KR20030088837A - Microarray copy image creation system and method thereof - Google Patents

Abstract

PURPOSE: A system for generating microarray facsimile image and a method thereof are provided to divide accurate areas of spots and generate a facsimile image close to an actual image. CONSTITUTION: A mathematical model generating module(40) derives a mathematical model related to gene distribution in spots of a gene solution dropped on a slide glass. An image storing module(50) stores various image information including the primitive image of a microarray chip. An image converting module(60) converts the primitive image into an image for a test, and constructs an overlap image from the image for a test. An edge detecting module(70) detects edges at the spot and a background area by dividing the spot in segment shapes for measuring revelation of genes corresponding to each spot. A spot template generating module(80) applies coordinates of pixels in the spot to the mathematical mode for generating spot templates. A random characteristic generating module(30) generates random characteristic values representing fluorescence intensity of the spots. A spot facsimile image generating module(90) applies the random characteristic values to the spot templates for generating a spot facsimile image. A microarray facsimile image generating module(100) reconstructs a whole microarray image by using the generated spot facsimile image.

Description

MICROARRAY COPY IMAGE CREATION SYSTEM AND METHOD THEREOF}

The present invention relates to a microarray simulated image generating system and method thereof, comprising: a microarray for reconstructing an image based on a template obtained from edge detection of an actual microarray image by including a fabrication and an experimental process of a microarray chip in a simulation. A simulated image generation system and method thereof are provided.

Microarray chip is a high-density experimental tool in which thousands to tens of thousands of DNA are integrated onto a slide glass with spots of about 200 μm in diameter. Fluorescence of mRNA of two groups, namely, experimental and control groups, to be compared After labeling, it is competitively bound to the chip and the respective fluorescence intensity (Fluorescence Intensity) can be measured to determine the relative expression patterns of thousands to tens of thousands of genes at the same time.

The microarray chip thus made greatly contributes to the analysis of unique genes expressed only in specific cells or tissues. In addition, it can be used for mass gene analysis, diagnosis and monitoring of human disease, research on biological response to environmental factors, food stability test, new drug development, clinical pathology and animal and plant quarantine.

The manufacturing method of such a microarray chip is as follows.

The test DNAs are first spotted on a slide glass into uniform sized spots to create an array of thousands to tens of thousands of spots. In addition, the mRNA is extracted from the control and experimental groups, and the reverse transcription of these mRNAs is carried out, at which time, the fluorescent (nucleotide) bases of red (Cy5) and green (Cy3) are inserted, and tagging is performed on the mRNA itself. Let's do it.

At this time, the genes expressed in yellow are represented by the overlap of green and red, and these genes can be seen that similar amounts are expressed in two environments.

The two mRNAs thus synthesized are mixed in the same amount and bound to the array chip, where the unbound genes are washed away, and only the bound genes remain, resulting in a microarray chip.

The manufactured microarray chip is read by a laser fluorescence scanner. At this time, the fluorescent image of the microarray chip is read in a pixel unit having a diameter of 5 μm or 10 μm according to the type of the scanner.

This fluorescence image is usually stored on a computer as an unsigned 16-bit image, where each gene's fluorescence indicates its gene expression, and this information is analyzed on computer software. Therefore, the range of fluorescence intensity that the microarray image can represent may range from 0 to (2 ¹⁶ -1), that is, to 65535.

However, in most experiments, genes with a high expression level of the fluorescence intensity of the spot close to 65535 are only a few of the genes, and since the expression level of most genes is much lower than this, the fluorescence intensity of the spot is also very high. low.

In addition, one pixel of the microarray image has a diameter of about 10 μm, and a spot having a diameter of about 200 μm includes about 20 pixels. Therefore, the microarray image looks very blurry when viewed with the naked eye. However, the microarray image analysis system to date has a limitation in separating the spot region and the background region from such an image.

On the other hand, when analyzing the genetic information, the microarray chip is a cDNA of a different gene is planted in a spot shape of about 200㎛ diameter on the slide glass, so each spot is separated into segments to measure the expression level of each gene.

In this case, except for some systems that detect the edge of the spot and separate and analyze the image of the spot, in order to extract the effective spot, most of the spots are located in the center of the segment by placing a reference circle of a constant size in the center of the segment. When the size of the reference circle becomes larger than the spot, the background as well as the spot is included in the reference circle. Therefore, in the microarray image analysis method using one or more of the average value, the median value, and the mode value of the fluorescence intensity of the spot, an error occurs in the data average value.

Alternatively, when the center of the segment is not located at the center of the spot but is shifted to one side, the position of the reference circle and the spot is shifted, so only a part of the spot included in the reference circle is used as valid information, and the rest of the spot is in the background. There is a problem in that the data error rate is increased.

In addition, the microarray image shows that the distribution of fluorescence intensity inside the spot has a specific pattern. In most spots, the fluorescence intensity at the edge is high and the intensity is lower toward the center of the spot. Thus, failure to isolate the exact area of the spot affects both the mean, median, or mode values.

Therefore, the technical problem to be achieved by the present invention is to simulate the software that includes all the actual image characteristics of the microarray as possible by comparing the simulated image value and the data value analyzed through the microarray image analysis system It is an object of the present invention to provide a microarray simulation image generation system and method for forming a microarray simulation image.

1 is a block diagram showing the configuration of a simulation image generating system according to an embodiment of the present invention.

2 is a block diagram illustrating a random characteristic value generation module according to an embodiment of the present invention.

3 is a diagram illustrating a spot template generation module according to an embodiment of the present invention.

4 is a flowchart illustrating a method of generating a simulated image according to an embodiment of the present invention.

5 is a flowchart illustrating an image processing process in a method of generating a simulated image according to an embodiment of the present invention.

