic acid sequence comprises a nucleotide variation.

The term "nucleotide variation" as used herein refers to the substitution, deletion or insertion of any single or multiple nucleotides in a DNA sequence at a particular position in a contiguous DNA segment. These contiguous DNA segments include one gene or any other part of a chromosome. These nucleotide variations may be mutants or polymorphic allele variations. For example, the nucleotide variation detected in the present invention includes single nucleotide polymorphism (SNP), mutation, deletion, insertion, substitution, and translocation. Examples of nucleotide variations include various mutations in the human genome (e.g., mutations of the methylenetetrahydrofolate reductase (MTHFR) gene), mutations associated with drug resistance of the pathogen, and tumorigenic-induced mutations. As used herein, the term "nucleotide variation" includes all variations at a particular position in the nucleic acid sequence. That is, the term "nucleotide variation" includes wild type at any position in the nucleic acid sequence and all mutant forms thereof.

The data set used herein is obtained by a signal generation process.

As used herein, the term " signal generation process "refers to the ability to generate signals depending on the properties of the target analyte in the sample, i.e., activity, amount or presence (or absence) Means any process. The signal generation process herein includes biological and chemical reactions. These biological responses include genetic analysis, immunological analysis and bacterial growth analysis such as PCR, real-time PCR and microarray analysis. According to one embodiment, the signal generation process includes analyzing the generation, change, or destruction of a chemical.

The signal generation process is accompanied by a signal change. The signal change can serve as an indicator to qualitatively or quantitatively indicate the presence or absence of the target nucleic acid sequence.

The details of the "signal generation process" are disclosed in WO 2015147412 filed by the present inventors, the teachings of which are incorporated herein by reference in their entirety.

According to one embodiment, the signal generation process is a signal amplification process.

According to one embodiment of the present invention, the signal generation process is a process with or without amplification of the target nucleic acid molecule.

Specifically, the signal generation process is a process involving amplification of a target nucleic acid molecule. More specifically, the signal generation process is a process capable of increasing or decreasing the signal upon amplification of the target nucleic acid molecule (specifically, increasing the signal), accompanied by amplification of the target nucleic acid molecule.

The term "signal generation" as used herein includes the appearance or disappearance of a signal and the increase or decrease of a signal. Specifically, the term "signal generation" means an increase in the signal.

The signal generation process can be performed according to various methods known to those skilled in the art. Examples of such methods include the TaqMan ^TM probe method (U.S. Patent No. 5,210,015), the molecular beacon method (Tyagi et al., Nature Biotechnology v. 14 MARCH 1996), the Scorpion method (Whitcombe et al., Nature Biotechnology 17: 804-807 (Nazarenko et al., 2516-2521 Nucleic Acids Research, 25 (12): 2516-2521 (1997), and U.S. Patent No. 6,117,635), the Lux method Patent No. 7,537,886), CPT (Duck P, et al. Biotechniques, 9: 142-148 (1990)), LNA method (US Patent No. 6,977,295), Plexor method (Sherrill CB, American Chemical Society, 126: 4550-4556 ( 2004)), Hybeacons TM (. DJ French, et al, Molecular and Cellular Probes (2001) 13, 363-374 and US Patent No. 7,348,141), a dual-labeled self-quenching (Bernard PS, et al., Clin Chem 2000, 46, 147-148), a PTOCE (PTO cleavage and extension) method (WO < RTI ID = 0.0 > 2012/0965 23), PTE Cleavage and Extension-Dependent Signaling Oligonucleotide Hybridization (PCE-SH) method (WO 2013/115442), PTE Cleavage and Extension-Dependent Non-Hybridization (WOE) WO 2011/037306).

The signal generation process was performed using TaqMan ^TM When carried out according to the probe method, the signal generating means may comprise a primer pair, a probe having an interactive double label, and a DNA polymerase having 5 '→ 3' nuclease activity. When the signal generation reaction is carried out according to the PTOCE method, the signal generating means includes a primer pair, a Probing and Tagging Oligonucleotide (PTO), a Capturing and Templating Oligonucleotide (CTO) and a DNA polymerase having a 5 '→ 3' nuclease activity . The PTO or CTO may be labeled with a suitable label.

According to one embodiment, the signal generation process may be performed by a process including signal amplification together with target amplification.

According to one embodiment, the signal amplification reaction as a signal generation process is performed in such a manner that the signal is amplified simultaneously with the amplification of the target nucleic acid sequence (for example, real-time PCR). Alternatively, the signal amplification reaction is carried out in such a way that the signal is amplified without amplification of the target nucleic acid molecule (see, for example, the CPT method (Duck P, et al., Biotechniques, 9: 142-148 assay (U.S. Pat. Nos. 6,358,691 and 6,194,149).

Various methods of amplifying target nucleic acid molecules are known, including but not limited to PCR (polymerase chain reaction), LCR (ligase chain reaction, Wiedmann M, et al., "Ligase chain reaction (LCR) - overview and applications. Q-beta replicase amplification (Q-beta) "), GLCR (gap filling LCR, WO 90/01069, EP 0439182 and WO 93/00447) (See, for example, Cahill P, et al., Clin Chem., 37 (9): 1482-5 (1991), U.S. Patent 5,556,751), SDA (strand displacement amplification, GT Walker et al., Nucleic Acids Res. (SEQ ID NO: 16911696 (1992), EP 0497272), nucleic acid sequence-based amplification (Compton, J. Nature 350 (6313): 912 (1991)), TMA (Transcription- Mediated Amplification, Hofmann WP et al. See, for example, J Clin Virol. 32 (4): 289-93 (2005); U.S. Patent No. 5,888,779) or RCA (Rolling Circle Amplification, Hutchison CA et al., Proc. Natl Acad Sci. USA, 102: 1733217336 ).

The term "signal" as used herein means a measurable output. As used herein, the term " signal value "is a quantitative representation of a signal.

The size, change, etc. of the signal can serve as an indicator to qualitatively or quantitatively indicate the characteristics of the target analyte (target nucleic acid sequence), particularly presence or absence.

Examples of useful indicators are fluorescence intensity, luminescence intensity, chemiluminescence intensity, bioluminescence intensity, phosphorescence intensity, charge transfer, voltage, current, power, energy, temperature, viscosity, optical scatter, radiant intensity, reflectance, . The most widely used indicator is fluorescence intensity. A signal change includes an increase or decrease of the signal as well as a signal occurrence or extinction.

The signal can be any of a variety of signal characteristics obtained from signal detection, such as signal intensity (e.g., RFU (relative fluorescence unit) value or RFU value at a particular cycle number, selected cycle number, or endpoint when performing an amplification reaction) Shape (or pattern) or C _t value, or a value obtained by mathematically processing the characteristic.

According to one embodiment, the term "signal" includes not only the signal itself detected at the detection temperature, but also the modified signal provided by mathematically processing the signal.

According to one embodiment of the present invention, when obtaining an amplification curve by real-time PCR, various signal values (or characteristics) can be selected from the amplification curve and used to determine the presence of the target nucleic acid sequence _t value or amplification curve data).

The signal (in particular, signal intensity) may vary depending on the signal generating means used as well as its detection temperature.

The term " signal generating means "as used herein means a means for providing a signal indicative of a characteristic, specifically presence or absence of a target analyte to be analyzed.

As used herein, the term " signal generating means "means any material used to generate a signal indicative of the presence of a target nucleic acid sequence, including, for example, oligonucleotides, labels and enzymes. Alternatively, the term "signal generating means" as used herein can be used to mean any method of using a material for signal generation.

Various signal generating means are known in the art. The signal generating means comprises an oligonucleotide having a label itself and a label. The label includes a fluorescent label, a luminescent label, a chemiluminescent label, an electrochemical label, and a metal label. The label itself, such as an intercalating dye, can serve as a signal generating means. Alternatively, a single label or an interactive double label comprising a donor molecule and an acceptor molecule may be used as a signal generation means in the form coupled to one or more oligonucleotides.

The signal generating means may comprise additional components that generate a signal, such as a nucleic acid cleavage enzyme (5'-nuclease and 3'-nuclease).

The signal generating means generating a signal in a manner dependent on the formation of the dimer; Generating a signal using the formation of a dimer in a manner dependent on cleavage of a mediation oligonucleotide that is specifically hybridized to the target analyte; And generating a signal by cleavage of the detectoin oligonucleotide.

As used herein, the term "signal amplification reaction" means a reaction that increases or decreases the signal generated by the signal generation means.

According to one embodiment, the signal amplification reaction refers to a reaction that increases (amplifies) the signal generated by the signal generation means, depending on the presence of the target analyte. Such a signal amplification reaction may or may not involve amplification of the target analyte (e. G., Target nucleic acid molecule). Specifically, the signal amplification reaction refers to the amplification of a signal accompanied by amplification of the target analyte.

The data set obtained by the signal amplification reaction includes the cycle number.

The term " cycle number "or" cycle ", as used herein, refers to a unit of change in said condition in a plurality of measurements involving a change in condition. For example, the change in conditions includes a change in temperature, reaction time, number of reactions, concentration, pH, and / or number of copies of the target nucleic acid molecule sequence. Thus, the cycle may include temperature, time or process cycle, unit operating cycle or recycle cycle.

For example, when analyzing substrate degradation ability by enzyme according to substrate concentration, substrate degradation degree of enzyme is measured several times by varying substrate concentration. An increase in substrate concentration may correspond to a change in condition, and an incremental unit may correspond to a cycle.

As another example, isothermal amplification allows a sample to be measured several times during the reaction time under isothermal conditions, the reaction time may correspond to a change in conditions, and the unit of reaction time may correspond to the cycle. For example, if a 5 minute interval such as 5, 10, 15 minutes, etc. is set to one reaction time, the cycle may be expressed as a 5 minute cycle, a 10 minute cycle, a 15 minute cycle, or the like. Alternately, if the interval of 5 minutes is regarded as one unit, a 5-minute cycle can be represented by 1 cycle, a 10-minute cycle by 2 cycles, and a 15-minute cycle by 3 cycles.

As another example, in the case of a melting analysis or a hybridization analysis, it is possible to measure the change of the signal while changing the temperature within a certain range of temperature, the temperature may correspond to the change of the condition, Measured temperature) may correspond to the cycle. For example, when the 0.5 ° C interval is set as one reaction time such as 40 ° C, 40.5 ° C, 50 ° C, 50.5 ° C, etc., the cycle is expressed by 40 ° C cycle, 40.5 ° C cycle, 50 ° C cycle, . Alternatively, if the interval of 0.5 占 폚 is regarded as one unit, a cycle of 40 占 폚 may be represented by one cycle, a cycle of 40.5 占 폚 may be represented by two cycles, and a cycle of 50 占 폚 may be represented by three cycles.

Specifically, when repeating a series of reactions or repeating the reaction at regular time intervals, the term "cycle" or "cycle number" means one unit of the above repetition.

For example, in a polymerase chain reaction (PCR), one cycle or cycle number refers to a reaction unit comprising denaturation of the target molecule, annealing (hybridization) between the target molecule and the primer, and primer extension. An increase in the repetition of the reaction may correspond to a change in the condition, and the unit of the repetition may correspond to the cycle or the cycle number.

The data set obtained by the signal amplification reaction includes a plurality of data points, each data point having a cycle number and a signal value in the cycle number.

As used herein, the term "signal value" refers to the signal value actually measured in each cycle of the signal generation process (e.g., the actual value of the fluorescence intensity processed by the signal amplification reaction) or a variant thereof. The deformation may comprise a mathematically processed value of the measured signal value (e.g., intensity). Examples of mathematically processed values of actual measured signal values (ie, signal values of a raw data set) include, but are not limited to, adding a selected constant to the measured signal value, subtracting a selected constant from the measured signal value, A value obtained by multiplying the selected constant or dividing the measured signal value by the selected constant; The log value of the measured signal value; Or may include, but are not limited to, a derivative of the measured signal value. The term "signal" as used herein is intended to encompass the term "signal value" and therefore both terms may be used interchangeably.

The signal value used herein means the value obtained by absolute or relative quantification of the magnitude of the signal initially detected in the cycle number at the detector. The signal value is also referred to as a "zero-order signal value ", a" raw signal value ", or an "original signal value" The unit of the signal value may vary depending on the type of signal generation reaction used. For example, when a signal value is obtained at each cycle number by a real-time PCR amplification reaction, the signal value may be expressed by RFU (Relative Fluorescence Unit).

As used herein, the term "data point" means a coordinate value that includes the cycle number and the signal value in the cycle number. The term "data" refers to all information that constitutes a data set. For example, each of the cycle number and the signal value is data.

The data points obtained by the signal generation process, particularly the signal amplification reaction, can be represented by coordinate values in a two-dimensional Cartesian coordinate system. In the coordinate values, the X-axis represents the cycle number and the Y-axis represents the signal value measured or processed in the cycle number.

The term "data set" as used herein means a collection of data points. For example, the data set may be a collection of data points obtained directly by a signal amplification reaction performed in the presence of the signal generation means, or a collection of data points modified from the original data set. The data set may be all or part of a plurality of data points obtained by a signal amplification reaction or modified data points thereof. Further, the data set may be a set of data points including a cycle number and an n-order change value in the cycle number.

The data set can be plotted to generate amplification curves.

The term "amplification curve" as used herein means a curve obtained by a signal amplification reaction. Amplification curves include curves obtained when the analyte is present in the sample, or curves (or lines) obtained when no analyte is present in the sample. According to one embodiment, the data set used in the present invention is a raw dataset that has not undergone mathematical processing. According to another embodiment, the data set used in the present invention is a mathematically processed data set, for example a baseline subtracted data set to remove background signals in a raw data set. The baseline-subtracted data set can be obtained by a variety of methods known in the art (e.g., U.S. Patent No. 8,560,247).

According to one embodiment, the method of the present invention further comprises the step of performing a signal generation reaction (e.g., a signal amplification reaction) prior to step (a) to obtain a data set.

The data set used herein includes the data set obtained by the signal generating means at the detection temperature. The data set herein may be any of the data sets obtained by detection at different detection temperatures in a signal amplification reaction or a data set obtained by detection using different signal detection means.

The data sets obtained by detection at different detection temperatures can be obtained, for example, at different detection temperatures (e.g., at least two detection temperatures in each cycle number) during a signal amplification reaction using a single signal generation means in a single reaction vessel, Means a data set obtained by detecting a change in a signal value. For example, two or more data sets can be obtained from the signal amplification reaction by detection at different detection temperatures according to the MuDTl technology (WO 2015/147412) or MuDT2 technology (WO 2016/093619) developed by the present inventor , The data set used herein may be one of the data sets.

