KR101717141B1 - Apparatus and method of survival analysis for patients using genetic switch threshold - Google Patents

Abstract

According to an embodiment of the present invention, a method for analyzing survival of a gene comprises the steps of: calculating standard normal distribution on an expression amount of a gene; setting a boundary value in the calculated standard normal distribution; discretely representing an expression state of the gene based on the set boundary value; and using the discretely represented result as an analysis element for a survival analysis model.

Description

[0001] APPARATUS AND METHOD OF SURVIVAL ANALYSIS FOR PATIENTS USING GENETIC SWITCH THRESHOLD [0002]

The present invention relates to statistics on gene expression. More specifically, the present invention relates to a method and apparatus for performing survival analysis so that statistics on gene expression can be used for significant patient survival analysis.

Expression of a gene is a process in which proteins constituting living organisms including human beings are formed into various forms by the diversity of genetic information of DNA. Although accurate prediction of gene expression is not possible, statistical analysis has been conducted to analyze gene expression.

All control group identification methods in gene expression data (Patent Publication No. 10-2012-0077594 (Jul. 10, 2012))

The technical problem to be solved by the present invention is to produce a result having higher reliability in the survival analysis according to the expression amount of the gene.

According to an embodiment of the present invention, there is provided a survival analysis method according to an expression amount of a gene, comprising: calculating a standard normal distribution of an expression amount of a gene; Setting a boundary value, discretizing the expression of the gene based on the set boundary value, and using the discretized result as an analysis element in a survival analysis model.

Preferably, the step of setting the boundary value sets the median value (z = 0) of the standard normal distribution as the boundary value.

Preferably, the step of setting the boundary value sets any one of the first boundary value zi, the second boundary value zii, and the third boundary value ziii as the boundary value .

Preferably, the step of setting the boundary value further comprises applying the generated discretized result to the survival analysis model using the first boundary value zi to generate a first p-value determining a second p-value (p2) for the survival analysis result by applying the generated discretized results to the survival analysis model using the second boundary value (zii) , Applying the generated discretized results to the survival analysis model using the third boundary value (ziii) to determine a third p-value (p3) for the survival analysis result, determining a p-value (p) having a lowest value among the first p-value, the second p-value, and the third p-value, , Setting a value associated with the determined p-value (p) among the third boundary value (ziii) as the boundary value Can.

Preferably, the step of setting the boundary value further comprises the step of setting the boundary value to a value of one of the first boundary value zi, the second boundary value zii, the third boundary value ziii and the fourth boundary value ziv Wherein when the number of samples indicating the result of the generated discretization is equal to or less than a threshold value by using the four boundary value ziv, (ziv) is excluded.

Preferably, the first boundary value zi is -2 (z = -2), the third boundary value ziii is 2 (z = 2), the second boundary value zii, And the fourth boundary value ziv is a value between -2 and 2.

Preferably, the survival analysis model corresponds to a Cox-proportional hazard model or a log-rank test model.

According to an embodiment of the present invention, there is provided an apparatus for analyzing a survival rate according to an expression amount of a gene, the method comprising: calculating a standard normal distribution of an expression amount of a gene; And discretizes the expression of the gene based on the set boundary value, and uses the result of the discretization as an analysis element in the survival analysis model.

Preferably, the survival analysis apparatus sets a median (z = 0) of the standard normal distribution as the threshold value.

Preferably, the survival analysis apparatus sets any one of the first boundary value zi, the second boundary value zii, and the third boundary value ziii to the boundary value.

Preferably, the survival analysis apparatus applies the generated discretized results to the survival analysis model using the first boundary value zi to obtain a first p-value (p1) for the survival analysis result Determining a second p-value (p2) for the survival analysis result by applying the resulting discretized results to the survival analysis model using the second threshold value zii, Applying the generated discretized results to the survival analysis model to determine a third p-value (p3) for the survival analysis results using the value (ziii), and comparing the first p-value, the second p (p) having the lowest value among the third p-values and determining the first boundary value zi, the second boundary value zii, the third boundary value (p) is set to the value of the boundary value.

