JP4307807B2 - Data processing apparatus, method, and computer program - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a technique for clustering data, and particularly to a technique suitable for clustering data that is radially distributed from a predetermined reference point, such as SNP (Single Nucleotide Polymorphism) data. .
[0002]
[Prior art]
Currently, in the field of bioinformatics, studies on individual differences based on differences in gene base sequences are being conducted.
This individual difference is considered to arise from a sequence difference of about 0.1% of the base sequence of the gene, and this difference is called genetic individuality (polymorphism). Of these polymorphisms, one that differs by only one base is called SNP (“single nucleotide polymorphism”).
This SNP is presumed to exist at a rate of about one place per several hundred to 1,000 bases, and it is considered that there are 3 to 10 million SNPs in the genome.
Then, by identifying this SNP and analyzing it against factors such as clinical data and the environment, a drug with a specific single base type may not work, and disease prevention and diagnosis It can be used for treatment.
[0003]
Thus, in order to realize the analysis using the SNP, it is necessary to analyze where the SNP is present and at what frequency.
Among them, when performing frequency analysis of SNP, TaqMan method, Invader method or the like is used. These methods measure the amount of SNP fluorescence emitted with two types of special reagents, and based on this fluorescence emission amount data, two types of homozygotes (for example, AA and GG when the base is A or G) and It is necessary to divide into two or three classifications of one type of heterozygote (for example, AG) and obtain the appearance frequency for each classification.
In order to perform SNP frequency analysis, conventionally, based on the amount of light emitted from each reagent, each data is plotted on two-dimensional coordinates. I was going.
[0004]
[Problems to be solved by the invention]
However, in the conventional method, since the data plotted on the two-dimensional coordinates are clustered by human eyes, the judgment criteria for clustering are not constant, and not only the clustering varies but also humans perform the visual observations. Clustering took a lot of time and there were problems such as human error.
[0005]
For this reason, automation of clustering is required, so it is conceivable to use a general clustering method such as the K-means method.
However, since the SNP data has a characteristic of being distributed radially around a certain center point when plotted on two-dimensional coordinates, it is based on the light emission amount using a general clustering method such as the K-means method. When clustering is performed, data that are close to each other are simply clustered, so that correct clustering is not possible, such as the formation of a cluster that spans homo and hetero, which are essentially different clusters, and automation is difficult. There was a problem that there was.
[0006]
The present invention has been made to solve the above-described problems and problems, and can appropriately cluster data. In particular, data that is distributed radially around a predetermined reference point, such as SNP data, can be obtained. It is an issue to provide a mechanism that enables appropriate clustering.
[0007]
[Means for Solving the Problems]
In order to solve the above-described problem, a data processing apparatus according to one aspect of the present invention is an apparatus for clustering a plurality of data, and plot processing means for plotting the data on two-dimensional coordinates, An angle information processing means for obtaining a straight line connecting the plotted individual data and a predetermined reference point, an angle information processing means for obtaining an angle between the straight line and the predetermined reference line, and a clustering process for clustering each data based on the angle information Means for processing the data.
[0008]
Further, the data is SNP fluorescence emission amount data of a gene by a predetermined two reagents, and the plotting means uses the fluorescence emission amount data of each reagent as an axis of a two-dimensional coordinate, You may make it plot on a two-dimensional coordinate.
[0009]
Further, a predetermined hypothetical point is taken on the coordinates, an angle between a straight line connecting the hypothetical point and each data on the coordinate and a predetermined line passing through the hypothetical point is obtained, and each of the data is determined based on the angle information. And a reference point processing means for determining the reference point from the intersection of the principal component straight lines of the clusters passing through the obtained cluster centers.
[0010]
Further, before performing the cluster analysis, it may further include means for extracting a point existing at a predetermined distance from the reference point and excluding the extracted point from the cluster analysis target.
[0011]
The cluster processing means may further include a display processing means for performing clustering of a plurality of patterns and displaying in parallel the selectable results of the plurality of patterns performed by the cluster processing means.
Further, the data is SNP fluorescence emission amount data of a gene by a predetermined two reagents, and the plotting means uses the fluorescence emission amount data of each reagent as an axis of a two-dimensional coordinate, You may make it plot on a two-dimensional coordinate.