The data set obtained using different signal detection means means a data set obtained by detecting a change in the signal value using, for example, different detection means (e.g., an optical module) in a signal amplification reaction. For example, in a multiplex real-time PCR using two or more signal generating means (e.g., fluorescent labels) for the detection of two or more target nucleic acid sequences, the data set may be transferred to a different signal generating means And the data set herein may be one of the data sets.

Step (b): The provision of normal-indicative values 120 in each cycle,

The signal value is then used to provide a normality-representing value at each cycle number of the data set.

In this step, a "normal-indication value data set" including a plurality of data points having a cycle number and a normal-indication value in the cycle number is obtained.

The steady-state value refers to a value representing the normal degree of the signal value in the cycle number. The normal-indication value is calculated for each cycle number and assigned to each cycle number.

The steady-state value can be expressed in various ways as long as it indicates the normality of the signal.

In one implementation, the steady-state value is represented by a numerical value that represents a higher steady-state value. In this case, a smaller normal-indication value indicates that the cycle number with the normal-indication value is more likely to indicate an abnormal signal, while a larger normal-indication value indicates that the cycle number with the normal- And the like. For example, a particular cycle number with a normal-indication value of 1000 is likely to represent a normal signal, while another cycle number with a normal-indication value of -2000 is likely to indicate an abnormal signal. A typical example of a normal-indication value as expressed above includes a normal score, which will be described below.

In an alternative embodiment, the normal-indication value is represented by a numerical value indicating a lower normal-indication value of higher normality. In this case, a larger normal-indication value indicates that the cycle number with the normal-indication value is likely to exhibit an abnormal signal, while a smaller normal-indication value indicates that the cycle number with the normal- And the like. For example, a particular cycle number with a normal-indication value of 1000 is likely to exhibit an abnormal signal, while another cycle number with a normal-indication value of -2000 is likely to represent a normal signal.

The steady-state value at each cycle number of the data set can be provided by various methods.

In one embodiment, the steady-state value in each cycle number is a 2-5 consecutive number of cycles including each of the number of cycles, particularly a signal value in two consecutive number of cycles By calculating the change value in each cycle number. For example, the steady-state value at the tenth cycle number is provided by calculating the change value at the tenth cycle number from the signal value at 2-5 consecutive cycle numbers including the tenth cycle number .

The term " change ", "change value ", or" change value "as used herein in connection with signal values in each cycle number means the amount of change in signal value at a particular cycle number. Since the "change", "change value", or "change value" is calculated from a specific cycle number, it can be expressed as a " Can also be expressed. As used herein, the "n-th order change value" means the amount of change of the n-th order change value at a specific cycle number. Since the n-th order change value is calculated from the specific cycle number, it can be expressed as "n-th order change value of the signal value in the cycle number" or briefly "n-order change value in the cycle number"

Specific examples of the change value include a first change value (e.g., a first difference, a difference quotient and a first derivative), a second change value (e.g., a second difference, a second difference Order and second derivative), a third-order change value (e.g., third-order difference, third-order difference, and third-order differentiation), and the like.

Therefore, the steady-state value in each cycle number can be calculated by calculating a first-order change value, a second-order change value, a third-order change value, etc. of the signal value in 2-5 consecutive cycle numbers including the cycle number Can be provided.

In one implementation, the steady-state value in each cycle number can be provided by modifying the calculated change in signal value in 2-5 consecutive cycle numbers, including the cycle number. The variations include any mathematical transformation, calculation, processing or computation. A mathematical transformation, computation, processing, or computation may include addition, subtraction, multiplication, or division between the values of the changes at different cycle numbers. A mathematical transformation, computation, processing, or computation may include addition, subtraction, multiplication, or division of a change value with another factor (value).

The number of signal values used to calculate the change value includes, but is not limited to, 2, 3, 4, or 5.

If the number of signal values is 2, 3, 4, or 5, the steady-state value in each cycle number indicates the signal value in 2, 3, 4, or 5 consecutive cycle numbers including the cycle number ≪ / RTI >

A typical example of a normal-indication value is a normality score.

While the present disclosure describes a normal score for a clearer understanding of the normal display-value, those skilled in the art will appreciate that other normal-indication values may be applied instead of the normal score.

A normal score, which is an example of a normal display-value, is described in more detail below.

Normality Score

The normal score includes (i) calculating a second change value at each cycle number of the data set; And (ii) calculating a normal score at each cycle number of the data set using the secondary change value; The calculation of the normal score is carried out by a mathematical operation indicating the sign change between the secondary change values in the two consecutive cycle numbers and the magnitude of the secondary change value.

(i) Calculation of the second change value at each cycle number

First, a secondary change value is calculated in each cycle number of the data set obtained in step (a). The calculation of the second-order change value is performed by calculating the first-order change value at each cycle number of the data set using the two signal values at two consecutive cycle numbers, And calculating a secondary change value at each cycle number of the data set using the change value.

In this step, a "primary change value data set" (including a cycle number and a plurality of data points having a primary change value in the cycle number) and a "secondary change value data set" (Including a plurality of data points having a cyclic number and a signal value in the cycle number) or a modified data set thereof do.

The term "signal value" used for calculating the first-order change value and the second-order change value is a signal value excluding a value indicating a relation with other signal values (for example, a change value such as a primary change value or a secondary change value) Quot; primary signal value ", "raw signal value ", or" original signal value "

The term "immediately adjacent cycle number" as used herein for a particular cycle number means a cycle number that is consecutive to the specific cycle number, i.e., the cycle number immediately before (preceding) or immediately after (after) the particular cycle . For example, in a typical data set in which the cycle number increases by one, the cycle number immediately adjacent to the fourth cycle number is the third cycle number or the fifth cycle number.

The term "two immediately adjacent cycle numbers "," immediately adjacent two cycle numbers ", or "successive cycle numbers" as used herein means two immediately adjacent cycle numbers, i.e. two consecutive cycle numbers do. For example, in a typical data set in which the cycle number increases by 1, two immediately adjacent cycle numbers refer to cycles x and x + 1 or cycles x-1 and x.

The term " change ", "change value ", or" change value ", as used herein in connection with the signal value at each cycle number, refers to the amount (or degree) of a change in signal value at a particular cycle number it means. Since the "change", "change value", or "change value" is calculated from a specific cycle number, the "change value of the signal value in the cycle number" or briefly the "change value in the cycle number" It can also be expressed as a variation. As used herein, the "n-th order change value" means the amount (or degree) of a change in the n-1th order change value at a specific cycle number. Since the n-th order change value is calculated from the specific cycle number, it can be expressed as "n-th order change value of the signal value in the cycle number" or briefly "n-order change value in the cycle number" In particular, the zeroth order means the raw signal value. According to the above definition, the first-order change value means the amount (or degree) of the change in the zero-order change value (i.e., signal value) at a specific cycle number, Quot; means the amount (or degree) of the change in the value (i.e., the amount (or degree) of the change in the signal value). As will be described below, it will be understood that the first-order change value and the second-order change value at a specific cycle number include those calculated in a cycle number other than the specific cycle number in the broad sense. The term " change value "can be used interchangeably with the term" change rate ".

In this step, the secondary change value in each cycle number is obtained by using the signal value in each cycle number. Specifically, the second change value is calculated by calculating the first-order change value at each cycle number of the data set using two signal values at two consecutive (immediately adjacent) cycle numbers, then two consecutive ) ≪ / RTI > is obtained by calculating the secondary change value at each cycle number of the data set using the two primary change values in the cycle number.

The calculation of the secondary change value may be performed in the same or different manner as the calculation of the primary change value.

The change value may be any one selected from the group consisting of a difference, a difference quotient, and a derivative, and therefore the n-th change value (e.g., the first change value and the second change value) Differential, n-order, or n-th derivative.

The change value, particularly the difference (difference value), the difference (the difference value) and the derivative (the derivative value) can be calculated or obtained by various methods known in the art.

For example, the difference used herein can be obtained by calculating the difference between the signal values in two immediately adjacent cycle numbers. The titer used herein can be obtained by dividing the difference by the interval between two immediately adjacent cycle numbers. Differences used herein can be obtained by applying a least square method to the signal values at two, three, four or more data points, or by determining the tangent (slope) at each cycle number in the amplification curve.

The symbols y (x), D (x), D '(x) and D "(x) used in calculating the secondary change values will have the following meanings:

The symbol y (x) means the signal value at the xth cycle number; D '(x) means a first-order change in the x-th cycle number; In the above definition, x is an integer equal to or greater than 1, meaning a specific cycle number in the data set. For example, if the obtained data set is 45 (Cycle number 1), the second cycle number (cycle number 2), and the 45th cycle number (cycle number 45), each cycle number is distinguished .

The secondary change value used herein may be any one selected from the group consisting of a second-order differential, a second-order differential, and a second-order differential.

The second difference is calculated by calculating the first difference (including the cycle number and the plurality of data points having the first difference in the cycle number) in each cycle number using the two signal values in two immediately adjacent cycle numbers (Including a plurality of data points having a cycle number and a second difference in the cycle number) in each cycle number using two first-order differences in two adjacent cycle numbers .

Differences used herein can be calculated in various ways known in the art.

In one implementation, the second difference (or second order) is computed by a forward difference method or a backward difference method.

For example, a first difference may be calculated from two signal values by an inversion method or a backward difference method, and then a second difference may be calculated from two first differences by an inversion method or a backward difference method. The forward differential method can be applied to the calculation of both the first and second differentials, or the backward differential method can be applied to the calculation of both the first and second differentials, or the forward differential method can be applied to the calculation of the first differential. And the backward difference method can be applied to the calculation of the second difference or the backward difference method can be applied to the calculation of the first difference and the forward difference method can be applied to the calculation of the second difference.

According to the forward differential method, the second differential can be calculated using the following equations ( I) and ( II ) sequentially, or by using the following equation ( III ) alone.

Equation I

D '(x) = y (x + 1) - y (x)

(II)

D "(x) = D '(x + 1) - D' (x)

(III)

D (x) = y (x + 2) - 2 * y (x + 1) + y

In the above equation, y (x), y (x + 1), and y (x + 2) represent the signal values at the xth cycle number, the x + 1th cycle number, and the x + 2th cycle number, respectively; D '(x) represents the first difference in the x-th cycle number; D "(x) represents the second difference in the x-th cycle number.

According to the backward differencing method, the second difference can be calculated using the following equations ( IV) and ( V ) sequentially, or by using the following equation ( VI ) alone.

Equation IV

D '(x) = y (x) - y (x-1)

Equation V

D "(x) = D '(x) - D' (x-1)

Equation VI

D "(x) = y (x) - 2 * y (x-1) + y (x-

Wherein y (x), y (x-1) and y (x-2) represent the signal values at the xth cycle number, the x-1 th cycle number and the x-2 th cycle number, respectively; D '(x) represents the first difference in the x-th cycle number; D "(x) represents the second difference in the x-th cycle number.

For example, in the case of the forward differential method, when D (1), D (2), D (3), D (4) (= 8-1), 22 (= 30-8), 70 (= 100-30) and 400 (= 1), D '(2), D' (= 22-7), 48 (= 70-22), and 330 (= 400-70), respectively, while D "(1), D" D '(2) where y (1), y (2), y (3), y (4) and y (5) are 1, 8, 30, 100 and 500, (= 8-1), 22 (= 30-8), 70 (= 100-30), and 400 (= 500-100), D '(3), D' ) And D "(3), D" (4) and D "(5) would be 15 (= 22-7), 48 (= 70-22) and 330 (= 400-70), respectively.

(X) = y (x) - y (x + 1) or D '(x) = y (X + 1), D "(x) = y (x) - 2 * y (x + 1) ) + y (x + 2), D "(x) = D '(x-1) -D' ) + y (x). < / RTI >

For example, when the signal amplification reaction is performed up to 45 cycle numbers, D "(45) and D" (x) are not calculated 44) can not be calculated because there is no value of the signal at the 46th cycle number or the 47th cycle number.

Similarly, in the backward differencing method, D "(x) is not calculated in the first cycle and immediately after the first cycle. For example, if the signal amplification reaction is performed up to 45 cycle numbers, D" (1) and D (2) can not be calculated because there is no signal value in the -1st cycle number or the 0th cycle number.

As such, functions such as y (x), D (x), D "(x) and D" (x) are not computed for a cycle number that does not exist or can not be defined.

Note that the results obtained by the forward and backward differencing methods have certain interchangeability with respect to the cycle number.

Specifically, D '(x) obtained by the forward differential method is the same as D' (x + 1) obtained by the backward differential method. For example, the first difference in the first cycle number obtained by the forward differential method is the same as the second difference in the second cycle number obtained by the backward difference method. Thus, in view of this interchangeability, one skilled in the art can easily convert the results of the forward differential method into the results of the backward differencing or vice versa. For example, when the first difference is obtained by the forward differential method, the first difference calculated in the x + 1th cycle number is regarded as the first difference in the xth cycle number in order to convert to the result of the backward difference method .

Further, D "(x) obtained by the forward differential method is the same as D" (x + 2) obtained by the backward differential method. For example, the second difference in the first cycle number obtained by the forward differential method is the same as the second difference in the third cycle number obtained by the backward difference method.

Thus, in view of this interchangeability, one skilled in the art can easily convert the results of the forward differential method into the results of the backward differencing or vice versa. For example, when a second-order differential is obtained by the forward differential method, the second-order differential calculated at the x + 2th cycle number is regarded as the second-order differential at the x-th cycle number .

Calculation of the second-order difference by the backward difference method is illustrated in the embodiment of the present application. However, those skilled in the art will be able to use the forward differential method instead of the backward differential method and only change the cycle number to obtain the same result as the backward differential method. Thus, it will be appreciated that the primary and secondary differences in a particular cycle herein may include those calculated in different cycles, depending on the computation used.

(ii) calculation of normal scores at each cycle number

Next, the secondary change value is used to calculate the normal score at each cycle number of the data set.

In this application, a "normal score data set" is obtained that includes a plurality of data points having a normal number in the cycle number and the cycle number.

The calculation of the normal score is carried out by a mathematical operation indicating the sign change between the secondary change values in the two consecutive cycle numbers and the magnitude of the secondary change value.