Preferably, the survival analysis device is configured to determine any one of the first boundary value zi, the second boundary value zii, the third boundary value ziii, and the fourth boundary value ziv as the boundary The fourth boundary value ziv is set to the survival analysis model when the number of samples showing the generated discretized result is equal to or smaller than the threshold value, Is excluded.

Preferably, the survival analysis apparatus sets the first boundary value zi to -2 (z = -2), sets the third boundary value ziii to 2 (z = 2) And the second boundary value zii and the fourth boundary value ziv are set to values between -2 and 2.

Preferably, the survival analysis model corresponds to a Cox-proportional hazard model or a log-rank test model.

According to an aspect of the present invention, there is provided a computer-readable recording medium having recorded thereon a computer program for performing a method of calculating a standard normal distribution of an expression amount of a gene for a survival analysis according to an expression amount of a gene, Setting a boundary value in the calculated normal normal distribution, discretizing the expression of the gene on the basis of the set boundary value, and using the discretized result as an analysis element in a survival analysis model Is recorded.

Advantageously, the step of setting the threshold value further comprises the step of: setting a threshold value (z = 0) of the standard normal distribution to the threshold value so that a program for performing the setting of the median value have.

Advantageously, the step of setting the boundary value further comprises the step of: setting one of the first boundary value zi, the second boundary value zii and the third boundary value ziii as the boundary value A program may be recorded on the computer readable recording medium.

Preferably, the step of applying the generated discretized results to the survival analysis model using the first boundary value zi to determine a first p-value (p1) for the survival analysis result, Applying the generated discretized results to the survival analysis model using a second boundary value ziii to determine a second p-value p2 for the survival analysis result, Applying the resulting discretized results to the survival analysis model to determine a third p-value (p3) for the survival analysis results, and determining the first p-value, the second p-value, And determining a p-value (p) having a lowest value among the third p-values; and determining the first boundary value zi, the second boundary value zii, the third boundary value ziii, And setting the value associated with the determined p-value (p) to the boundary value, It can be recorded on a recording medium that can be read by.

Preferably, one of the first boundary value zi, the second boundary value zii, the third boundary value ziii, and the fourth boundary value ziv is set as the boundary value, 4 eliminating the application of the fourth boundary value ziv to the survival analysis model when the number of samples indicating the generated discretized result is equal to or less than a threshold value by using the fourth threshold value ziv, May be recorded on a computer-readable recording medium.

Preferably, a program for performing the Cox-proportional hazard model or the log-rank test model as the survival analysis model can be recorded on a computer-readable recording medium.

According to the present invention, the effect of gene expression on the survival of a patient can be more accurately analyzed.

According to the present invention, it is possible to generate a result having higher reliability in genomics research.

FIG. 1 shows a method used for survival analysis according to existing gene expression.
2 is a diagram showing the expression amount of a gene according to SNP (Single Nucleotide Polymorphism).
FIG. 3 is a diagram showing a standard normal distribution table in which a boundary value is newly defined in consideration of the expression amount of a gene according to a genetic mutation.
4 is a diagram showing a standard normal distribution table in which a boundary value is newly set in consideration of the expression amount of a gene according to a genetic mutation.
5 is a flowchart showing a survival analysis method according to the expression level of a gene.
6 is a view showing a survival analysis apparatus according to the expression level of a gene.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings and accompanying drawings, but the present invention is not limited to or limited by the embodiments.

As used herein, terms used in the present invention are selected from general terms that are widely used in the present invention while taking into account the functions of the present invention, but these may vary depending on the intention or custom of a person skilled in the art or the emergence of new technologies. In addition, in certain cases, there may be a term arbitrarily selected by the applicant, in which case the meaning thereof will be described in the description of the corresponding invention. Therefore, it is intended that the terminology used herein should be interpreted based on the meaning of the term rather than on the name of the term, and on the entire contents of the specification.