[0012]
A data processing method according to an aspect of the present invention is a method for classifying a plurality of data into a predetermined class by a computer, a process of plotting each of the data on coordinates, and the plotted individual data And a predetermined reference point, a process for determining an angle between the straight line and the predetermined reference line, and a process for clustering each data based on the angle information.
[0013]
A computer program according to one aspect of the present invention is a computer program for classifying a plurality of data into a predetermined class for a computer, and processing for plotting each of the above data on coordinates for the computer And calculating a straight line connecting the plotted individual data and a predetermined reference point, calculating an angle between the straight line and the predetermined reference line, and processing for clustering each data based on the angle information. It is made to perform.
[0014]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, an embodiment in which a data processing apparatus and a computer program according to the present invention are applied to an SNP data processing system will be described with reference to the drawings.
FIG. 1 shows an example of a SNP data processing system according to this embodiment.
As shown in FIG. 1, this system includes an SNP data processing device 1 and a result confirmation processing device 2, a preprocessing device 3, a correction processing device 4, a merge processing device 5, and an SNP that constitute a data processing device according to the present invention. It consists of a management device 6.
Each of these devices may be configured to be mutually connectable via a LAN (Local Area Network) or the like, or configured to exchange data via a predetermined medium such as a CD-ROM, FD, or MO. May be.
[0015]
The pretreatment device 3 is a computer that performs processing by the TaqMan method or the like.
For example, the pretreatment device 3 measures the fluorescence emission amount of SNPs on a pair of chromosomes using two types of special reagents, and performs processing to generate fluorescence emission amount data of each SNP.
The fluorescence emission amount data is composed of a color and its emission intensity. For example, if the gene is homozygous of AA, one of the two reagents emits light, and if it is homozygous of GG, another reagent emits light and changes to another color. Then, since each reagent emits light, it is an intermediate color.
[0016]
The correction processing device 4 is a computer for correcting the data rejected by the result confirmation processing device 2.
As this correction processing, for example, the correction processing device 4 refers to the rejected data file (reject file), acquires the fluorescence emission amount data that is the basis of the rejected data from the preprocessing device 3, and By displaying this on the two-dimensional coordinates, the operator visually confirms the data distribution and performs a process for enabling manual clustering.
[0017]
The merge processing device 5 merges the data checked by the result checking device 2, the corrected data corrected by the correction processing device 4, and the uncorrectable reject data to create management SNP data. It is a computer that performs.
The SNP management device 6 is a computer that stores the created management SNP data and manages it by creating a database.
[0018]
The SNP data processing device 1 is a device for clustering SNP data. The SNP data processing device 1 is constituted by a computer, and includes a CPU (Central Processing Unit), a computer program executed by the CPU, an internal memory such as a RAM and a ROM for storing the computer program and predetermined data, a hard disk drive, and the like The functional block shown in FIG. 2 can be configured by the external storage device.
The function block shown in FIG. 2 includes an assay data storage unit 101, a call data storage unit 102, a setting processing unit 103, a plot processing unit 104, a reference point processing unit 105, a labeling region processing unit 106, an angle information processing unit 107, a clustering. The processing unit 108 and the fitness level processing unit 109 are configured.
[0019]
The assay data storage unit 101 is a storage unit that stores fluorescence emission amount data of each SNP data.
In the assay data storage unit 101, for example, the file name of each SNP data, the fluorescence emission amount data of the SNP, and the like can be stored.
[0020]
The call data storage unit 102 can store data obtained as a result of automatic clustering processing performed by the SNP data processing device 1.
The call data storage unit 102 can store, for example, each SNP data and cluster information of each SNP data.
[0021]
The setting processing unit 103 can perform initial file setting processing and the like.
The plot processing unit 104 performs a process of plotting this on coordinates based on the fluorescence emission amount data of each SNP stored in the assay data storage unit 101. For example, the plot processing unit 104 can process this process by plotting each SNP data on a two-dimensional coordinate with the light emission amount of one reagent as the X axis and the light emission amount of the other reagent as the Y axis.
[0022]
The reference point processing unit 105 performs processing for obtaining a reference point serving as a reference when measuring the angle on the coordinates of each SNP data.