As used herein, the term "normal score" (abbreviated as " NS ") refers to a sign change between a second change value in two immediately adjacent cycle numbers and a second change value in two immediately adjacent cycle numbers Quot; and " size " The normal score may be a number indicating the extent of normality of signals obtained by the signal amplification reaction. A small normal score indicates that the cycle number with the normal score is likely to represent an abnormal signal. For example, a particular cycle number with a normal score of 1000 is likely to represent a normal signal, while another cycle number with a normal score of -2000 is likely to exhibit an abnormal signal.

The normal score is used not only to select the candidate cycle number among all the cycle numbers in the data set but also to use the normal score before the change of the signal value (also called the "pre-change score") and the normal score after the change of the signal value Quot;) is used to determine an abnormal signal.

As used herein, the term "normal score in a cycle number" refers to a normal score calculated using a second change value at a specific cycle number and a second change value at a cycle number immediately adjacent to the specific cycle number, (Assigned) to a specific cycle number. It may be described in various expressions, such as a normal score obtained from the signal value in the cycle number, a normal score obtained from the secondary change value of the signal value in the cycle number, a normal score calculated in the cycle number, or a variation thereof. It should be understood that the normal score at a particular cycle number may include those calculated at different cycle numbers in the broad sense.

The immediately adjacent cycle number used to calculate the normal score at the xth cycle number includes the cycle immediately before or after the xth cycle. For example, in a typical data set in which the cycle number increases by 1, the immediately adjacent cycle number of the xth cycle number is cycle number x + 1 or cycle number x-1.

The normal score is obtained by a mathematical operation indicating the sign change between the second change value in two immediately adjacent cycle numbers and the magnitude of the second change value. As described above, the secondary change value may be, for example, a second-order differential, a second-order differential, or a second-order differential.

According to an embodiment of the present invention, the normal score in the x-th cycle number is a mathematical operation that indicates a sign change between the x-th cycle number and the x-th cycle number and the second- Lt; / RTI >

According to another embodiment of the present invention, the normal score in the xth cycle number is a mathematical expression indicating the sign change between the xth cycle number and the second change value in the x-th cycle number and the magnitude of the second change value. Lt; / RTI >

The sign change used herein is such that the second-order change value at the x-th cycle number has a positive sign (positive value, +) and the second-order change value at the x + 1 or x- (Negative value, -). A mathematical operation indicating the sign change between the secondary change values is performed when the secondary change value in the xth cycle number has a positive sign and the secondary change value in the x + 1 or x-1th cycle number is a negative sign , The secondary change value in the xth cycle number and the secondary change value in the x + 1 or x-1th cycle number are all the same sign (for example, all positive values or all Negative < / RTI > value), it is an arbitrary operation that provides a positive normal score.

As used herein, the magnitude of the secondary change value represents the magnitude of the secondary change value in the xth cycle number and the magnitude of the secondary change value in the x + 1 or x-1th cycle number.

Examples of mathematical operations that express the magnitude of the sign change and the secondary change value between the secondary change values include mathematical amplification (e.g., multiplication) of the secondary change values, mathematical ratios (e.g., division) do.

According to one embodiment, the normal score is calculated by multiplying the second-order variance value in two immediately adjacent cycle numbers. The multiplication of the secondary change values effectively represents the sign change between the secondary change values and the magnitude of the secondary change value.

More specifically, the normal score can be calculated by the following equation ( VII) or ( VIII )

Equation VII

NS (x) = D "(x) * D" (x + 1)

(X + 1) represents the second-order change value at the x-th cycle number, and D "(x + Represents a secondary change value in the cycle number, and x is an integer of 1 or more.

Formula VIII

NS (x) = D "(x) * D" (x-1)

(X) represents a normal score at the x-th cycle number, D "(x) represents a secondary change value at the x-th cycle number, and D" Represents a secondary change value in the cycle number, and x is an integer of 2 or more.

In the above Equations VII and VIII , D "(x-1), D" (x) and D "(x + 1) represent the second differences in the cycle numbers x-1, x and x + 1, respectively.

For example, the D "(1), D" (2), D "(3) and D" if the (4), each -100, 50, 350, -400, NS (1), formula VII NS (2) and NS (3) are -5000 (= -100 * 50), 17500 (= 50 * 350) and -14000 (= 350 * -400), respectively; Would be, 17500 (= 50 * 350), and -14000 (= 350 * -400) a NS (2), NS (3) and NS (4) for the formula VIII 5000 (100 * 50 =) .

Note that the normal score at the last cycle number can not be calculated using Equation VII , whereas the normal score at the first cycle number can not be calculated using Equation VIII .

It is also noted that the normal score obtained by equation VII and the normal score obtained by equation VIII have a certain mutual conversion potential for the cycle number.

Specifically, NS (x) obtained by equation ( VII ) is the same as NS (x + 1) obtained by equation ( VIII ). For example, the normal score at the fourth cycle number obtained by equation ( VII) is equal to the normal score at the fifth cycle number obtained by equation ( VIII ).

Thus, in view of this interchangeability, one skilled in the art can easily convert the normal scores obtained by equation VII into the normal scores obtained by equation VIII , and vice versa.

The calculation of the normal score according to Equation VII is illustrated in the embodiments of the present application. However, those skilled in the art using the formula VIII in place of VII equation calculates a normal score at each cycle number, and then, by adjusting the cycle number, i.e., by subtracting one from the calculated cycle number, the same as the formula VII You will get results. Thus, it should be understood that the normal score at a particular cycle number may include a normal score calculated at different cycle numbers, depending on the method of calculation.

On the other hand, the calculation of the normal score using Equation ( VII) or ( VIII) can be variously combined with the calculation of the second-order change value using the forward differential method or the backward differential method.

For example, the calculation of the second-order differential using the forward differential method can be combined with the calculation of the normal score using Equation VII ; The calculation of the second-order differential using the forward differential method can be combined with the calculation of the normal score using Equation VIII ; The calculation of the second-order differential using the backward differencing method can be combined with the calculation of the normal score using Equation VII ; The calculation of the second order differential using the backward differencing method can be combined with the calculation of the normal score using Equation VIII .

However, in the various combinations of either the forward or backward differencing and either of the formulas VII or VIII , the cycle number with the same normal score will have a certain regularity, and thus an abnormal signal It should be noted that the cycle numbers shown will also vary with certain regularities.

For example, if the combination of the forward differencing and the equation VII produces a normal score of -63 in the second cycle number, the combination of the forward differential and the equation VIII will produce the same normal score in the third cycle number, The combination of backward differencing and equation ( VII) will produce the same normal score in the fourth cycle number, and the combination of backward differencing and equation ( VIII) will produce the same normal score in the fifth cycle number. Therefore, the cycle number representing the abnormal signal may vary depending on the calculation method of the normal score.

The inventors have confirmed that the cycle number theoretically determined to represent an abnormal signal by the combination of the backward differencing method and the formula VII represents an abnormal signal in the visual inspection of the actual data set. This proves that the method of the present invention using backward differencing and the combination of Equation VII is very accurate and effective in determining the cycle number representing an abnormal signal. However, those skilled in the art will be able to use other combinations when considering the above-described rules of cycle number change. For example, if a combination of the forward differencing and the equation VII is used, the cycle number representing the abnormal signal can be adjusted by adding the cycle number 2 to the result. Thus, it will be understood by those skilled in the art that these various combinations fall within the scope of the present invention.

As described above, according to the forward or backward differencing method and the combination of the formula VII or the formula VIII , the first order difference, the second order difference and the normal score corresponding to each cycle number can be changed with a certain regularity. Thus, it should be understood herein that the first order differential, second order differential and normal score at a particular cycle number may include those calculated at different cycle numbers.

The calculation of the normal score by the combination of the backward differencing and the equation VII can also be confirmed in the present embodiment.

Step (c): The selection 130 of the candidate cycle number (s) for the abnormal signal by the normal-

In this step, a candidate cycle for an abnormal signal is selected by the normal-indication value, and the normal-indication value in the candidate cycle (s) corresponds to the normal-indication value before the change ( 130 ). In particular, if the normal-indication value is a normal score, the candidate cycle (s) for the abnormal signal is selected by the normal score.

The term "candidate cycle number " as used herein means a cycle number that is likely to exhibit an abnormal signal or is expected to exhibit an abnormal signal.

The present inventors have found that a normal-indication value such as a normal score presented by the present inventors is highly related to an abnormal signal, that is, a normal-indication value such as a normal score can be used as an indicator for an abnormal signal. According to the findings of the present inventors, when the normal-indication value is the normal score and the normal score is calculated by the formula VII or VIII , the smaller the normal score calculated in the specific cycle number, the more likely that the cycle number is indicative of an abnormal signal high. Thus, the steady-state value, such as the normal score, is used to find the candidate cycle number for the abnormal signal.

The expression "selecting the candidate cycle number (s) for the abnormal signal by the normal score" means selecting the candidate cycle number (s) based on its normal-indication value, It means that it serves as a criterion for selecting a number.

The selection of the candidate cycle number can be made based on the normal-indication value, in particular the magnitude of the normal score (large or small). For example, the normal score "70" is considered to be larger in magnitude than the normal score "-80 ".

The selection of the candidate cycle number can be achieved by a variety of methods as follows:

In one implementation, when the larger normal-indication value indicates a higher normal degree in the cycle number, the selected candidate cycle number is a cycle number with a normal-indication value less than the threshold value.

The selection of the candidate cycle number may be implemented by applying a threshold to the steady-state value at all cycle numbers and selecting the cycle number (s) with a steady-state value that is less than the threshold value.

The number of candidate cycle number (s) selected may be zero or more. For example, if there is no cycle number having a normal-indication value smaller than the threshold value, the number of candidate cycle numbers to be selected is zero. If there is only one cycle number having a normal-indication value smaller than the threshold value, the number of candidate cycle numbers selected is one. If there are a plurality of cycle numbers having normal-indication values smaller than the threshold value, the number of candidate cycle numbers to be selected is more than one.

The threshold value used to select the candidate cycle number may have a signal value of less than 0 in view of the high likelihood that the cycle number with a small steady-state value will exhibit an abnormal signal. The threshold can be determined empirically or experimentally. The threshold may be, for example, -100, -200, -300, -400, -500, -600, -700, -800, -900, -1000, -2000, -3000, -4000 or less Value) of RFU (relative fluorescence unit).

In another embodiment, when the larger normal-indication value indicates a higher normal degree in the cycle number, the selected candidate cycle number is a cycle number having a normal-indication value that is less than the threshold and is at least the minimum.

The selection of the candidate cycle number may be implemented by applying a threshold to the steady-state value at all cycle numbers and selecting the cycle number (s) having a steady-state value that is less than and less than the threshold value.

The number of candidate cycle number (s) selected may be 0 or 1. For example, if there is no cycle number having a normal-indication value smaller than the threshold value, the number of candidate cycle numbers to be selected is zero. If there is more than one cycle number with a steady-state value less than the threshold value, the number of candidate cycle numbers selected is one.

The threshold value used to select the candidate cycle number may have a signal value of less than 0 in view of the high likelihood that the cycle number with a small steady-state value will exhibit an abnormal signal. The threshold can be determined empirically or experimentally. The threshold may be, for example, -100, -200, -300, -400, -500, -600, -700, -800, -900, -1000, -2000, -3000, -4000 or less Value) of RFU (relative fluorescence unit).

In another embodiment, when the larger normal-indication value indicates a higher normal degree in the cycle number, the selected candidate cycle number is a cycle number having a negative sign and a minimum normal-indication value.

The selection of the candidate cycle number is carried out by not using the threshold value, that is, selecting the cycle number having the negative sign and the minimum normal-display value as the candidate cycle number.

The number of candidate cycle number (s) selected may be 0 or 1. For example, if there is no cycle number having a negative sign, the number of candidate cycle numbers to be selected is zero. If there is more than one cycle number with a negative sign, then the number of candidate cycle numbers selected is one.

In any of the implementations described above, it is contemplated that any of the embodiments that meet the defined criteria (e.g., have a normal-indication value that is less than the threshold value, a normal-indication value that is less than the threshold value, If there is no cycle number (with a normal-indication value), no candidate cycle is selected in the data set. This indicates that the data set analyzed by the present invention does not include a cycle number representing an abnormal signal. In this case, an indication that the data set obtained in step (a) does not contain an abnormal signal, that is, an indication that the data set is composed of a normal signal, may be displayed.

In an alternative embodiment, if the smaller normal-indication value represents a higher normal degree of signal value at the cycle number, then the candidate cycle is: (i) a cycle having a normal-indication value greater than the threshold value selected from a value greater than zero number; (ii) a cycle number having a normal-indication value that is greater than and greater than a threshold value selected from a value greater than zero; Or (iii) a cycle number having a positive sign and a maximum normal-indication value.

As described above, in selecting the candidate cycle number, the normal-display value in the candidate cycle number is adopted as the pre-change value in the candidate cycle number.

As used herein, the term " pre-alteration normal value-display value "(e.g., pre-change normal score) is a normal-display value provided in step (b) or a normal-display value corresponding to the selected candidate cycle number , Normal score). The pre-change steady-state value (e.g., normal score) is calculated at a specific cycle number in step (b), which is assigned to a specific cycle number. That is, the normal-display value before change (for example, the normal score) is calculated by using the signal value before being changed by the signal change method in step (d) (that is, by using the unchanged signal value or the pre- ) Calculated from a specific cycle number

The term "pre-change normal-display value" (e.g., the pre-change normal score) is distinguished from the "normal post-change value"

The pre-change pre-display value (e.g., pre-change pre-change score) in the candidate cycle number is not newly calculated or generated in this step, but is provided or obtained simultaneously or automatically upon selection of the candidate cycle number.

Specifically, a normal-indication value (e.g., normal score) at every cycle number is provided at step (b), and a normal-indication value at the candidate cycle number (e.g., normal score) Is assigned or assigned a normal-indication value (e.g., a normal score before change). Thus, the normal-indication value (e.g., normal score) at the candidate cycle number corresponds to the pre-change indication-value (e.g., the pre-change normal score).

(For example, the normal score before the change) in the candidate cycle number is compared with the "modified normal-display value" (e.g., the normal score after the change) in the candidate cycle number, Is indicative of an abnormal signal.

Step (d): Providing 140 the modification of the signal value in the candidate cycle number and the addition of the normal-

In this step, the signal value in the candidate cycle number (s) is changed, and furthermore, a normal-indication value in the candidate cycle number (s) is further provided using the changed signal value, and the candidate cycle number ( 140 ) corresponds to the normal-indication value after the change.

The modifiers "pre-alteration" and "post-alteration" are used to change the signal value at the candidate cycle number obtained before changing the signal value at the two-element candidate cycle number Is used herein to distinguish another obtained. The modifier "before change" can be used interchangeably with "unchanged", and the modifier "after change" can be used interchangeably with "changed".