FIG. 1 shows a method used for survival analysis according to existing gene expression.

The effects of gene expression on the survival of patients in the medical and biotechnological fields are mainly discretized into 0 and 1, based on the median of the gene expression data, and this value is used as a survival analysis model (eg, Cox proportional hazard ratio or log-rank test).

The graph shown in the figure is a standard normal distribution table, and the value of Z is a standard normalized value of the expression amount of a gene that affects the survival of a patient. In a specific patient, when the hazard ratio was greater than 1 as a result of the cox-hazard analysis, when the expression level of a specific gene was higher than Z = 0, the expression of the gene in the survival analysis model was high, When the expression level of a particular gene is lower than Z = 0, the expression of the gene in the survival analysis model is relatively small, and this environment can be considered as a factor in creating a good prognosis for the patient. Conversely, when the hazard ratio was less than 1 in the cox-hazard analysis of a particular patient, when the expression level of a specific gene was higher than Z = 0, the expression of the gene in the survival analysis model was high, , And when the expression level of a specific gene is lower than Z = 0, the expression of the gene in the survival analysis model is relatively small, and this environment can be considered as a factor in making a bad prognosis to the patient have.

2 is a diagram showing the expression amount of a gene according to SNP (Single Nucleotide Polymorphism).

Expression quantitative trait loci (eQTL) The characteristics of the genes that appear in the study show that the border points of the gene expression values can appear at different locations rather than simply at the median value. For example, when a situation such as a genetic mutation occurs, such a situation may affect the expression amount of a specific gene.

When there is a genetic variation (SNP) affecting a particular gene, the amount of gene expression may vary depending on the type of genetic variation (SNP) (AA type, AB or BB type). If eQTL affects patient survival, both the genetic mutation (SNP) and the original gene of this eQTL can be factors affecting patient survival.

In the figure, the number of AA type samples is much larger than the number of samples of AB type or BB type, and the expression amount of genes in the AA type may be lower than the gene expression amount in AB type or BB type samples. In the survival analysis for the genetic variation (SNP), when the survival rate of the patient was abruptly decreased when AB type or BB type, samples in which gene expression levels were relatively large (AB type or BB type samples) .

However, since a large number of samples (AB type or BB type sample) have a relatively small number of samples and a large number of AA type samples having a relatively high survival rate, The affected genes also exhibit these characteristics. Samples with relatively good prognosis have a low expression level and a large number of them are present. Samples with bad prognosis have a high expression level and a small number of characteristics.

This means that the threshold value of the gene expression that actually affects the patient's survival may be higher or lower than the median value.

FIG. 3 is a diagram showing a standard normal distribution table in which a boundary value is newly defined in consideration of the expression amount of a gene according to a genetic mutation.

In the case of the genetic mutation described in FIG. 2, the threshold value for the expression amount of the gene to be considered as a factor affecting the survival of the patient is likely to be located higher than the median value.

In the survival analysis at the median, the p-value (the probability that the test statistic of observed data is significantly different from the predicted value set by the observer) was not significant. , We can see that there is an error in the existing survival analysis method if the p-value is significant when z = 1 is analyzed as the boundary value.

That is, according to one embodiment of the present invention, more accurate survival analysis may be possible when the threshold value is adjusted.

4 is a diagram showing a standard normal distribution table in which a boundary value is newly set in consideration of the expression amount of a gene according to a genetic mutation.

According to an embodiment of the present invention, the survival analysis of the patient according to the expression amount of the gene in consideration of the genetic variation can be performed as follows.

The survival analysis device (or program) discretizes expression data using various gene expression level threshold values. Referring to the drawings, various values between -2 and 2 in the standard normal distribution can be used as boundary values for gene expression.

In order to ensure statistical reliability, when a group (for example, five or less samples) with a small number of samples is present among the discretized groups 0 and 1, It is excluded from the survival analysis.