As this processing, for example, the reference point processing unit 105 sets the origin on the coordinates as a temporary reference point (assumed point), and sets the angle formed between the straight line connecting each SNP data on the coordinates from the origin and the X axis. Based on this, the SNP data is classified into a plurality of clusters, a principal component straight line at the center of each cluster is obtained, and the same process is repeated again with the intersection of the principal component straight lines as the next hypothetical point. The point that has converged can be used as the reference point.
It should be noted that the reference point is not determined by determining the point at which the hypothetical point has converged, but the reference point processing unit 105 may determine the point obtained by repeating the above-described processing a predetermined number of times as the reference point. Good. Alternatively, if the convergence is not achieved, the reference point processing unit 105 may determine the first reference point (such as the origin) as the reference point.
[0023]
The labeling area processing unit 106 performs a process of classifying a labeling area that is a target of cluster analysis and a non-labeling area that is not a target of cluster analysis.
As this processing, for example, the labeling area processing unit 106 takes an intermediate point (x_median, y_median) between the maximum value and the minimum value of the SNP data, and this intermediate point Based on the origin When the distance is larger than the threshold (S), the labeling region is used, and when the distance is small, the non-labeling region can be used.
The threshold value (S) for labeling may be determined by the operator each time an operation is performed, or may be set in advance as a default.
[0024]
The angle information processing unit 107 performs processing for obtaining an angle between a straight line connecting each SNP data from a reference point on coordinates and a predetermined reference line.
The reference line is a line that serves as a reference when measuring an angle. For example, the X axis or the Y axis may be used as a reference, or another axis may be used as a reference line and is arbitrary.
[0025]
The clustering processing unit 108 performs processing for clustering the SNP data based on the angle information of the SNP data.
This clustering process can be performed using an existing clustering algorithm such as a k-means method based on one-dimensional angle information.
In the case of performing clustering, for example, the clustering processing unit 108 can perform two patterns of processing in parallel, that is, clustering into two clusters and clustering into three clusters.
[0026]
The fitness processing unit 109 performs a process of calculating a fitness indicating whether or not the result of clustering by the classing processing unit 108 is suitable as clustering of SNP data.
As this processing, for example, the fitness processing unit 109 sets α as the distance between the clusters and β as the data distribution in each cluster, and the larger the ratio (F ratio) of α / β, the more The goodness of fit can be determined as appropriate clustering. As another fitness level of clustering, for example, the fitness level processing unit 109 can determine the fitness level based on whether or not the allele frequency is distributed according to the Hardy Weinberg equilibrium law. The Hardy Weinberg equilibrium law is, for example, when the frequencies of alleles M and N are p and q (p + q = 1), respectively, and the genotype frequency is expressed by the product of the constituent allele frequencies. The frequency of p ² , The frequency of NN is q ² The rule that the frequency of MN becomes a ratio of 2pq.
[0027]
The result confirmation processing device 2 is a device that performs processing for causing the operator to confirm the processing results clustered by the SNP data processing device 1.
As shown in FIG. 3, the result confirmation processing device 2 is connected to a display 20 and an input device 30 such as a keyboard and a mouse. The result confirmation processing device 2 includes a computer, a CPU, a computer program executed by the CPU, a RAM for storing the computer program and predetermined data, an internal memory such as a ROM, and an external storage device such as a hard disk drive. Thus, the functional block shown in FIG. 3 can be configured.
The functional block shown in FIG. 3 includes a confirmation data storage unit 201, a data input / output processing unit 202, and a display control unit 203.
[0028]
The confirmation data storage unit 201 is a storage unit for storing data for which the confirmation of the clustering result has been completed by the operator. The confirmation data storage unit 201 can store SNP data and clustered cluster information.
[0029]
The data input / output processing unit 202 can perform a process of accepting input of SNP clustering data generated by the SNP data processing apparatus 1 and a process of outputting data that has been confirmed to the merge processing apparatus 5.
[0030]
The display control unit 203 displays the clustered result data on the display 20 and performs processing for requesting confirmation from the operator.
In addition, when the SNP data processing device 1 classifies two patterns of two rasters and three clusters, the display control unit 203 displays the results of these two patterns in parallel on the display 2 and operates them. Can check and select the result data.