In this regard, the term " pre-change signal value "refers to the signal value at a particular cycle number that has not yet changed (in particular, the candidate cycle number) Lt; / RTI > The term " cycle number before change "refers to the cycle number with the signal value before change, while the term " cycle number after change" refers to the cycle number with the signal value after change. The term "first difference before change "," second difference before change "and" normal change before change " (E.g., "normalized score after change"), while the term "difference after first change", "second difference after change", and " Quot;) refers to the first-order, second-order, and normal-indication values (e.g., normal score) calculated in the cycle number after the change. In addition, the term " pre-change data set "refers to a data set consisting of pre-change signal values, while the term " post-change data set" refers to a data set that includes one or more post-

In this step, the signal value at the candidate cycle number can be varied in a variety of ways, including signal correction methods known in the art.

The signal value at the candidate cycle number can be changed by the signal change method (method) described herein.

As used herein, the term " signal change scheme (method) "means a means or rule for changing a signal value at a candidate cycle number to another suitable signal value. The signal change method (method) may include, for example, changing direction of the signal value in the candidate cycle (e.g., whether the signal value in the candidate cycle number is increasing or decreasing) and degree of change (e.g., How much the value increases or decreases). Alternatively, the signal change method (method) is a means for determining a post-change signal value (greater or less than the pre-change signal value) at which the pre-change signal value in the candidate cycle is changed.

The signal changing method according to the present invention will be described in detail as follows.

In one implementation, the signal modification scheme involves modifying the signal value at the candidate cycle number so that its absolute value decreases. That is, the signal value at the candidate cycle number is changed by the signal change method so that its absolute value decreases.

According to one embodiment, such a change does not include a change in sign value of the signal value.

For example, assuming that the signal value at the candidate cycle number is "+10 ", such a change in the signal value is, for example, +9, +8, +7, +6, +5, +4, For example, -1, -2, -3, -4, -5, -6, -7, -8, -9, etc. . Similarly, assuming that the signal value at the candidate cycle number is "-10 ", such a change in the signal value is, for example, -9, -8, -7, -6, -5, -4, 3, -2, -1, etc., but the change to +1, +2, +3, +4, +5, +6, +7, +8, do not include.

According to one embodiment, the absolute value of the signal value in the candidate cycle number is reduced to 50% or less, 40% or less, 30% or less, 20% or less, 10% or less, or 5% or less of the value before the change.

In a particular implementation, the signal modification scheme changes the signal value in the candidate cycle number such that its absolute value is greater than or equal to a relatively small absolute value of the signal values in the two cycle numbers immediately adjacent to the candidate cycle number . That is, the signal value in the candidate cycle number is changed so that its absolute value is greater than or smaller than the relatively small absolute value of the signal values in the two cycle numbers immediately adjacent to the candidate cycle number.

For example, assuming that the signal value at the candidate cycle number is "11" and the two signal values at the cycle number immediately adjacent to the candidate cycle number are "6" and "8", the signal at the candidate cycle number The value "11" can be changed to any signal value that is smaller than "11 " and" 6 " Assuming that the signal value in the candidate cycle number is "-11" and the two signal values in the cycle number immediately adjacent to the candidate cycle number are "-6" and "-8", the signal value in the candidate cycle number "-11" may be changed to any signal value that is greater than "-11" and less than or equal to "-6 ".

In one implementation, the signal modification scheme is configured to change the signal value in the candidate cycle number by the signal modification scheme such that its absolute value is less than a relatively large absolute value of the signal values in the two cycle numbers immediately adjacent to the candidate cycle number .

In a further specific embodiment, the signal modification scheme alters the signal value in the candidate cycle number such that its absolute value is close to a relatively small absolute value of the signal values in the two cycle numbers immediately adjacent to the candidate cycle number . That is, the signal value in the candidate cycle number is changed by the signal change method such that its absolute value is close to a relatively small absolute value of the signal values in the two cycle numbers immediately adjacent to the candidate cycle number.

For example, assuming that the signal value at the candidate cycle number is "11" and the two signal values at the cycle number immediately adjacent to the candidate cycle number are "6" and "8", the signal at the candidate cycle number The value "11" may be changed to a value close to "6 ", for example, 6.1, 6.2,

In a further particular embodiment, the signal modification scheme comprises modifying the signal value at the candidate cycle number such that its absolute value is close to the signal value at the cycle number immediately before the candidate cycle.

In one implementation, the signal value at the candidate cycle number may be (i) a relatively small absolute value of the signal values at two cycle numbers immediately adjacent to the candidate cycle number, or (ii) The signal value after the change is within 150% -50%, within 140% -60%, within the range of 130% -70%, or between 120% -80% of the reference signal value when the reference signal value such as the signal value is changed. , Within 110% -90% or within 105% -95%. In one implementation, the modified signal value is less than 150%, less than 140%, less than 130%, less than 120%, less than 110%, or less than 105% of the value of the reference signal. In one embodiment, the modified signal value is at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95% of the reference signal value.

In one implementation, the signal modification scheme provides a modified signal value that is greater than or equal to the reference signal value in the data set representing the signal increase curve, or a modified signal value that is less than or equal to the reference signal value in the data set representing the signal reduction curve.

In one implementation, a change by a signal change scheme does not include a change in the sign value of the signal value.

In another embodiment, the signal modification scheme includes changing the signal value in the candidate cycle number such that the first-order change value in the candidate cycle number decreases. That is, the signal value in the candidate cycle number is changed by a signal change method for decreasing the first-order change value in the candidate cycle number.

In another embodiment, the signal change method may include decreasing the signal value in the candidate cycle number when the second change value in the candidate cycle number is negative, or decreasing the signal value in the candidate cycle number when the second change value in the candidate cycle number is positive , Increasing the signal value at the candidate cycle number.

The sign of the secondary change value in the candidate cycle number is associated with an increase or decrease in the signal value in the candidate cycle number.

The second change value of the positive number indicates that the first change value in the candidate cycle number is larger than the first change value in the cycle number immediately before the candidate cycle, because the signal value in the candidate cycle number is larger than the candidate cycle number Which is relatively larger than the signal value at the previous cycle number. On the contrary, the secondary change value of the negative number in the candidate cycle number indicates that the first change value in the candidate cycle number is smaller than the first change value in the cycle number immediately before the candidate cycle, Is relatively smaller than the signal value in the cycle number immediately before the candidate cycle number. Therefore, the direction of change (increase / decrease) of the signal value in the candidate cycle number can be determined based on the sign (positive sign or negative sign) of the second difference in the candidate cycle number. The second change value in the candidate cycle number may be a second order difference, a second order difference, or a second order differential of the signal value, especially a second order difference of the signal value as described above.

In implementations that use the sign of the second difference in the candidate cycle number, the signal change scheme may either reduce the signal value in the candidate cycle number if the second change value in the candidate cycle number is negative, And increasing the signal value at the candidate cycle number if the second change value in the cycle number is a positive number.

In a particular implementation using the sign of the second order difference in the candidate cycle number, if the second order change in the candidate cycle number is a positive number, then the signal modification scheme of step (d) And decreasing the signal value at the candidate cycle number to be at least a relatively small signal value among the signal values at the two cycle numbers immediately adjacent to the cycle number.

 In a particular implementation using the sign of the second difference in the candidate cycle number, if the second change in the candidate cycle number is negative, the signal modification method of step (d) And increasing the signal value at the candidate cycle number to be less than the relatively large signal value among the signal values at the two cycle numbers immediately adjacent to the candidate cycle number.

Specifically, when the secondary change value in the candidate cycle number is a positive number, the signal value in the candidate cycle number is smaller than the signal value in the candidate cycle number, and the other one of the two cycles immediately adjacent to the candidate cycle number Value. ≪ / RTI > For example, if a cycle number having a signal value of "11" as the candidate cycle number among the three consecutive signal values "6 "," 11 ", and "8" is selected and the secondary change value in the candidate cycle number is positive , The signal value "11" in the candidate cycle number may be changed to any signal value that is smaller than "11" An example of a signal value (post-change value) at which the signal value at the candidate cycle number is changed may include 10, 9, 8, 7 or 6 (including all values between these numbers). The post-change value may be arbitrarily selected within the range.

Alternatively, when the second change value in the candidate cycle number is negative, the signal value in the candidate cycle number is relatively larger than the signal value in the candidate cycle number and immediately adjacent to the candidate cycle number It can be changed to another value that is less than or equal to the larger value. For example, if a cycle number having a signal value of "3" as the candidate cycle number among three consecutive signal values "6 "," 3 ", and "8" is selected and the second- If it is negative, the signal value "3" in the candidate cycle number can be changed to any signal value that is greater than " 3 " An example of a signal value (post-change value) at which a signal value at a candidate cycle number is changed may include 4, 5, 6, 7 or 8 (including all values between these numbers). The post-change value may be arbitrarily selected within the range.

  In a further embodiment, if the normal score is used as an example of a steady-state value, the signal value at the candidate cycle number is: (i) the first change value before the change in the candidate cycle number and Obtaining a first change value after the change in the candidate cycle number using the pre-change score of the candidate cycle number; and (ii) Is changed to the post-change signal value obtained by the step of obtaining the post-change signal value. According to an embodiment, the absolute value of the first-order change value after the change in the candidate cycle number is smaller than the absolute value of the first-order change value before the change in the candidate cycle number. If the normal score is used as an example of a normal-indication value, the pre-change primary change value in the candidate cycle number and the pre-change score in the candidate cycle number provide a smaller absolute value of the post-change primary change value Can be used to set the expression. In one implementation, the smaller absolute value of the post-change primary change value may provide a post-change signal value close to the signal value in the cycle number immediately before the candidate cycle number.

According to this embodiment, the pre-change primary change value may be calculated using two signal values in two consecutive cycle numbers. The first change value before the change may be the first difference before the change. The first difference before the change can be calculated by the forward differential method as in Equation ( I) or the backward difference method as in Equation ( IV ).

According to a particular implementation, if the normal score is used as an example of a normal-indication value, the pre-change score in the candidate cycle number can be calculated by the formula VII or VIII .

The post-change signal value in the candidate cycle number may be calculated by adding the pre-change signal value in the cycle number immediately adjacent to the candidate cycle number to the first change value after the change in the candidate cycle number.

This embodiment can be further implemented using Equations IX and X below.

The signal value (signal value before the change) in the candidate cycle number can be changed to the signal value (signal value after change) determined by the equations ( IX) and ( X ).

Equation IX

Wherein R, D _{'after the change} (c) denotes the first change value after a change in the candidate cycle number, D' _non-modified (c) denotes a first change value before change in the candidate cycle number, _NS-modified (c) represents the pre-change score in the candidate cycle number; k is a number of 1 or more; and c represents the candidate cycle number.

Equation X

y _{After change} (c) = _Before y _change (c-1) + _{After changing} D '(c)

(C) _{After the} above formula, y represents the _change after the change in the candidate signal cycle number value, _y-modified (c-1) indicates a non-modified signal value in the (candidate cycle number -1), D _{'change and then} (c) shows a first variation of the value after the change in the candidate cycle number calculated by the following equation IX.

Be calculated by y _{changed since the} (c-1) - after a change in the candidate cycle numbers first change value (D (c) = y _{change after} (c) _{after the change, after the change} (c)) is formula D ' _after, y can _change (c) may be represented by the equation y _{after the change} (c) = y _{change after} (c-1) + D _{'after the change} (c). (c-1) _after y _change can be considered to be the same as (c-1) _before y _{change in} view of the fact that the signal value in the (c-1) th cycle number is not _changed . Therefore, (c) _{after the} y _change can be calculated by the sum of (c-1) _{before the} y _change and (c) _{after the} D ' _change as shown in the equation ( X ).

In the above equation ( IX ), k may be approximately 1, in particular a number of 1.

An example of a signal change method using Equations IX and X will be described below.

When the signal values at the c-th cycle number (as the candidate cycle) are changed using the equations IX and X , the first difference (D ' _{before change} c) and the pre-change score at the candidate cycle number ( _{Before the} NS _change (c)) is applied to the equation ( IX ) to obtain the first difference (D ' _{after the change} (c)) _after the change in the candidate cycle number.

For example, if the candidate cycle number (e.g., the tenth cycle number) is the signal value of "8916.60" (RFU), the first difference before the change of "128.81" , The first difference after the change in the candidate cycle can be calculated by Equation IX as follows:

Subsequently, the signal value ( _before y _change (c-1)) in the cycle number immediately before the candidate cycle and the first difference (D ' _{after the change} ) in the candidate cycle number are applied to the formula ( X ) , And obtains the signal value after the change (y _{after the change} (c)) in the candidate cycle number.

For example, 9 assuming that the signal values at the first cycle number is 8797.79, changes after the signal value at the prospective cycle number can be calculated by the following formula X as follows: y _{change after} 10 = 8787.79 + 0.90 = 8788.69.

As a result, the signal value at the prospective cycle number, "8916.60" can be changed to another signal value "8788.69" according to the equation IX and X.

A signal modification scheme according to this embodiment of the present invention is shown in FIG. As shown in FIG. 4, the signal value (10 _before y _change ) in the candidate cycle number is replaced with the _post-change signal value (10 _after y _change ) in the candidate cycle number.

Thus, using Equations IX and X , it is possible to automatically provide a post-change signal value in a candidate cycle, thereby providing the original signal value in the candidate cycle to another signal value, Can be replaced automatically.

After the signal value in the candidate cycle number is changed as described above, the normal-display value in the candidate cycle number is additionally provided using the changed signal value (the changed signal value). In particular, when the normal score is used as an example of a normal-indication value, a normal score in the candidate cycle number is additionally provided using the changed signal value (post-change signal value).

The normal-display value or normal score further provided in the candidate cycle number using the changed signal value is referred to as the " normal after-change value "or the" normal after change score "in the candidate cycle number. Thus, the normal-indication value or normal score further provided in the candidate cycle number (s) corresponds to the post-change normal-indication value or the post-change normal score

As used herein, the term " normal post-alteration value "or" normal post-change score "refers to a normal value, calculated at a particular cycle number, using the signal value changed in step (d) - refers to a displayed value or a normal score.

The normal-display value after change or the normal score after change can be calculated in the same manner as the normal-display value before change or the change-before-change score in step (b).

For example, as an example of the normal-display value, the modified normal score may be calculated by recalculating the secondary change value in the candidate cycle number using the post-change signal value in the candidate cycle number, and using the secondary change value Can be further provided by recalculating the normal score at the candidate cycle number.