The survival analysis device independently performs the survival analysis on the extracted data with each threshold value.

The survival analysis device selects a boundary value result that has the best performance among the performed results (eg, the lowest p-value). The survival analysis device can perform discretization for gene expression using selected threshold values.

The survival analysis device can be used by checking that the automatically determined threshold value matches the threshold value shown by the eQTL.

5 is a flowchart showing a survival analysis method according to the expression level of a gene.

According to one embodiment of the present invention, the survival analysis apparatus calculates a standard normal distribution of the expression amount of the gene (s50100).

The survival analysis apparatus sets a boundary value in the calculated standard normal distribution (s50200).

The survival analysis apparatus discretizes the expression of the gene based on the set boundary value (s50300). Here, discretization may be a criterion that considers or does not consider the expression of a particular gene in the survival analysis model. In other words, when the expression of a specific gene in the survival analysis model is used as an analysis element, the process of expressing the expression of the gene as 1 (high expression) or 0 (low expression) can be regarded as a discipline. For example, if the expression level of a specific gene is higher than the set threshold value, the expression of the gene is determined to be high in the survival analysis model. If the expression level of the specific gene is lower than the set threshold value, The expression of the < / RTI > In the process of disassociating gene expression, the criteria for disassociation can vary depending on the analysis of the gene. For example, when the value of z representing the best p-value is set as a boundary value, it can be assumed that the expression of the gene in question is higher than that in the case of expression of the gene over the boundary value, 1, and in the case of expression of a gene that does not meet the boundary value, it can be assumed that the expression of the gene is low and the expression of the gene can be set to zero.

The survival analysis device uses the discretized results as an analysis element in the survival analysis model (s50400).

In this process, the median of the standard normal distribution (z = 0) may be set to the boundary value, or a value other than the median value may be set to the boundary value. When a value other than the median value is set as the boundary value, as described above, the expression amount of the gene is varied according to the genetic mutation in the sample, and it is necessary to adjust the boundary value of the expression amount of the specific gene Is the case.

According to an embodiment of the present invention, the boundary value is adjusted and the experiment is performed a plurality of times, and the boundary value determined in the experiment can be used as a boundary value for the corresponding gene in the survival analysis model. For example, for a given number of samples (for example, 1000), the hypothesis is compared with the result for the actual sample while changing the value of 0.5 from z = -2 to z = 2, Lt; RTI ID = 0.0 > p-value < / RTI > Of these, boundary values with the smallest p-value can be used in the survival analysis model.

6 is a view showing a survival analysis apparatus according to the expression level of a gene.

The survival analysis apparatus 60100 according to an embodiment of the present invention may include a main processor 60140, and / or a threshold value setting processor 60120.

The main processor 60140 calculates a standard normal distribution of the expression amount of the gene. The main processor 60140 discretizes the expression of the gene based on the set boundary value. The main processor 60140 uses the result of the discretization as an analysis element in the survival analysis model.

The threshold value setting processor 60120 may set the threshold value in the calculated standard normal distribution.

The boundary value setting processor 60120 sets one or more virtual boundary values and delivers the values to the main processor 60140. The main processor 60140 uses the received boundary values to perform a survival analysis Can be performed. The main processor 60140 transmits the survival analysis result to the threshold value setting processor 60120. The threshold value setting processor 60120 determines a p-value value corresponding to each virtual threshold value, The low virtual boundary value may be set to a threshold value to be used in the actual survival analysis model and transmitted to the main processor 60140.

When analyzing the effect of gene expression on the clinical prognosis of a patient, gene expression data may be used as the continuous values, or disassociated to 0 or 1 based on the median, to analyze the prognosis Respectively. However, in such cases, different gene switch thresholds (for example, z = 0) may be used depending on the gene, which may lead to actual clinical changes in the patient's body when the expression level of the gene exceeds a certain threshold value. Non-value), the effect of the patient's survival analysis may be limited. According to the present invention, the effect of gene expression on the survival of a patient can be more accurately analyzed through survival analysis considering various gene switch boundary values applicable to the gene.