[0031]
Next, an embodiment of a data processing method according to the present invention will be described with reference to the drawings.
First, the processing flow of the entire system will be described with reference to FIG.
In FIG. 1, the pretreatment device 3 acquires SNP fluorescence emission data using the TaqMan method or the like (S1).
The SNP data processing device 1 acquires the fluorescence emission amount data of the SNP from the preprocessing device 3, performs clustering of the SNP data, and labels the SNP data indicating the cluster (S2).
[0032]
When the clustering is completed, the result confirmation processing device 2 displays the result on the two-dimensional coordinates based on the clustering result data generated by the SNP data processing device 1, and requests confirmation from the operator (S3).
As a result of the confirmation, if it is determined by the operator that proper clustering has not been performed, the reject data name is written to the reject file and provided to the correction processing device 4 (S4).
[0033]
The correction processing device 4 acquires SNP fluorescence emission amount data from the preprocessing device 3 based on the reject data name and displays it on a predetermined display so that the operator can correct the clustering visually. (S5).
[0034]
The merge processing device 5 acquires the data determined to be proper clustering by the operator's confirmation in the process of S3, the data corrected by the process of S5, and the reject data determined to be uncorrectable. Management data is created by merging data (S6).
[0035]
When the merge process is completed, the merged management data is provided to the SNP management apparatus 6, which manages the management data by creating a database (S7) and ends the process.
[0036]
Next, detailed processing when the SNP data processing apparatus 1 performs clustering will be described with reference to FIG.
In FIG. 4, first, the setting processing unit 103 refers to an initial setting file input by an operator, and performs initial setting such as a predetermined constant for clustering (S101).
The initial setting file includes, for example, an output file name, an input file name, a setting file number indicating the number of files to be processed, the number of records in one file, and a threshold value of a labeling area (S ), And data such as rotation angle for placing data in the continuous area of tangent.
[0037]
The setting processing unit 103 opens the output file stored in the call data storage unit 102 (S102), and determines whether the number of read SNP data files has reached the number of setting files to be processed this time ( S103).
If the number of set files has been reached as a result of the determination, it is determined that the processing has been completed for all the SNP data files that are the targets of the current processing, and the processing ends.
[0038]
If the number of set files has not been reached as a result of the discrimination, the plot processing unit 104 opens the input file stored in the assay data storage unit 101, reads the SNP fluorescence emission amount data, Plot on the two-dimensional coordinates based on the intensity of the luminescent color (S104).
The two-dimensional coordinates are obtained by taking the light emission amount of one reagent on one axis (X axis) and the light emission amount of the other reagent on the other axis (Y axis).
[0039]
When the plotting is completed, the reference point processing unit 105 converts each SNP data into polar coordinates, and performs one-dimensional clustering using the angle information of the polar coordinates (S105).
The polar coordinates of each data can be obtained, for example, based on the angle and distance between the straight line and the X axis, with the reference point processing unit 105 obtaining a straight line connecting the data with the origin on the coordinate as the pole. In addition, the clustering can be performed by the reference point processing unit 105 using a known clustering method such as a K-means method, for example.
[0040]
When clustering is completed, the reference point processing unit 105 performs principal component analysis of each cluster using a predetermined principal component analysis algorithm, finds a principal component line passing through the center of each cluster, and determines an intersection of these principal component lines. (S106).
Then, the reference point processing unit 105 performs the processes of S105 and S106 a predetermined number of times (n times) again using this intersection as a temporary reference point (assumed point), and the intersection n from the obtained intersection 1 converges to a certain position. It is determined whether or not (S107).
As a result of the determination, if the intersection has not converged, the process returns to the above-described process of S105 and the process is repeated again.
If it is determined in the process of S107 that the intersection has converged to a certain position, the intersection n is set as a reference point (S108).
[0041]
Instead of determining whether or not the intersection has converged, the number of times the intersection calculation is repeated is set in advance, and the reference point processing unit 105 returns to the processing of S105 and repeats the processing up to the set number of times. The reference point may be determined based on the result.