The normal-display value after the change in the candidate cycle number is used to determine whether or not the candidate cycle number indicates an abnormal signal by comparing it with the "pre-change display value" in the candidate cycle number.

Step (e): The comparison between the normal-display value after the change and the normal-display value after the change (150)

In this step, the normal-display value after the change in the candidate cycle number (s) is compared with the normal-display value before the change ( 150 ). In particular, when the normal score is used as an example of the normal-indication value, the normal score after the change in the candidate cycle number (s) is compared with the pre-change score.

The term "compare "," compare "or" compare "with respect to two normal-indicating values refers to a process of determining which of two normal-indicating values is greater. Comparisons between two steady-state values shall be made taking into account the sign of the steady-state value, ie positive or negative sign. For example, the normal-indication value "10" is considered to be greater than the normal-indication value "-80 ".

The post-change steady-state value used for comparison is provided further in step (d), whereas the post-change steady-state value is provided in step (b) and is adopted in step (c).

Step (f): Determination of the cycle number (160) indicative of the abnormal signal

In this step, it is determined whether the candidate cycle number (s) represents an abnormal signal based on the comparison result in step (e) ( 160 ).

Specifically, if the normal-display value after the change in the candidate cycle number indicates a normal level higher than the normal-display value before change, it is determined that the candidate cycle number indicates an abnormal signal.

In one implementation, where the larger normal-indication value represents a higher normal value in the cycle number, if the normal-indication value after the change in the candidate cycle number is greater than the pre-change indication value, then the candidate cycle number is an abnormal signal . Typical examples of steady-state values having these characteristics include the normal scores described herein.

In this case, the small normal-indication at a particular cycle number is highly related to the abnormal signal in the cycle number. In other words, the smaller the normal-indication value at a particular cycle number, the more likely the cycle number will represent an abnormal signal. Therefore, if the magnitude of the normal-indication value in the candidate cycle number becomes larger due to the change of the signal value according to the method of the present invention, it can be regarded that the abnormal signal in the candidate cycle number is changed to the normal signal. The number can be determined by the cycle number representing the abnormal signal. On the other hand, if the magnitude of the normal-indication value in the candidate cycle number becomes smaller due to the change of the signal value according to the method of the present invention, it can be seen that the normal signal in the candidate cycle number is rather changed into an abnormal signal. The candidate cycle number can be determined as the cycle number representing the normal signal.

In an alternative embodiment in which the smaller normal-indication value indicates a higher normal degree in the cycle number, if the normal-indication value after the change in the candidate cycle number is less than the pre-change indication value, It is determined to indicate an abnormal signal.

In this case, the small normal-indication value at a particular cycle number is highly related to the normal signal at the cycle number. In other words, the smaller the normal-indication value at a particular cycle number, the less likely that the cycle number will exhibit an abnormal signal. Therefore, when the magnitude of the normal-indication value in the candidate cycle number becomes smaller due to the change of the signal value according to the method of the present invention, it can be regarded that the abnormal signal in the candidate cycle number is changed to the normal signal. The cycle number can be determined by the cycle number representing the abnormal signal. In contrast, if the magnitude of the normal-indication value in the candidate cycle number becomes larger due to the change of the signal value according to the method of the present invention, it can be seen that the normal signal in the candidate cycle number is changed to an abnormal signal rather. The cycle number can be determined by the cycle number representing the normal signal.

As described above, the present invention can distinguish between the cycle number indicating the abnormal signal and the cycle number indicating the normal signal by comparing the normal-display value before the change in the cycle number with the normal-display value after the change.

The method of section I described above can be applied to a plurality of data sets obtained by multiple PCR. For example, if multiple data sets are obtained by multiplex PCR, the method of section I can be applied to each data set to determine the cycle number representing the abnormal signal in each data set, can do. Specifically, in the case of obtaining a plurality of data set by the detection of the different detected temperature from a single amplification reaction according to the technique MuDT1 (WO 2015/147412 Reference) it developed by the inventors, the method of section (I) for each data set To determine a cycle number that represents an abnormal signal in each data set, as well as to correct each data set.

In addition to determining the cycle number representing an abnormal signal, the method of the present invention can be applied to correct for abnormal signals in the data set, i. E. To provide a corrected data set.

In one embodiment, if it is determined in accordance with the method of the present invention that the candidate cycle number is indicative of an abnormal signal, a corrected data set may be provided by changing the signal value at the candidate cycle number to the appropriate signal value.

With regard to the provision of the corrected data set, if the post-change normal-indication value in the candidate cycle number indicates a normal level higher than the pre-change-normal value, the post-change data set is provided as a corrected data set On the other hand, if the normal-display value after the change in the candidate cycle number indicates a normal degree lower than the normal-display value before the change, the change of the signal value in the candidate cycle number is invalidated A pre-change data set may be provided.

As used herein, the term " alteration " refers to simply replacing or replacing a particular value or the like with another value, while the term "correction" refers to replacing or replacing an abnormal value with a normal value. In other words, unlike the change, the correction means that the characteristic of the specific value is improved.

Thus, if the method of the present invention determines that the candidate cycle number is indicative of an abnormal signal, while providing a corrected data set (post-change data set), if it is determined that the candidate cycle number represents a normal signal, Set (data set before change).

Alternatively, the method of the present invention may be designed to provide either a post-change data set and a pre-change data set, or to provide a cycle number indicative of an abnormal signal.

In one implementation, if a calibrated data set (post-change data set) is provided, the calibrated data set includes not only changing the signal value in the candidate cycle number to the appropriate signal value, but also the candidate cycle number May be provided by further modifying the signal values at all subsequent cycle numbers. In this case, the change of the signal value in all the cycle numbers after the cycle number indicating the abnormal signal is the same as the difference in the cycle number in which the difference between the signal value after the change in each cycle number and the signal value before change indicates an abnormal signal . ≪ / RTI >

In one implementation, the invention is designed to display only the cycle number that represents the abnormal signal without displaying the data set after the change.

In another embodiment, the method of the present invention is designed to display only the modified data set without indicating the cycle number representing the abnormal signal.

In another embodiment, the method of the present invention is designed to display a cycle number indicative of an abnormal signal with a pre-change data set or a cycle number indicative of an abnormal signal with an indication such as 'retest' or 'invalid'.

The design of such a method of the present invention can be easily adjusted by those skilled in the art, which should also be construed as being within the scope of the present invention.

As described above, the candidate cycle number selected in step (c) of the method of the present invention may be a plurality of candidate cycle numbers.

In this case, the candidate cycle number is applied sequentially or simultaneously to steps (d) - (f) above.

Specifically, when a plurality of candidate cycle numbers, for example, a first candidate cycle number and a second candidate cycle number are selected in step (c), the signal values in the candidate cycle number are individually changed by a signal changing method, After the change in the candidate cycle number, the normal-display value is compared with the normal-display value before change, and then it is determined whether or not each candidate cycle number indicates an abnormal signal.

According to one embodiment, when a plurality of candidate cycle numbers are selected and after changing a signal value in one candidate cycle and a normal-display value after the change in the one candidate cycle is calculated, the signal in the other candidate cycle The value is the signal value before the change, not the signal value after the change. Alternatively, the post-change signal value in another candidate cycle may be used in place of the pre-change signal value in the other candidate cycle.

According to one embodiment, detection of an abnormal signal in a data set may be performed several times, changing the manner of selecting the candidate cycle number.

II. Detection of abnormal signals in data set by iterative method

The method of the present invention may be repeatedly performed to detect additional abnormal signals. The repetition of steps (a) - (f) allows not only to detect additional abnormal signals but also to provide a more precisely calibrated data set.

In another aspect of the present invention, the present invention provides a method of detecting an abnormal signal in a data set in an iterative manner, further comprising repeating the following steps: (g) after performing step (f) Wherein the modified data set is obtained by modifying the signal value in the cycle number (s) indicating an abnormal signal; (h) performing the steps (a) - (f) using the modified data set instead of the data set of step (a).

The method may also be referred to as "iterative manner", "continuous mode", or "loop manner" in that it repeats steps (a) - (f) to detect additional abnormal signals.

According to this iterative scheme, additional abnormal signals can be detected as follows:

Step (g): Providing a dataset after the change

First, after step (f), a modified data set is provided.

The modified data set is obtained by changing the signal value in the cycle number (s) determined to represent an abnormal signal.

In the step (f), if the normal-display value after the change in the candidate cycle number indicates a normal level higher than the normal-display value before the change, the candidate cycle number is determined to indicate an abnormal signal. In this case, the signal value in the candidate cycle number may be changed to provide a modified data set. Conversely, if the normal-indication value after the change in the candidate cycle number indicates a normal degree lower than the pre-change-normal value, the post-change data set is not provided and the repeat mode is not further progressed.

The modified data set can be obtained by changing the signal value in the cycle number indicating an abnormal signal in the same manner as in step (d).

The repetition of steps (a) - (f) is carried out using the newly provided post-change data set instead of the data set of step (a).

When performing steps (a) - (f), the candidate cycle number may be selected in the same way or in a different manner. For example, in the first implementation of steps (a) - (f), a cycle number having a steady-state value smaller than the threshold value may be selected as the candidate cycle number, and the second In practice, the cycle number having a normal-indication value that is less than the threshold value and is at least the minimum value may be the cycle selected as the candidate cycle number.

In one embodiment, the modified data set is obtained by further modifying the signal value at every cycle number after the cycle number representing the abnormal signal.

The phrase "all cycle numbers after the cycle number representing an abnormal signal" refers to the cycle area from the cycle number to the last cycle number after the cycle immediately preceding the abnormal signal. For example, in the case of a data set consisting of 45 cycle numbers in total, all cycle numbers after the 25th cycle number refer to the area from the 26th cycle number to the 45th cycle number.

In one implementation, a change in the signal value at every cycle number after the cycle number that represents the abnormal signal indicates that the difference between the signal value after the change at each cycle number and the signal value before the change indicates the difference in the cycle number .

For example, assuming that the difference between the pre-change signal value and the post-change signal value in the cycle number indicating the abnormal signal is "10 ", the signal value in each cycle number after the cycle number indicating the abnormal signal is" 10 ". ≪ / RTI >

In another embodiment, the change in the signal value at every cycle number after the cycle number representing the abnormal signal is implemented such that the first order difference at each cycle number does not change. For example, when the signal value at the 10th cycle number is changed, the signal value after the 11th cycle number is changed so that the first difference after the change at the 11th cycle number is the same as the first difference before the change, Is calculated by adding the signal value after the change in the ith cycle number and the first difference before the change in the 11th cycle number. In the same manner, the signal value at the 12th cycle number can be calculated by adding the post-change signal value at the 11th cycle number and the first difference before the change at the 12th cycle number.

In particular, when there are a plurality of cycle numbers indicating an abnormal signal, the signal value in any one of the cycle numbers and the signal value after the cycle number may be changed by changing the signal value in another cycle number And a change in the signal value after the cycle number.

For example, if there are tenth and twenty-seventh cycle numbers representing an abnormal signal, all the signal values at the tenth cycle and thereafter are changed, then all the signal values at the twenty-seventh and thereafter can be changed. In this case, the change of the signal value at the tenth cycle number may also affect the signal value at every cycle number (including the 27th cycle number) after the tenth cycle number. For example, when the signal value at the tenth cycle number is changed from "300" to "100", the signal value at the 27th cycle number is also lowered by the difference of "200". Therefore, the change in the subsequent 27th cycle number should be performed considering the change of the signal value at the 10th cycle number and thereafter. For example, if the signal value at the 27 < th > cycle and thereafter changes, the signal value may be further changed from the value affected by the change of the tenth cycle number.

Step (h): Performing steps (a) - (f)

Next, steps (a) - (f) are repeated using the modified data set instead of the data set of step (a).

The repetition of steps (a) - (f) includes providing a normal-indication value at each cycle number of the post-change data set and selecting the candidate cycle number (s) for the abnormal signal by the steady- , The normal-indication value at the candidate cycle number (s) corresponds to the normal-indication value before the change; Further comprising the step of changing the signal value at the candidate cycle number (s) and further providing a normal-indication value at the candidate cycle number (s) using the modified signal value, The provided normal-indication value corresponds to the normal-indication value after the change; If the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the pre-change-normal value, it is determined that the candidate cycle number (s) indicates an abnormal signal.

If the steady-state value is a normal score, steps (a) - (f) include: calculating a secondary change value at each cycle number of the post-change data set; Calculating a normal score at each cycle number of the post-change data set using the secondary change value; Selecting the candidate cycle number (s) for the abnormal signal by the normal score, wherein the normal score calculated in the candidate cycle number (s) corresponds to a pre-change score; Recalculating a normal score in the candidate cycle number (s) using the modified signal value by modifying the signal value in the candidate cycle number (s) and recalculating the normal score in the candidate cycle number (s) The normal score corresponds to the normal score after the change; Comparing the normal score after the change in the candidate cycle number with the pre-change score; And determining that the candidate cycle number (s) indicates an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the pre-change-normal value .

The repetition of steps (a) - (f) is the same as described in section I , except that a new candidate cycle number is selected using the new post-change data set instead of the pre-change data set.

The repetition of steps (a) - (f) may be terminated if there is no cycle number determined to represent an abnormal signal. For example, if one candidate cycle number is selected and the selected candidate cycle number is determined not to represent an abnormal signal, or if a plurality of candidate cycle numbers are selected and all of the selected candidate cycle numbers do not represent abnormal signals If so, the iteration of steps (a) - (f) may be terminated.

When the iteration is over, all cycle numbers determined during the iteration are finally determined as a cycle number representing an abnormal signal in the original data set.

In the iteration of steps (a) - (f), the steady-state value at every cycle number can be calculated in advance with the steady-state value after the change at the candidate cycle number. That is, if the normal-indication value after the change in the candidate cycle number is calculated in the first implementation of step (d), the normal-indication value at another cycle number calculated in the second implementation of step (d) May be predetermined in the first execution of step (d) with the post-change signal value at every cycle number after the cycle number.

According to the iterative approach, each data set used in the selection of the candidate cycle number during the iteration of steps (a) - (f) may be distinguished using different terms. For example, when steps (a) - (f) are performed twice, each data set used in each iteration includes a "pre-change data set", a "post-change data set", a " Set "or the like.