Genetic-based survival analysis is one of the most important analytical parts of genomics research. No matter how large a group of excellent candidate genes have been discovered, it is useless if the survival analysis at the final stage does not reveal that the expression level is related to the prognosis of the patient. Thus, improving sensitivity in gene survival analysis is an issue that has great impact on genomics and biology research. Therefore, the present invention proposes a method that can detect genes that could not be found by existing survival analysis methods and has a higher sensitivity than the existing methods, and an apparatus for performing the method. There is an effect that a result having reliability can be generated.

A module, processing unit, device or unit may be processors executing sequential execution processes stored in memory (or storage unit). Each of the steps described in the above embodiments may be performed by hardware / processors. Each module / block / unit described in the above embodiments may operate as a hardware / processor. Further, the methods proposed by the present invention can be executed as codes. The code may be written to a storage medium readable by the processor and thus read by a processor provided by the apparatus.

The method inventions according to the present invention can all be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium.

The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the medium may be those specially designed and constructed for the present invention or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. This is possible. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined by the equivalents of the claims, as well as the claims.

Claims (20)

In a survival analysis method according to the expression level of a gene,
Calculating a standard normal distribution of the expression amount of the gene;
Setting a boundary value in the calculated normal normal distribution;
Disassembling the expression of the gene based on the set boundary value; And
Using the discretized results as an analytical element in a survival analysis model;
Lt; / RTI >
The step of setting the boundary value comprises:
Applying the generated discretized results to the survival analysis model to determine respective p-values corresponding to the plurality of boundary values for the survival analysis results, And a threshold value corresponding to a low value as the threshold value. The method of claim 1, wherein the step of setting the boundary value comprises:
Wherein the median (z = 0) of the standard normal distribution is set to the boundary value. The method of claim 1, wherein the step of setting the boundary value comprises:
Wherein one of the first boundary value zi, the second boundary value zii, and the third boundary value ziii is set as the boundary value. 4. The method of claim 3, wherein the setting of the boundary value comprises:
Applying the resulting discretized result to the survival analysis model using the first boundary value zi to determine a first p-value (p1) for the survival analysis result;
Applying the resulting discretized result to the survival analysis model using the second threshold value zii to determine a second p-value (p2) for the survival analysis result;
Applying the resulting discretized results to the survival analysis model using the third boundary value ziii to determine a third p-value (p3) for the survival analysis results;
Determining a p-value (p) having a lowest one of the first p-value, the second p-value, and the third p-value; And
Setting a value associated with the determined p-value (p) among the first boundary value zi, the second boundary value zii, and the third boundary value ziii as the boundary value;
Gt; expression < / RTI > 5. The method of claim 4, wherein the step of setting the boundary value comprises:
Wherein one of the first boundary value zi, the second boundary value zii, the third boundary value ziii, and the fourth boundary value ziv is set as the boundary value,
The application of the fourth boundary value ziv to the survival analysis model is excluded when the number of samples indicating the result of the generated discretization is equal to or less than the threshold value by using the four boundary value ziv Survival analysis method according to gene expression amount. 6. The method of claim 5,
The first boundary value zi is -2 (z = -2)
The third boundary value ziii is 2 (z = 2)
Wherein the second boundary value (zii) and the fourth boundary value (ziv) are values between -2 and 2, respectively. 5. The method of claim 4,
A survival analysis method according to a gene expression amount characterized by a Cox-proportional hazard model or a log-rank test model. In the survival analysis apparatus according to the expression amount of the gene,
The standard normal distribution for the expression level of the gene is calculated,
Setting a boundary value in the calculated standard normal distribution,
Disassembling the expression of the gene based on the set boundary value,
The result of the discretization is used as an analysis element in the survival analysis model