[0042]
When the reference point setting is completed, the labeling area processing unit 106 displays the SNP data plotted on the two-dimensional coordinates. Middle The coordinates (x_median, y_median) of the point are acquired (S109).
this Middle The point (M) is shown in FIG. like , The maximum value Max and the minimum value Min in the SNP fluorescence emission amount data are obtained, and this intermediate value (x_median) , y_median) Middle Can be a point.
[0043]
The labeling area processing unit 106 determines whether the number of read records has reached the set number of records, that is, whether all the records have been processed (S110).
If the set number is not reached as a result of the determination, the labeling area processing unit 1 0 6 determines that the value of the coordinates (x, y) of one SNP fluorescence emission amount data is (x / x_median). ² + (Y / y_median) ² <Whether or not it is the threshold (S), that is, origin It is determined whether or not the distance from is within a predetermined threshold S (S111).
As a result of the discrimination, for SNP data having coordinates smaller than the threshold, the SNP data is set as a non-labeling region, and a flag to be excluded from the target data to be clustered is set (S112).
As a result of the determination, a flag indicating that the SNP data having coordinates larger than the threshold value belongs to the labeling area is set (S113).
An example of this labeling process is shown in FIG. As shown by the arc-shaped line in FIG. 6, the inner area is a non-labeling area, and the area outside the arc-shaped line is a labeling area.
[0044]
If the number of read records reaches the set number as a result of the determination processing of the labeling region and the determination in S110, the angle information processing unit 107 sets the reference point as a pole for the SNP fluorescence emission amount data of the labeling region. The polar coordinates are converted (S114).
As this processing, for example, as shown in FIG. 7, the reference point (the origin in the illustrated example) is a pole, and the angle between the straight line connecting this reference point and each data and the reference line (for example, X axis) is set. Based on this measurement, SNP fluorescence emission data can be converted into polar coordinates.
[0045]
Subsequently, in FIG. 5, when the conversion to polar coordinates is completed, the clustering processing unit 108 performs one-dimensional clustering by a predetermined clustering algorithm based on the polar coordinate angle information of each SNP data (S115).
At this time, the clustering processing unit 108 performs clustering in two cases of clustering into two clusters and clustering into three clusters. For this clustering process, for example, an existing clustering algorithm such as the k-means method can be used.
An example of creating a histogram based on the angle is shown in FIG. In FIG. 8, the horizontal axis represents an angle (radian) and the vertical axis represents the number of data.
[0046]
When the clustering is completed, the clustering processing unit 108 stores the polar coordinates and the clustered two-dimensional coordinates in the call data storage unit 102 (S116).
[0047]
The fitness processing unit 109 calculates the F ratio of the cluster on the coordinates for each of the two clusters and the three clusters (S117).
In addition, the fitness processing unit 109 calculates the allele ratio and the like for each of the two clusters and the three clusters, and calculates the degree to which this ratio conforms to the Hardy Weinberg equilibrium law (S118).
[0048]
Then, the fitness processing unit 109 determines whether appropriate clustering is performed or reject data that cannot be properly clustered based on the F ratio of each cluster and the degree of conformity with the Hardy Weinberg equilibrium law (S119). ).
This discrimination process can be processed by determining threshold values for the degree of fitness of the F ratio and the Hardy Weinberg equilibrium law in advance, and discriminating from the reject data when these calculation results are below this threshold value.
[0049]
When it is determined that the data is rejected as a result of the determination, the fitness processing unit 109 creates a reject file describing the data name, sample ID, and the like (S120).
[0050]
Also, when it is determined that the clustering is appropriate or the processing in S120 is completed, the label, F ratio, and the degree of conformity of the Hardy Weinberg equilibrium law are stored in the call data storage unit 102 as an output file (S121), the process returns to the above-described process of S103, the process is repeated until the number of set files is reached, and the process is terminated.
[0051]
Next, processing when the operator confirms the clustering data created by the result confirmation device 2 will be described with reference to FIG.
In FIG. 9, when the result confirmation processing device 2 is provided with two patterns of clustering result data from the SNP data processing device 1 via a predetermined network or the like, the data input / output processing unit 202 converts the provided data. Accept (S201).
The display control unit 203 determines whether the data has been clustered or rejected without clustering based on the F ratio of each cluster of the output file and the fitness data of the Hardy Weinberg equilibrium law (S202). ).