The "data set after the first change" refers to a data set in which the signal value in the cycle number determined to represent an abnormal signal in the first implementation of steps (a) - (f) has been replaced by its appropriate post-change signal value; The "data set after the second change" is a data set in which the signal value at another cycle number determined to indicate an abnormal signal in the second implementation of steps (a) - (f) Quot;

The method of section II described above can be applied to a plurality of data sets obtained by multiple PCR. For example, if multiple data sets are obtained by multiplex PCR, the method of section II can determine the cycle number representing the abnormal signal in each data set, as well as correct each data set. Specifically, the MuDT1 technique (See WO 2015/147412) when a plurality of the data set by the detection of the different detected temperature from a single amplification reaction obtained according to the method of Section II are each of the data set developed by the present inventors To determine a cycle number that represents an abnormal signal in each data set, as well as to correct each data set.

In addition to determining the cycle number representing an abnormal signal, the method of section II can be applied to correct anomalous signals in the data set, i. E. To provide a corrected data set.

If it is determined in accordance with the method of the present invention that the candidate cycle number is indicative of an abnormal signal, the data set in which the signal value at the candidate cycle number is changed may be provided as a corrected data set (e.g., an amplification curve).

 Once the iteration is over, all the cycle numbers determined during the iteration are finally determined as the cycle number representing the abnormal signal in the original data set.

At the end of the iteration, the data set in which the signal value in the cycle number determined to represent an abnormal signal prior to termination may be ultimately provided as a corrected data set.

The corrected data set can be used for further analysis. For example, the data set can be used to determine the presence / absence of a target analyte.

The methods of Sections I and II can be applied to a particular region, for example, a region of interest within a data set rather than all the cycle numbers in the data set.

In one embodiment, the method of the present invention can be applied only to the cycle number in the baseline region in the data set.

In another embodiment, the method of the present invention can be applied only to the cycle number in the exponent area in the data set.

In another embodiment, the method of the present invention can be applied only to the cycle number in the congestion area in the data set.

In another embodiment, the method of the present invention can be applied only to the cycle number selected by the user. The cycle number to be analyzed may be arbitrarily selected. For example, the cycle number to be analyzed is from the third cycle number to the last cycle number, from the fifth cycle number to the last cycle number, or from the seventh cycle number to the last cycle number. Alternatively, the cycle number to be analyzed is a mid-range cycle number.

The methods of sections I and II described above can be used in combination with other methods known in the art, such as those disclosed in U.S. Patent No. 8,560,247 and U.S. Patent Application Publication No. 2015/0186598. For example, after comparing the results of any of the methods described above with the results of any conventional method known in the art, a commonly determined cycle number may ultimately be determined as a cycle number representing an abnormal signal.

The steady-state value may include a value obtained by multiplying the above-described normal score as well as two first-order-variance values in two cycle numbers.

In one implementation, a known method of correcting an abnormal signal in a cycle number can be applied to step (d) to change the signal value at the selected cycle number.

III. Detection of abnormal signals in the data set (no selection of candidate cycles)

Detection of an abnormal signal is performed without selecting a candidate cycle.

In another aspect of the present invention, the present invention provides a method of detecting an abnormal signal in a data set, comprising the steps of:

(a) obtaining a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;

(b) performing the following steps (b-1) to (b-4) on all the cycle numbers in the data set;

providing a normality-representing value in the cycle number using the (b-1) signal value, wherein the steady-state value is a value representing a normal degree of signal value in the cycle number;

(b-2) modifying the signal value in the cycle number and further providing a normal-indication value, wherein the normal-indication value further provided in the cycle number corresponds to the post-alteration normal-indication value;

(b-3) comparing the normal-display value after the change in the cycle number with the normal-display value before the change; And

(b-4) determining that the cycle number indicates an abnormal signal if the normal-display value after the change in the candidate cycle number is larger than the normal-display value before the change.

Unlike the methods of Sections I and II, the method of Section III is characterized by sequential analysis of all cycle numbers instead of analyzing the selected candidate cycle number.

The method of section III is not limited to the sequence of analysis of the cycle number as long as all cycle numbers are analyzed at least once. That is, all the cycle numbers in the data set can be applied to the method of section III , for example, sequentially, randomly, or in a regular manner.

In one embodiment, the data set obtained in step (a) may be a data set except for a cycle region in which the unusual signal is less likely to occur. For example, the data set in step (a) includes the first cycle number to the tenth cycle number, the first cycle number to the ninth cycle number, the first cycle number to the eighth cycle number, the first cycle number to the seventh Cycle number, first cycle number to sixth cycle number, first cycle number to fifth cycle number, first cycle number to fourth cycle number, first cycle number to third cycle number, second cycle number to first cycle number, A cycle number, or a cycle set of a first cycle number.

The method of section III is similar to that of sections I and II , so that the common content between them is omitted in order to avoid the excessive complexity of the present specification by the repetitive description.

IV. Recording medium for signal extraction, computer program and apparatus

Since the recording medium, the apparatus and the computer program of the present invention described below are for carrying out the method of the present invention on a computer, the common description therebetween omits the description in order to avoid the excessive complexity of the present specification by the repetitive description.

In another aspect of the present invention, the present invention provides a computer-readable recording medium comprising instructions for implementing a processor to perform a method of detecting an abnormal signal in a data set comprising the steps of:

(a) receiving a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;

(b) providing a normality-representing value in each cycle number of the data set using the signal value, wherein the normal-indication value is a value indicating a normal degree of the signal value in the cycle number ;

(c) selecting a candidate cycle number (s) for an abnormal signal by the normal-indication value, wherein the normal-indication value in the candidate cycle number (s) Value;

(d) modifying the signal value in the candidate cycle number (s) and further providing a normal-indication value in the candidate cycle number (s) using the modified signal value, wherein the candidate cycle number (S) further provided corresponds to the normal-indicating value after the change;

(e) comparing the normal-display value after the change in the candidate cycle number (s) with the normal-display value before the change; And

(f) determining that the candidate cycle number (s) represents an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.

According to another aspect of the present invention, the present invention provides a computer-readable recording medium comprising instructions for implementing a processor for performing a method of detecting an abnormal signal in a data set comprising the steps of:

(a) obtaining a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;

(b) performing the following steps (b-1) to (b-4) for the entire cycle number in the data set;

providing a normality-representing value in the cycle number using the (b-1) signal value, wherein the steady-state value is a value representing a normal degree of signal value in the cycle number;

(b-2) modifying the signal value in the cycle number and further providing a normal-indication value, wherein the normal-indication value further provided in the cycle number corresponds to the post-alteration normal-indication value;

(b-3) comparing the normal-display value after the change in the cycle number with the normal-display value before the change; And

(b-4) determining that the cycle number indicates an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.

According to another aspect of the present invention there is provided a computer program stored on a computer readable recording medium embodying a processor for executing a method of detecting an abnormal signal in a data set comprising the steps of:

(a) receiving a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;

(b) providing a normality-representing value in each cycle number of the data set using the signal value, wherein the normal-indication value is a value indicating a normal degree of the signal value in the cycle number ;

(c) selecting a candidate cycle number (s) for an abnormal signal by the normal-indication value, wherein the normal-indication value in the candidate cycle number (s) Value;

(d) modifying the signal value in the candidate cycle number (s) and further providing a normal-indication value in the candidate cycle number (s) using the modified signal value, wherein the candidate cycle number (S) further provided corresponds to the normal-indicating value after the change;

(e) comparing the normal-display value after the change in the candidate cycle number (s) with the normal-display value before the change; And

(f) determining that the candidate cycle number (s) represents an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.

According to another aspect of the present invention there is provided a computer program stored on a computer readable recording medium embodying a processor for executing a method of detecting an abnormal signal in a data set comprising the steps of:

(a) obtaining a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;

(b) performing the following steps (b-1) to (b-4) for the entire cycle number in the data set;

providing a normality-representing value in the cycle number using the (b-1) signal value, wherein the steady-state value is a value representing a normal degree of signal value in the cycle number;

(b-2) modifying the signal value in the cycle number and further providing a normal-indication value, wherein the normal-indication value further provided in the cycle number corresponds to the post-alteration normal-indication value;

(b-3) comparing the normal-display value after the change in the cycle number with the normal-display value before the change; And

(b-4) determining that the cycle number indicates an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.

Program instructions, when executed by a processor, cause the processor to perform the method of the invention described above. Program instructions for implementing the method of the present invention may include the following instructions: (i) an instruction to calculate a secondary change value at each cycle number in the data set; (ii) an instruction to calculate a steady-state value at each cycle number using a second-order change value; (iii) an instruction to select the candidate cycle number (s) for the abnormal signal by the normal-indication value; (iv) an instruction to change the signal value in the candidate cycle number (s) and recalculate the normal-indication value in the candidate cycle number (s) using the modified signal value; (v) an instruction to compare the normal-indication value after the change in the candidate cycle number (s) with the normal-indication value before the change; And (vi) determining whether the candidate cycle number (s) represents an abnormal signal.

The method of the present invention is implemented in a processor, which may be a stand alone computer, a network attached computer, or a processor in a data acquisition device such as a real-time PCR device.

Types of computer-readable recording media include but are not limited to CD-R, CD-ROM, DVD, flash memory, floppy disk, hard drive, portable HDD, USB, magnetic tape, MINIDISC, non- volatile memory card, EEPROM, , A RAM, a ROM, a system memory, and a Web server.

The signal value from the signal generation process can be received through several mechanisms. For example, the signal value may be collected by the processor in the PCR data acquisition device. The signal value may be provided to the processor in real time as the signal value is collected, or the signal value may be stored in a memory unit or buffer and provided to the processor after completion of the experiment. Similarly, the signal value may be provided to a separate system, such as a desktop computer system, by a network connection (e.g., LAN, VPN, Internet and intranet) with the collecting device or by a direct connection (e.g., USB or other direct- Or it may be provided on a portable medium such as a CD, a DVD, a floppy disk, and a portable HDD. Similarly, the signal value may be provided to the server system via a network connection (e.g., LAN, VPN, Internet, intranet and wireless communication network) to a client, such as a notebook or desktop computer system.

Instructions implementing the processor implementing the invention may be included in the logic system. The instructions may be provided in any software recording medium such as a portable HDD, USB, floppy disk, CD and DVD, but may be downloadable and may be stored in a memory module (e.g., a hard drive or other memory such as local or attached RAM or ROM) ). ≪ / RTI > Computer code for implementing the invention can be implemented in a variety of coding languages such as C, C ++, Java, Visual Basic, VBScript, JavaScript, Perl, and XML. In addition, various languages and protocols may be used for external and internal storage and delivery of signals and instructions in accordance with the present invention.

In a further aspect of the present invention, the present invention provides an apparatus for detecting abnormal signals in a data set, comprising: (a) a computer processor; and (b) a computer readable recording medium as described above coupled to the computer processor to provide.

According to one embodiment, the apparatus further comprises a reaction vessel capable of receiving the sample and signal generating means, a temperature adjusting means for adjusting the temperature of the reaction vessel, and / or a detector for detecting the signal in the cycle number.

A computer processor may be constructed such that one processor performs all of the above-described performance. Alternatively, the processor unit may be configured to allow multiple processors to perform their respective performance.

According to one embodiment, the processor may be implemented by installing the software in a conventional device (e. G., Real-time PCR device) for detection of the target nucleic acid sequence.

The signal value can be received in an amplification curve in a variety of ways. For example, the signal value can be received and collected by the processor in the data collector of the real-time PCR device. Upon acquisition of the signal values, they may be provided to the processor in a real-time manner, stored in memory units or buffers, and then provided to the processor after the experiment.

Similarly, signal values may be transmitted over a network connection (e.g., LAN, VPN, intranet and Internet) or through a direct connection (e.g., USB and wired or wireless direct connection) From a real-time PCR device to a computer system, such as a desktop computer system. Alternatively, the signal value may be provided to the server system via a network connection (e.g., LAN, VPN, intranet, Internet and wireless communication network) connected to a client, such as a notebook or desktop computer system.

As described above, the method of the present invention may be implemented by an application (i.e., a program) installed by a provider in the computer system or directly installed by a user, and recorded on a computer-readable recording medium.

A computer program embodying the method of the present invention may implement all functions for detecting abnormal signals. The computer program may be a program containing program instructions stored on a computer-readable recording medium embodying a processor for carrying out the method of the present invention.

The computer program can be coded using a suitable computer language such as C, C ++, JAVA, Visual basic, VBScript, JavaScript, Perl, XML and machine language. The program may include function codes for the mathematical functions described above and control codes for implementing the processors in order by a processor of the computer system.

The code may further include a memory reference code in which additional information or media needed by the processor to implement the described functionality is referenced at the location (address) of the internal or external memory of the computer system.

When a computer system needs to communicate with another remote computer or server to implement the functionality of the processor, the code may be used by a processor to communicate with a remote or other computer using a communication module (e.g., a wired and / And may further include communication related codes that code how to communicate with other computers or servers or what information or media is to be transmitted.

The functional program and code (code segment) for implementing the present invention can be easily deduced or modified by a programmer of the art in view of the system environment of the computer that reads the recording medium and executes the program.

Recording media that are networked to a computer system may be distributed and the computer-readable code may be stored and executed in a distributed manner. In this case, at least one of the plurality of distributed computers may implement some of the functions, and may implement some of the functions and transmit the results of the implementation to at least one computer capable of transferring the results of the implementation to the at least one computer.

A recording medium on which an application (i.e., program) is recorded for carrying out the present invention is a recording medium (e.g., a hard disk) included in an application store or an application provider server, an application provider server itself, Other computers are included.

The computer system capable of reading the recording medium may include any computing device, such as a general PC, such as a desktop or notebook computer, a smart phone, a tablet PC, a PDA (personal digital assistant) .

The features and advantages of the present invention are summarized as follows:

(a) The method of the present invention may use a steady-state value to accurately determine a cycle number that represents an abnormal signal in the data set, or even a plurality of abnormal signals. As such, the method of the present invention provides information about correction or invalidation of a data set by indicating whether a cycle representing an abnormal signal exists in the data set and which cycle number represents an abnormal signal.

(b) The method of the present invention can provide a corrected data set in which an abnormal signal in the cycle number is replaced with a normal signal value if the candidate cycle number is determined to represent an abnormal signal. The corrected set of data can be used to provide qualitative and / or quantitative information about the target analyte as a new set of data for the target analyte (in particular, the target nucleic acid sequence).

(c) The method of the present invention can accomplish both the determination of a cycle exhibiting an abnormal signal and the correction of an abnormal signal in a simple and time-efficient manner.

(d) In addition, the use of the data set corrected by the method of the present invention can significantly reduce the false positive or false negative results for the target analyte.