Applying the generated discretized results to the survival analysis model to determine respective p-values corresponding to the plurality of boundary values for survival analysis results, and if the determined p-values And the threshold value corresponding to the lowest value among the threshold values. 9. The survival analysis apparatus according to claim 8,
Wherein the median (z = 0) of the standard normal distribution is set to the boundary value. The survival analysis apparatus according to claim 8, wherein the survival analysis apparatus sets one of the first boundary value (zi), the second boundary value (zii) and the third boundary value (ziii) The survival analysis device according to the amount of expression. 11. The apparatus according to claim 10,
Applying the generated discretized results to the survival analysis model using the first boundary value zi to determine a first p-value (p1) for the survival analysis results,
Applying the resulting discretized result to the survival analysis model using the second boundary value zii to determine a second p-value (p2) for the survival analysis result,
Applying the resulting discretized results to the survival analysis model using the third boundary value ziii to determine a third p-value (p3) for the survival analysis result,
Determining a p-value (p) having a lowest one of the first p-value, the second p-value, and the third p-value,
A value related to the determined p-value (p) among the first boundary value zi, the second boundary value zii, and the third boundary value ziii is set as the boundary value. The survival analysis device according to the amount of gene expression. 12. The apparatus according to claim 11,
Wherein one of the first boundary value zi, the second boundary value zii, the third boundary value ziii, and the fourth boundary value ziv is set as the boundary value,
The application of the fourth boundary value ziv to the survival analysis model is excluded when the number of samples indicating the result of the generated discretization is equal to or less than the threshold value by using the four boundary value ziv A survival analysis device based on the expression level of the gene. 14. The survival analysis apparatus according to claim 12,
The first boundary value zi is set to -2 (z = -2)
The third boundary value ziii is set to 2 (z = 2)
Wherein the second boundary value (zii) and the fourth boundary value (ziv) are set to values between -2 and 2, respectively. 12. The method of claim 11,
Cox-proportional hazard model or log-rank test model. For survival analysis according to the expression level of the gene,
Calculating a standard normal distribution of the expression amount of the gene;
Setting a boundary value in the calculated normal normal distribution;
Disassembling the expression of the gene based on the set boundary value; And
And using the discretized results as an analytical element in a survival analysis model,
The step of setting the boundary value comprises:
Applying the generated discretized results to the survival analysis model to determine respective p-values corresponding to the plurality of boundary values for the survival analysis results, And setting a boundary value corresponding to a lower value as the boundary value. ≪ Desc / Clms Page number 24 > 16. The method of claim 15, wherein setting the boundary value comprises:
And setting the median of the standard normal distribution (z = 0) to the boundary value. 16. The method of claim 15, wherein setting the boundary value comprises:
And setting one of the first boundary value zi, the second boundary value zii, and the third boundary value ziii as the boundary value. 18. The method of claim 17,
Applying the resulting discretized result to the survival analysis model using the first boundary value zi to determine a first p-value (p1) for the survival analysis result;
Applying the resulting discretized result to the survival analysis model using the second threshold value zii to determine a second p-value (p2) for the survival analysis result;
Applying the resulting discretized results to the survival analysis model using the third boundary value ziii to determine a third p-value (p3) for the survival analysis results;
Determining a p-value (p) having a lowest one of the first p-value, the second p-value, and the third p-value; And
Setting a value associated with the determined p-value (p) among the first boundary value zi, the second boundary value zii, and the third boundary value ziii as the boundary value;
Readable recording medium having recorded thereon a computer readable program for executing the program. 19. The method of claim 18,
Setting one of the first boundary value zi, the second boundary value zii, the third boundary value ziii, and the fourth boundary value ziv as the boundary value,
(Ziv) is used to exclude the application of the fourth boundary value (ziv) to the survival analysis model when the number of samples representing the resulting discretized result is less than or equal to a threshold value A computer-readable recording medium on which a program is recorded. 19. The method of claim 18,
A computer-readable recording medium recording a program for performing a Cox-proportional hazard model or a log-rank test model.

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