[0052]
As a result of the discrimination, if the data has been subjected to appropriate clustering, the display control unit 203 displays the clustering result having a high fitness as an active state (example shown in the figure) as a two-dimensional graph as shown in FIG. The left side is the active state), and the clustering result having a low fitness is displayed in parallel on the display 2 in a shaded state (S203).
At this time, data belonging to each cluster may be represented by different colors. Further, the labeling data may be displayed as a round shape, and the non-labeling data may be displayed as a square shape.
[0053]
In this state, the operator compares the two clustering results and visually determines whether the clustering results are correct.
Then, the display control unit 203 determines that the operator selects the clustering result selected (3 cluster side in the example of FIG. 10) as the correct clustering result, or the clustering result not selected (example of FIG. 10). In step S214, it is determined which of the two cluster side) is determined to be correct, or which of the two cluster sides is determined not to be an appropriate clustering result.
[0054]
When the operator determines that the active clustering result is correct and designates the “NEXT” radio button in FIG. 10, the display control unit 203 confirms the selected clustering result as an appropriate clustering result. The data is stored in the data storage unit 201 (S205), and the process ends.
If there is data to be processed next, the process returns to S201 and is repeated.
[0055]
Further, when the operator determines that the clustering result of the shaded one is correct and designates the graph or radio button (“2 cluster” radio button in the example of FIG. 10), the display control unit 203 selects The clustering result thus obtained is switched to the active state display (S206), and when the operator instructs the NEXT button, the clustering data is stored in the confirmation data storage unit 201 and the process is terminated.
If the operator determines that none of the clustering results is appropriate, the process proceeds to S208 described later.
[0056]
If it is determined in the process of S202 that the data is reject data, the display control unit 203 displays the characters “REJECTED” in an active state and displays any clustering result with a shade ( S207).
In this state, the operator visually checks to determine whether correction is possible, and the display control unit 203 determines whether the operator has given an instruction to correct clustering (S208).
When the operator manually corrects the data, the data is provided to the correction processing device 4 by instructing the “Manual call” radio button in FIG. 10 (S209), and the operator manually performs the clustering result. The process is terminated so that the correction can be made.
Further, when the operator determines that the data itself cannot be corrected, for example, when the original data itself is not appropriate, and indicates the “unable” radio button in FIG. 10, the display control unit 203 The data is stored in the confirmation data storage unit 201 as reject data (S210), and the process is terminated.
[0057]
As described above, according to the present embodiment, the plot processing unit 104 plots the SNP fluorescence emission amount data on the coordinates, and the angle information processing unit 107 obtains a straight line connecting the plotted individual SNP data and the reference point. Since the angle between this straight line and a predetermined reference line is obtained, and the SNP fluorescence emission amount data is clustered based on the angle information by the clustering processing unit 108, SNP data distributed radially around the reference point is obtained. Clustering can be performed appropriately.
Thereby, since the SNP data can be automatically clustered, uniform and error-free clustering can be performed as compared with the case where it is manually performed, and the work amount of the person who performs clustering can be reduced.
[0058]
Further, the reference point processing unit 105 takes a predetermined assumption point on the coordinates, obtains an angle between a straight line connecting the assumption point and each SNP fluorescence emission amount data on the coordinates and a predetermined reference line, and this angle information. For example, a position where the SNP data is away from the origin of coordinates is determined by clustering each SNP fluorescence emission amount data and determining the intersection of straight lines passing through the center of gravity of each obtained cluster as a reference point. Even if it is a case where appropriate clustering is not possible when the origin of coordinates is used as a reference, such as when the data is distributed in the network, clustering of SNP fluorescence emission amount data can be performed after setting an appropriate reference point.
[0059]
In addition, since the labeling region processing unit 106 extracts points existing at a predetermined distance from the reference point before performing the cluster analysis, the extracted point is excluded from the cluster analysis target. Thus, clustering can be performed after excluding data in a non-labeling region that is likely to cause an error in clustering in advance, so that more appropriate clustering can be performed.
[0060]
Further, the clustering processing unit 108 performs clustering of two patterns of 2 clusters and 3 clusters, and the display control unit 203 displays the clustering results of these two patterns in a selectable manner in parallel. Can compare two clusters, compare each clustering result, and select an appropriate cluster.