1 is a flow diagram illustrating a process for determining a cycle representing an abnormal signal in a data set according to an exemplary embodiment of the present invention.
Fig. 2 shows an exemplary data set (pre-change data set) used in the analysis of Example 1. Fig.
3 is a graph showing a normal score (NS) calculated at each cycle number of the data set of FIG.
Figure 4 shows an example of a signal change scheme of the present invention for changing the signal value in the candidate cycle for the data set of Figure 2; According to the signal change method, the signal value ( _before y _change (10)) in the 10th cycle number is replaced with the _post-change signal value (10 _after y _change ) as the candidate cycle number, The signal value at every cycle number is also replaced by the respective after-change signal value.
5 shows the pre-change data set (corresponding to the data set of FIG. 2; dotted line); And the signal value in the candidate cycle number (tenth cycle number) in the pre-change data set and all the cycle numbers after the candidate cycle number (the 11th cycle number to the 45th cycle number) according to an embodiment of the present invention And a data set (solid line) after the first-order change in which the signal value is replaced with each appropriate post-change value.
FIG. 6 is a graph showing the normal scores calculated at each cycle number of the first-order modified date set (indicated by the solid line in FIG. 5).
FIG. 7 shows a data set after the primary change (dotted line); And a signal value in another candidate cycle number (11th cycle number) in the data set after the primary change according to one embodiment of the present invention and all the cycle numbers after the candidate cycle number Number) is replaced with each appropriate after-change signal value (solid line).
8 is a graph showing the normal scores calculated in each cycle number of the post-secondary change data set (indicated by solid lines in FIG. 7).
FIG. 9 shows a data set after the secondary change (dotted line); And a signal value at another candidate cycle number (the 23rd cycle number) in the data set after the secondary change according to an embodiment of the present invention and all the cycle numbers after the candidate cycle number Number) is replaced with each appropriate after-change signal value (solid line).
10 is a graph showing the normal scores calculated in each cycle number of the data set after the third-order change (indicated by the solid line in FIG. 9).
11 shows the pre-change data set (dotted line) of Fig. 2; And a corrected data set (second-order modified data set, solid line) finally provided according to one embodiment of the method of the present invention.

Hereinafter, the present invention will be described in more detail with reference to Examples. It is to be understood that the scope of the present invention is not limited by these examples in accordance with the gist of the present invention, and it is to be understood by those skilled in the art that the present invention is not limited thereto It will be obvious.

Example

Example  1: Detection of abnormal signal

In accordance with one embodiment of the present invention, it was determined whether an abnormal signal could be detected in the data set obtained from the real-time PCR reaction.

<1-1> Real time PCR  Acquisition of Data Set by Reaction

Of the data sets obtained by real-time PCR reactions on the analytes, a data set suspected of having abnormal signals by visual inspection was selected for application of one embodiment of the present invention. The real-time PCR reaction was performed in a 45-amplification cycle using a TaqMan probe as a signal-generating means in a CFX96 (TM) Real-Time PCR Detection System (Bio-Rad Laboratories).

The selected data set (amplification curve) and the signal value (RFU) at each cycle number are shown in FIG. 2 and Table 1, respectively.

X One 2 3 4 5 6 7 8 9 10 RFU 8776.39 8762.88 8768.55 8768.85 8778.93 8789.20 8801.55 8790.66 8787.79 8916.60 X 11 12 13 14 15 16 17 18 19 20 RFU 8891.73 8897.98 8895.84 8897.33 8910.11 8923.05 8950.22 8992.13 9066.27 9175.60 X 21 22 23 24 25 26 27 28 29 30 RFU 9316.99 9485.84 9666.92 9827.49 9961.62 10053.62 10124.35 10162.62 10192.80 10209.73 X 31 32 33 34 35 36 37 38 39 40 RFU 10230.79 10253.57 10265.73 10278.29 10284.25 10295.40 10294.58 10288.54 10286.77 10283.82 X 41 42 43 44 45 - - - - - RFU 10286.75 10288.49 10295.78 10289.51 10300.51 - - - - -

<1-2> Calculation of second difference in each cycle number

For this data set, a first order difference in each cycle number was calculated by subtracting the signal value in two immediately adjacent cycle numbers. The second order difference in each cycle number was then calculated by subtracting the first difference in two immediately adjacent cycle numbers. The calculation of the first difference and the second difference was performed by a backward difference method.

Specifically, the second difference in each cycle number was calculated by using the following equations ( IV) and ( V ) sequentially, or by using the following equation ( VI ) alone.

Equation IV

D '(x) = y (x) - y (x-1)

Equation V

D "(x) = D '(x) - D' (x-1)

Equation VI

D "(x) = y (x) - 2 * y (x-1) + y (x-

(X) represents the first difference in the xth cycle number, D "(x) represents the second difference in the xth cycle number, y (x) Y (x-1) is the signal value at the x-1 th cycle number, and y (x-2) is the signal value at the x-2 th cycle number.

<1-3> Calculation of normal score (NS) in each cycle number

Then, the normality score (NS) in each cycle number was calculated by multiplying the second difference in two immediately adjacent cycle numbers according to the following formula ( VII ). The normal score was used as one example of the normal-indication value.

Equation VII

NS (x) = D "(x) * D" (x + 1)

(X + 1) represents the second-order difference in the x-th cycle, and D "(x + 1) Lt; / RTI &gt;

The calculated NS in each cycle number is schematically shown in FIG. 3 and Table 2. FIG.

X One 2 3 4 5 6 7 8 9 10 NS - - -102.90 -52.50 1.75 0.37 -48.65 -186.50 1056.35 -20235.34 X 11 12 13 14 15 16 17 18 19 20 NS -4782.73 -261.09 -30.48 41.00 1.87 2.36 209.66 475.09 1134.40 1128.29 X 21 22 23 24 25 26 27 28 29 30 NS 880.30 335.69 -250.71 542.08 1113.66 896.35 690.30 262.68 107.27 -54.72 X 31 32 33 34 35 36 37 38 39 40 NS 7.12 -18.31 -4.19 -2.60 -34.23 -62.05 62.44 -22.27 -5.04 -6.95 X 41 42 43 44 45 - - - - - NS -7.00 -6.60 -75.19 -234.17 - - - - - -

<1-4> Providing NS before selecting and changing candidate cycles

Based on the NS calculated in Example <1-3> (see FIG. 3 and Table 2), the cycle number with the minimum NS was selected as the candidate cycle number. As a result, the tenth cycle number (NS = -20235.34; signal value: 8916.60) was selected as the candidate cycle number.

Also, NS "-20235.34" in the candidate cycle number was adopted as NS before the change, and this was provided for comparison in Example < 1-6 >.

<1-5> Providing the NS after changing or changing the signal value in the candidate cycle number

The signal value in the candidate cycle number, i.e., the tenth cycle number, is changed according to the predetermined signal value changing method using the following equations ( IX) and ( X ).

Specifically, the first difference before the change in the candidate cycle number (the first difference calculated using the pre-change signal value) and the NS before the change in the candidate cycle number are applied to the following formula IX , To obtain a tertiary amine.

Equation IX

Wherein R, D _{'after the change} (c) denotes the first change value after a change in the candidate cycle number, D' _non-modified (c) denotes a first change value before change in the candidate cycle number, _NS-modified (c) represents the pre-change score in the candidate cycle number; k is a number of 1 or more; and c represents the candidate cycle number.

In the present embodiment, a first-order difference is used as one of the first-order change values.

In the present embodiment, the candidate cycle number was the tenth cycle number, and the first difference _{before change} (D ' _{before change} (10)) in the candidate cycle number was 128.81, _{Before change} (10)) was -20235.34.

To, by using the _non-modified (10) and _NS-modified 10 formula IX (the equation, K = 1) 1 primary differential (D after the change of the candidate cycle number by 'and as D _{change after} 10 ) Were calculated:

Thereafter, a signal value before change in the cycle number immediately before the candidate cycle number and a first difference after the change in the candidate cycle number are applied to the following equation ( X ) to obtain a signal value after the change in the candidate cycle number.

Equation X

y _{After change} (c) = _Before y _change (c-1) + _{After changing} D '(c)

(C) _{After the} above formula, y represents the _change after the change in the candidate signal cycle number value, _y-modified (c-1) indicates a non-modified signal value in the (candidate cycle number -1), D _{'change and then} (c) shows a first variation of the value after the change in, the prospective cycle number calculated by the following equation IX.

In the present embodiment, a first-order difference is used as one of the first-order change values.

The signal value after the change in the 10th cycle number can be calculated as follows: y _{after the change} (10) = y _{before the change} (9) + D ' _{after the change} (10).

In this embodiment, the ninth change of the cycle number before the signal values _(y-modified 9) was 8797.79, _{after the} first difference (D _'change of the modified from the 10th cycle number calculated by the formula IX (10)) was 0.90, so (10) = 8797.79 + 0.90 = 8788.69 _{after the} y _change .

Based on the calculation result, the signal value ( _before y _change (10)) "8916.60" in the 10th cycle number was _{changed to} "8788.69" after changing the signal value (10 _after y change).

Then, the NS in the candidate cycle number was recalculated using the changed signal value. The recalculated NS in the candidate cycle number was "-97.10 ". The NS "-97.10" in the candidate cycle number was changed to NS and was provided for comparison in Example < 1-6 >.

<1-6> Determination of abnormal signal

According to an embodiment of the present invention, when the NS after the change in the candidate cycle number is compared with the NS before the change, and the NS after the change in the candidate cycle number is larger than the NS before the change, the candidate cycle number indicates an abnormal signal .

In the present embodiment, NS "-97.10" after the change in the candidate cycle number (tenth cycle number) was larger than NS "-20235" before the change.

Therefore, it is determined that the tenth cycle number is a cycle number indicating an abnormal signal.

Example  2: In an implementation example  Detection of additional abnormal signals due to (1)

We investigated whether abnormal signals could detect additional abnormal signals using data sets that were changed to normal signals. To this end, a data set after the primary change in which the signal value in the cycle number representing the abnormal signal is changed is prepared, and the data set of the embodiment <1-1> to <1-6 .

<2-1> Primary after change  Providing Data Sets

To further identify the cycle number representing the abnormal signal, the modified data set was used in place of the data set of the embodiment <1-1>.

The modified data set was obtained as follows:

First Embodiment <1-6> on the signal value at the 10 th cycle is determined that an abnormal signal indicating the number (y _{before change} 10: "8916.60") the signal values (y _{after the change} after the change (10): " 8788.69 ") (see FIG. 4).

Then, the signal values at all the cycle numbers after the candidate cycle number were further changed (refer to FIG. 4). In this case, the signal value in the cycle number after the candidate cycle number is changed so that the difference between the pre-change signal value and the post-change signal value in each cycle number is the same as the difference in the candidate cycle number. Specifically, the first difference (D ' _{before change} 11) _before the change in the eleventh cycle number and the after-change signal value (y _{after the change} 10) in the tenth cycle number are added to calculate the difference After the change, the signal value was calculated. In this way, the signal values from the 12th cycle number to the last cycle number were changed.

The generated data set was named "data set after first-order change"

X One 2 3 4 5 6 7 8 9 10 RFU 8776.39 8762.88 8768.55 8768.85 8778.93 8789.20 8801.55 8790.66 8787.79 8788.69 X 11 12 13 14 15 16 17 18 19 20 RFU 8763.82 8770.07 8767.93 8769.42 8782.20 8795.15 8822.31 8864.22 8938.36 9047.70 X 21 22 23 24 25 26 27 28 29 30 RFU 9189.09 9357.94 9539.01 9699.58 9833.72 9925.71 9996.44 10034.72 10064.90 10081.82 X 31 32 33 34 35 36 37 38 39 40 RFU 10102.88 10125.66 10137.83 10150.39 10156.35 10167.49 10166.67 10160.64 10158.87 10155.91 X 41 42 43 44 45 - - - - - RFU 10158.85 10160.59 10167.87 10161.60 10172.61 - - - - -

FIG. 5 shows a data set (solid line) after the 1st-order change and a data set before the change of the signal value (the data set before the change of the example <1-1>: dotted line).

<2-2> Calculation of second difference in each cycle number

For the data set after the first-order change, the second-order difference in each cycle number was calculated as in Example <1-2>.

<2-3> Calculation of normal score (NS) in each cycle number

The NS in each cycle number was calculated by multiplying the second difference in two immediately adjacent cycle numbers as in Example < 1-3 >.

The recalculated NS at each cycle number is shown in FIG.

X One 2 3 4 5 6 7 8 9 10 NS - - -102.90 -52.50 1.75 0.37 -48.65 -186.50 30.23 -97.10 X 11 12 13 14 15 16 17 18 19 20 NS -802.05 -261.09 -30.48 41.00 1.87 2.36 209.66 475.09 1134.40 1128.29 X 21 22 23 24 25 26 27 28 29 30 NS 880.30 335.69 -250.71 542.08 1113.66 896.35 690.30 262.68 107.27 -54.72 X 31 32 33 34 35 36 37 38 39 40 NS 7.12 -18.31 -4.19 -2.60 -34.23 -62.05 62.44 -22.27 -5.04 -6.95 X 41 42 43 44 45 - - - - - NS -7.00 -6.60 -75.19 -234.17 - - - - - -

<2-4> Selection of the candidate cycle number and Before change  Providing NS

Based on the recalculated NS in Example < 2-3 > (see FIG. 6 and Table 4), the cycle number having the minimum NS was selected as the candidate cycle number. As a result, the eleventh cycle number (NS = -802.05; signal value = 8763.82) was selected as the candidate cycle number.

Also, NS "-802.05" in the candidate cycle number was adopted as the NS prior to change, and this was provided for comparison in Example < 2-6 >.

<2-5> Change of the signal value in the candidate cycle number and after change  Providing NS

The signal value in the candidate cycle number, that is, the eleventh cycle number, is changed according to the previously set signal change method as in the embodiment <1-5>.

As a result, the signal value after the change in the 11th cycle number was calculated as follows: (11) = 8788.69 + 0.85 = 8789.54 _{after the} y _change .

(11)) "8763.82 " in the 11th cycle is _changed to the post-change signal value (11 _{after the change} y)" 8789.54 "

Then, the NS in the candidate cycle number was recalculated using the changed signal value. The recalculated NS in the candidate cycle number was "-0.27 ". The NS "-0.27" in the candidate cycle number was changed to NS and was provided for comparison in Example < 2-6 >.

<2-6> Determination of abnormal signal

According to an embodiment of the present invention, the NS after the change in the candidate cycle number is compared with the NS before the change in the candidate cycle number.