[0061]
In the above-described embodiment, an example in which the SNP data processing device 1, the result confirmation processing device 2, the preprocessing device 3, the correction processing device 4, the merge processing device 5, and the SNP management device 6 are configured as separate devices will be described. However, any or all of these functions may be realized by one apparatus, and is optional.
[0062]
In the above-described embodiment, the clustering process of the SNP fluorescence emission amount data has been described. However, the present invention is not limited to this, and any data that is radially distributed from a predetermined reference point can be applied. .
[0063]
The computer program for the SNP data processing apparatus 1 or the result confirmation processing apparatus 2 of the present embodiment may be stored and distributed in a computer-readable medium (FD, CD-ROM, etc.), superimposed on a carrier wave, Distribution via a communication network is also possible.
When the functions of the SNP data processing device 1 or the result confirmation processing device 2 are shared by an OS (Operating System) or jointly performed by the OS and an application program, only the portion other than the OS is used as a computer program. The computer program may be stored in a computer-readable medium, or the computer program may be distributed.
[0064]
【The invention's effect】
According to the present invention, data can be appropriately clustered, and particularly data distributed radially around a predetermined reference point such as SNP data can be appropriately clustered.
[Brief description of the drawings]
FIG. 1 is a diagram showing an outline and a processing flow of an embodiment of a system using a data processing apparatus according to the present invention.
FIG. 2 is a functional block diagram of the SNP data processing device according to the present embodiment.
FIG. 3 is a functional block diagram of a confirmation processing apparatus according to the embodiment.
FIG. 4 is a processing flow showing a processing flow of the SNP data processing apparatus according to the present embodiment.
FIG. 5 is a subsequent process flow showing a process flow of the SNP data processing apparatus according to the present embodiment.
FIG. 6 is a diagram showing a concept of labeling processing according to the present embodiment.
FIG. 7 is a diagram showing a concept of processing for acquiring angle information of each data on coordinates according to the embodiment.
FIG. 8 is a diagram showing an example of a histogram based on angle information according to the present embodiment.
FIG. 9 is a view showing a processing flow of the confirmation processing apparatus according to the embodiment.
FIG. 10 is a diagram showing an example of a screen of the confirmation processing apparatus according to the present embodiment.
[Explanation of symbols]
1 SNP data processor
2 Result confirmation processing device
104 Plot processing unit
105 Reference point processing section
106 Labeling area processing section
107 Angle information processing unit
108 Clustering processing unit
203 Display control unit

Claims (5)

Based on the result data obtained by experiments for analyzing the frequency of appearance of alleles for one SNP in DNA by using two types of fluorescent reagents designed for each SNP with individual fluorescent labels added, A data processing apparatus for performing data analysis based on emission intensity and emission color of the fluorescent label,
Corresponding to each SNP, analysis data storage means for storing fluorescence emission amount data including emission intensity of each fluorescent label;
With reference to the analysis data storage means, the fluorescence emission amount data is read out, and a two-dimensional coordinate diagram composed of an X axis indicating the emission intensity of one fluorescence reagent and a Y axis indicating the emission intensity of the other fluorescence reagent. Plotting means for plotting points based on each emission intensity of the fluorescence emission amount data;
Intermediate point calculation processing means for calculating intermediate intermediate point coordinates (x_median, y_median) based on the maximum value and the minimum value of each emission intensity among the points plotted in the two-dimensional coordinate diagram;
Based on the coordinates of the calculated intermediate point and the first threshold value for the region determination set in advance,
For the points plotted in the above two-dimensional coordinate map,
(X / x_median) ² + (Y / y_median) ² <First threshold
Subject exclusion processing means for performing a first threshold determination processing for determining whether or not the above mathematical formula is satisfied, and excluding a point determined to satisfy the mathematical formula from a target of clustering processing;
An angle information processing means for calculating a straight line connecting the point and the origin with respect to a point determined not to satisfy the mathematical formula by the threshold determination, and calculating angle information of an angle formed by the straight line and the X axis; ,
Based on the calculated angle information, clustering processing means for generating a clustering result into two types of clustering results in which the plotted points are 2 clusters and a clustering result in which 3 clusters are plotted with respect to the same two-dimensional coordinate diagram When,
Display control means for displaying the two types of clustering results in parallel;
A data processing apparatus comprising: A variance ratio is calculated for the two types of clustering results, and it is determined whether or not the variance ratio is larger than a second threshold value for a preset fitness level. A clustering result evaluation unit that determines that the appropriate clustering is performed when it is determined that the variance ratio is greater than
Further having
The data processing apparatus according to claim 1. The display control means is a display form that can identify that the clustering result determined to be appropriate is appropriate, while the display form that can identify that the clustering result determined to be inappropriate is inappropriate, Display in parallel,
The data processing apparatus according to claim 2. Corresponding to each SNP, it is performed by a computer having analysis data storage means for storing the fluorescence emission amount data including the emission intensity of each fluorescent label, and two types designed for each SNP with individual fluorescent labels added By using a fluorescent reagent, based on the result data obtained by an experiment for analyzing the frequency of occurrence of an allele for one SNP in DNA, data analysis based on emission intensity and emission color of the fluorescent label is performed. A data processing method,
The computer
With reference to the analysis data storage means, the fluorescence emission amount data is read out, and a two-dimensional coordinate diagram composed of an X axis indicating the emission intensity of one fluorescence reagent and a Y axis indicating the emission intensity of the other fluorescence reagent. A process of plotting points based on each emission intensity of the fluorescence emission amount data,
A process of calculating intermediate intermediate point coordinates (x_median, y_median) based on the maximum value and the minimum value of each emission intensity among the points plotted in the two-dimensional coordinate diagram;
Based on the coordinates of the calculated intermediate point and the first threshold value for the region determination set in advance,
For the points plotted in the above two-dimensional coordinate map,
(X / x_median) ² + (Y / y_median) ² <First threshold
A first threshold determination process for determining whether or not the above mathematical expression is satisfied, and a process for excluding the point determined to satisfy the mathematical expression from the target of the clustering process;
Processing for calculating a straight line connecting the point and the origin with respect to a point determined not to satisfy the mathematical formula by the threshold determination, and calculating angle information of an angle formed by the straight line and the X axis;
Based on the calculated angle information, for the same two-dimensional coordinate map, a process of generating clustering results into two types, that is, a clustering result in which the plotted points are two clusters and a clustering result in which three clusters are formed;
A process of displaying the two types of clustering results in parallel;
The data processing method characterized by performing. Corresponding to each SNP, an analysis data storage means for storing fluorescence emission amount data including the emission intensity of each fluorescence label is added to a computer having an individual fluorescence label and two types designed for each SNP. In order to execute data analysis based on the emission intensity and emission color of the fluorescent label based on the result data obtained by the experiment for analyzing the appearance frequency of the allele for one SNP in the DNA by using the fluorescent reagent Computer program,
For the above computer
With reference to the analysis data storage means, the fluorescence emission amount data is read out, and a two-dimensional coordinate diagram composed of an X axis indicating the emission intensity of one fluorescence reagent and a Y axis indicating the emission intensity of the other fluorescence reagent. A process of plotting points based on each emission intensity of the fluorescence emission amount data,
A process of calculating intermediate intermediate point coordinates (x_median, y_median) based on the maximum value and the minimum value of each emission intensity among the points plotted in the two-dimensional coordinate diagram;
Based on the coordinates of the calculated intermediate point and the first threshold value for the region determination set in advance,
For the points plotted in the above two-dimensional coordinate map,
(X / x_median) ² + (Y / y_median) ² <First threshold
A first threshold determination process for determining whether or not the above mathematical expression is satisfied, and a process for excluding the point determined to satisfy the mathematical expression from the target of the clustering process;
A process for calculating a straight line connecting the point and the origin with respect to a point determined not to satisfy the mathematical formula by the threshold determination, and calculating angle information of an angle formed by the straight line and the X axis;
Based on the calculated angle information, for the same two-dimensional coordinate map, a process of generating clustering results into two types, that is, a clustering result in which the plotted points are two clusters and a clustering result in which three clusters are formed;
A process of displaying the two types of clustering results in parallel;
A computer program for executing

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