In the present embodiment, NS "-0.27" after the change in the candidate cycle number (eleventh cycle number) was larger than NS "-802.05" before the change.

Therefore, the 11th cycle number is determined as a cycle number indicating an abnormal signal.

Example  3: In an implementation example  Detection of additional abnormal signals due to (II)

We investigated whether abnormal signals could detect additional abnormal signals using data sets that were changed to normal signals. To this end, a data set after the secondary change in which the signal value in the cycle number representing the abnormal signal is changed is prepared, and it is compared with the data set of the embodiment <1-1> .

<3-1> Secondary after change  Providing Data Sets

In order to further confirm the cycle number indicating an abnormal signal, the data set after the second-order change was used in place of the data set of the embodiment <1-1>.

The secondary modified data set was obtained as follows:

First, for the data set after the first-order change, the signal value ( _before y _change (11)) "8763.82 &quot; in the 11th cycle number determined to exhibit an abnormal signal in the embodiment <2-6> (11) (8789.54 _{after changing} y).

Then, the signal values at all the cycle numbers after the candidate cycle number were further changed. In this case, the signal value in the cycle number after the candidate cycle number is changed so that the difference between the signal value before change and the signal value after change in each cycle number is the same as the difference in the candidate cycle number.

The generated data set was named "data set after the second change" and it is shown in Table 5.

X One 2 3 4 5 6 7 8 9 10 RFU 8776.39 8762.88 8768.55 8768.85 8778.93 8789.20 8801.55 8790.66 8787.79 8788.69 X 11 12 13 14 15 16 17 18 19 20 RFU 8789.54 8795.79 8793.65 8795.14 8807.92 8820.87 8848.04 8889.94 8964.08 9073.42 X 21 22 23 24 25 26 27 28 29 30 RFU 9214.81 9383.66 9564.73 9725.30 9859.44 9951.43 10022.16 10060.44 10090.62 10107.54 X 31 32 33 34 35 36 37 38 39 40 RFU 10128.60 10151.38 10163.55 10176.11 10182.07 10193.21 10192.39 10186.36 10184.59 10181.64 X 41 42 43 44 45 - - - - - RFU 10184.57 10186.31 10193.59 10187.32 10198.33 - - - - -

The data set after the secondary change (solid line) and the primary change data set (dotted line) are shown in Fig.

<3-2> Calculation of second difference in each cycle number

For the data set after the secondary change, the secondary difference in each cycle number was calculated as in Example <1-2>.

<3-3> Calculation of normal score (NS) in each cycle number

The NS in each cycle number was calculated by multiplying the second difference in two immediately adjacent cycle numbers as in Example < 1-3 >.

The recalculated NS at each cycle number is shown in FIG. 8 and Table 6.

X One 2 3 4 5 6 7 8 9 10 NS - - -102.90 -52.50 1.75 0.37 -48.65 -186.50 30.23 -0.19 X 11 12 13 14 15 16 17 18 19 20 NS -0.27 -45.32 -30.48 41.00 1.87 2.36 209.66 475.09 1134.40 1128.29 X 21 22 23 24 25 26 27 28 29 30 NS 880.30 335.69 -250.71 542.08 1113.66 896.35 690.30 262.68 107.27 -54.72 X 31 32 33 34 35 36 37 38 39 40 NS 7.12 -18.31 -4.19 -2.60 -34.23 -62.05 62.44 -22.27 -5.04 -6.95 X 41 42 43 44 45 - - - - - NS -7.00 -6.60 -75.19 -234.17 - - - - - -

<3-4> Selection of candidate cycle number and provision of NS before change

Based on the NS recalculated in Example <3-3> (see FIG. 8 and Table 6), the cycle number with the minimum NS was selected as the candidate cycle number. As a result, the 23rd cycle number (NS = -250.71; signal value = 9564.74) was selected as the candidate cycle number.

Also, NS "-250.71" in the candidate cycle number was adopted as NS before the change, and this was provided for comparison in Example < 3-6 >.

<3-5> Providing NS after changing or changing the signal value in the candidate cycle number

The signal value in the candidate cycle number, that is, the 23rd cycle number, is changed according to a predetermined signal change method as in the embodiment <1-5>.

As a result, after a change in the 23 th cycle number signal value was calculated as follows: y _{change after} 23 + 10.6 = 9383.66 = 9394.42

Based on the calculation result, the signal value at the 23rd cycle (y _{before change} 11) after the change to "9564.74" was changed to a signal value (y _{change after} 11) "9394.42".

Then, the NS in the candidate cycle number was recalculated using the changed signal value. The recalculated NS in the candidate cycle number was "-23682.71 ". NS "-23682.71" in the candidate cycle number was changed to NS, which was provided for comparison in Example < 3-6 >.

<3-6> Determination of abnormal signal

According to an embodiment of the present invention, the NS after the change in the candidate cycle number is compared with the NS before the change in the candidate cycle number.

In the present embodiment, NS "-23682.71" after the change in the candidate cycle number (23rd cycle number) was smaller than NS "-250.71" before the change.

Therefore, the 23rd cycle number is determined as a cycle number representing a normal signal.

According to an embodiment of the invention, for each data set, if the NS after the change in the candidate cycle is less than the NS before change, the method of the present invention can be terminated. In this embodiment, since the NS after the change in the candidate cycle number of the third embodiment is smaller than the NS before the change, the cycle number indicating an abnormal signal is no longer determined.

According to Examples 1 to 3, the tenth cycle number and the eleventh cycle number were finally determined to be cycle numbers indicating abnormal signals.

In addition, the data set in which the signal values in the 10th and 11th cycle numbers are replaced with the signal value after each proper change (the data set after the secondary change) was finally provided as the corrected data set. The final provided corrected data set is shown in FIG. In the figure, the dotted line indicates the data set before correction (the data set before modification), and the solid line indicates the finally corrected data set (the data set after the secondary modification).

As shown in FIG. 11, it has been found that the cycle number indicating an abnormal signal can be accurately corrected by the method of the present invention. Thus, using the method of the present invention, it is possible not only to determine the cycle number representing the abnormal signal in the data set, but also to correct the data set including the abnormal signal (s).

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the present invention. It is therefore intended that the scope of the invention be defined by the claims appended hereto and their equivalents.

Claims (22)

CLAIMS What is claimed is: 1. A method for detecting an abnormal signal in a data set, comprising:
(a) obtaining a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;
(b) providing a normality-representing value in each cycle number of the data set using the signal value, wherein the normal-indication value is a value indicating a normal degree of the signal value in the cycle number ;
(c) selecting a candidate cycle number (s) for an abnormal signal by the normal-indication value, wherein the normal-indication value in the candidate cycle number (s) Value;
(d) modifying the signal value in the candidate cycle number (s) and further providing a normal-indication value in the candidate cycle number (s) using the modified signal value, wherein the candidate cycle number (S) further provided corresponds to the normal-indicating value after the change;
(e) comparing the normal-display value after the change in the candidate cycle number (s) with the normal-display value before the change; And
(f) determining that the candidate cycle number (s) represents an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.
2. The method of claim 1, wherein the steady-state value in each cycle number is provided by calculating a change value in each cycle number from a signal value in 2-5 consecutive cycle numbers including each cycle number &Lt; / RTI &gt;
3. The method of claim 2, wherein the steady-state value comprises: (i) calculating a second change value at each cycle number of the data set; And (ii) computing a normal score at each cycle number of the data set using the secondary change value, wherein the calculation of the normal score is performed in two consecutive cycle numbers And a mathematical operation indicating the magnitude of the sign change and the second-order change value between the second-order change values.
4. The method of claim 3, wherein the calculation of the second change value is performed by calculating a first change value at each cycle number of the data set using two signal values at two consecutive cycle numbers, And calculating a second change value at each cycle number of the data set using the two first-order change values in the number.
4. The method according to claim 3, wherein the secondary change value is any one selected from the group consisting of a second-order differential, a second-order differential, and a second-order differential.
6. The method of claim 5, wherein the second order differential or second order differential is obtained by a forward difference method or a backward difference method.
4. The method of claim 3, wherein the calculation of the normal score is performed by multiplying a second change value in two consecutive cycle numbers.
The method of claim 7, wherein the calculation of the normal score is characterized in that which is performed by the following formula VII or VIII:
Equation VII
NS (x) = D "(x) * D" (x + 1)
(X + 1) represents the second-order change value at the x-th cycle number, and D "(x + Represents a secondary change value in the cycle number, and x is an integer of 1 or more.
Formula VIII
NS (x) = D "(x) * D" (x-1)
(X) represents a normal score at the x-th cycle number, D "(x) represents a secondary change value at the x-th cycle number, and D" Represents a secondary change value in the cycle number, and x is an integer of 2 or more.
2. The method of claim 1, wherein if the larger normal-indication value indicates a higher normality in the cycle number, then the candidate cycle number is: (i) a cycle number having a normal-indication value less than a threshold selected from a value less than zero; (ii) a cycle number having a steady-state value that is less than and less than a threshold selected from a value less than zero; Or (iii) a cycle number having a negative sign and a minimum normal-indication value; If the smaller normal-indication value indicates a higher normal degree of signal value in the cycle number, then the candidate cycle is: (i) a cycle number having a normal-indication value greater than the threshold value selected from a value greater than zero; (ii) a cycle number having a normal-indication value that is greater than and greater than a threshold value selected from a value greater than zero; Or (iii) a positive sign and a normal-indicating value that is a maximum.
2. The method of claim 1, wherein the signal value at the candidate cycle number is modified to decrease its absolute value.
11. The method of claim 10, wherein the signal value in the candidate cycle number is changed such that its absolute value is greater than or equal to a relatively small absolute value of the signal values in two cycle numbers immediately adjacent to the candidate cycle number How to.
4. The method of claim 3, wherein the signal value in the candidate cycle number is selected from the group consisting of (i) a first change value before the change in the candidate cycle number, and a second change value in the candidate cycle number Obtaining a first change value after the change; And (ii) using the first change value after the change in the candidate cycle number to obtain the post-change signal value in the candidate cycle number.
4. The method of claim 3, wherein the signal value at the candidate cycle number is changed to a post-change signal value determined by Equations IX and X:
Equation IX

Wherein R, D _{'after the change} (c) denotes the first change value after a change in the candidate cycle number, D' _non-modified (c) denotes a first change value before change in the candidate cycle number, _NS-modified (c) represents the pre-change score in the candidate cycle number; k is a number of 1 or more; and c represents the candidate cycle number.
Equation X
y _{After change} (c) = _Before y _change (c-1) + _{After changing} D '(c)
(C) _{After the} above formula, y represents the _change after the change in the candidate signal cycle number value, _y-modified (c-1) indicates a non-modified signal value in the (candidate cycle number -1), D _{'change and then} (c) shows a first variation of the value after the change in the candidate cycle number calculated by the following equation IX.
The method of claim 1, wherein when a plurality of candidate cycle numbers are selected in the step (c), the candidate cycle number is sequentially or simultaneously applied to the steps (d) - (f).
The method of claim 1, further comprising repeating the following steps:
(g) providing a modified data set after performing step (f), wherein the modified data set is obtained by changing a signal value in the cycle number (s) representing an abnormal signal; (h) performing the steps (a) - (f) using the modified data set instead of the data set of step (a).
16. The method of claim 15, wherein the modified data set is obtained by further modifying a signal value at every cycle number after the cycle number representing the abnormal signal.
The method as claimed in claim 16, wherein the change of the signal value in all the cycle numbers after the cycle number indicating the abnormal signal indicates that the difference between the post-change signal value and the pre-change signal value in each cycle number is a cycle number indicating an abnormal signal Is equal to the difference between the first and second values.
16. The method of claim 15, wherein the iteration of steps (a) - (f) ends when there is no cycle number determined to represent an abnormal signal.
A method for detecting an abnormal signal in a data set, comprising the steps of:
(a) obtaining a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;
(b) performing the following steps (b-1) to (b-4) on all the cycle numbers in the data set;
providing a normality-representing value in the cycle number using the (b-1) signal value, wherein the steady-state value is a value representing a normal degree of signal value in the cycle number;
(b-2) modifying the signal value in the cycle number and further providing a normal-indication value, wherein the normal-indication value further provided in the cycle number corresponds to the post-alteration normal-indication value;
(b-3) comparing the normal-display value after the change in the cycle number with the normal-display value before the change; And
(b-4) determining that the cycle number indicates an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.
CLAIMS What is claimed is: 1. A computer-readable recording medium comprising instructions for implementing a processor for performing a method of detecting an abnormal signal in a data set comprising:
(a) receiving a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;
(b) providing a normality-representing value in each cycle number of the data set using the signal value, wherein the normal-indication value is a value indicating a normal degree of the signal value in the cycle number ;
(c) selecting a candidate cycle number (s) for an abnormal signal by the normal-indication value, wherein the normal-indication value in the candidate cycle number (s) Value;
(d) modifying the signal value in the candidate cycle number (s) and further providing a normal-indication value in the candidate cycle number (s) using the modified signal value, wherein the candidate cycle number (S) further provided corresponds to the normal-indicating value after the change;
(e) comparing the normal-display value after the change in the candidate cycle number (s) with the normal-display value before the change; And
(f) determining that the candidate cycle number (s) represents an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.
(a) a computer processor; and (b) the computer-readable recording medium of claim 20, coupled to the computer processor, for detecting an abnormal signal in the data set.
What is claimed is: 1. A computer program embodied in a computer-readable recording medium for implementing a processor for performing a method of detecting an abnormal signal in a data set comprising the steps of:
(a) receiving a data set for a target analyte by a signal amplification reaction, the data set comprising a plurality of data points having a cycle number and a signal value in the cycle number;
(b) providing a normality-representing value in each cycle number of the data set using the signal value, wherein the normal-indication value is a value indicating a normal degree of the signal value in the cycle number ;
(c) selecting a candidate cycle number (s) for an abnormal signal by the normal-indication value, wherein the normal-indication value in the candidate cycle number (s) Value;
(d) modifying the signal value in the candidate cycle number (s) and further providing a normal-indication value in the candidate cycle number (s) using the modified signal value, wherein the candidate cycle number (S) further provided corresponds to the normal-indicating value after the change;
(e) comparing the normal-display value after the change in the candidate cycle number (s) with the normal-display value before the change; And
(f) determining that the candidate cycle number (s) represents an abnormal signal if the normal-indication value after the change in the candidate cycle number indicates a normal degree higher than the normal-indication value before the change.

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