*** Description of the symbols for the main parts of the drawings ***

30: random characteristic value generation module

40: mathematical model generation module

70 edge detection module

80: Spot template generation module

90: spot simulation image generation module

100: microarray simulation image generation module

In order to achieve this technical problem, a microarray simulation image generation system according to a feature of the present invention, a mathematical model generation module for deriving a mathematical model for the distribution of the gene (Spot) in the spot (Spot) of the dropping gene solution on the slide glass; An image storage module for storing various image information including a raw image (Image) for a microarray chip composed of a gene set extracted from a sample of a test group and a control group tagged by fluorescent bases of different colors; An image conversion module for converting an original image of the microarray chip stored in the image storage module into a test image, constructing an overlap image from the test image, and storing each image in the image storage module; An edge detection module that detects an edge in the spot area by separating the spot into segments to measure the expression level of a gene corresponding to each spot in the test image stored in the image storage module; A spot template generation module generating a spot template by applying the coordinates of a pixel in a spot set based on the spot edge template detected by the edge detection module to the mathematical model; Random characteristic value generation module for generating a random characteristic value indicating the fluorescence intensity of the spot after hybridization of the experimental group and the control mRNA; A spot simulation image generation module generating a spot simulation image by applying the random characteristic value to the spot template generated by the spot template generation module; And a microarray simulation image generation module for reconstructing the spot simulation image generated by the spot simulation image generation module into the entire microarray image.

The mathematical model derived from the mathematical model generation module preferably satisfies the following equation.

Where P (r) is the gene distribution in the spot on the slide glass, C (0) is the initial droplet concentration, K _C is the concentration constant, K _V is the volume constant, and r ₀ is the radius of the initial droplet And r _t is the radius of the droplet when time t.

The spot template generated by the spot template generating module preferably satisfies the following equation.

In the above equation, P _ij is the amount of gene fixation of the pixels in the spot (x _ij , y _ij ), C (0) is the initial droplet concentration, K _C is the concentration constant, K _V is the volume constant, and ζ _i is The distance from the point (ξ _i , η _i ) on the edge of the spot to the center of the spot (C _x , C _y ), r _ij is the distance from the center of the spot to the pixels (x _ij , y _ij ) in the spot.

The random characteristic value derived from the random characteristic value generation module preferably satisfies the following equation.

Where d _n is the target gene mass of the nth spot, C ₀ is the initial droplet concentration, K _V is the volume constant, ζ _i is the center of the spot at the point on the edge of the spot (ξ _i , η _i ) Is the distance to (C _x , C _y ).

In addition, the spot simulation image generated by the spot simulation image generation module preferably satisfies the following equation.

In the above formula, S _mn is the fluorescence intensity value of the n-th spot of the experimental group and the control group, a _m is the total mRNA amount of the experimental group and the control group, θ _mn is the ratio of the nth gene of the total mRNA amount expressed, d _n Is the target gene quantity of the nth spot, K _C is the concentration constant, K _V is the volume constant, ζ _i is the center of the spot (C _x , C _y ) at the point on the edge of the spot (ξ _i , η _i ) R _ij is the distance from the center of the spot to the pixels in the spot (x _ij , y _ij ).

In addition, the microarray simulation image generating system according to the present invention may further include a background image generating module for generating a background image through the background fluorescence intensity and background noise, the entire microarray by combining the spot simulation image and the background image Can be rebuilt with an image.

In addition, the method of generating a microarray simulation image according to a feature of the present invention, the first step of deriving a mathematical model for the distribution of the gene (Spot) in the spot (Spot) of the gene solution dropped on the slide glass; A second step of storing various image information including a raw image (Image) for a microarray chip consisting of a set of genes extracted from a sample of a test group and a control group tagged with fluorescent bases of different colors; Converting the original image into a test image, constructing an overlap image from the test image, and storing each image in the image storage module; A fourth step of separating spots into segments in order to measure the expression level of a gene corresponding to each spot in the test image, and detecting spot edges by detecting spot regions from each segment; Generating a spot template by applying the detected spot edge template to a mathematical model; Generating a random characteristic value representing the fluorescence intensity of the spot after hybridization of the experimental and control mRNAs; A seventh step of generating a spot simulation image by applying the random characteristic value to the spot template; And an eighth step of reconstructing the spot simulation image into a full microarray image.

The fifth step may include: setting new coordinates of a pixel in the spot by obtaining the center of the spot and the point on the edge of the spot; And generating a spot template by applying a coordinate of a pixel in the spot to a mathematical model.

The sixth step is to obtain the total mRNA amount of the experimental group or control group; Obtaining a ratio occupied by the n th gene in the total mRNA amount of the expressed gene; obtaining a target gene amount corresponding to the nth spot; Obtaining an amount of the probe capable of hybridizing to the nth spot from the total mRNA amount and the ratio of the nth gene; And obtaining the fluorescence intensity of the nth spot after hybridization from the amount of the probe and the amount of target DNA.

The eighth step may include: generating a spot array image by combining location information with a spot simulation image; And combining the background image with the spot array image to form a microarray simulation image.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings the most preferred embodiment that can be easily carried out by those of ordinary skill in the art as follows.

1 shows a configuration of a microarray simulated image generating system according to an embodiment of the present invention.

As shown in FIG. 1, the microarray simulated image generation system according to an embodiment of the present invention includes a background image generation module 20 for forming a background image through background fluorescence intensity and background noise,

Random characteristic value generation module 30 for generating a random characteristic value representing the fluorescence intensity of the spot after hybridization of the experimental group and the control mRNA,

Mathematical model generation module 40 for deriving a mathematical model of the distribution of genes in the spot of the gene solution loaded on the slide glass during the microarray chip generation process,

an image storage module 50 for scanning the cDNA microarray image and storing the raw image stored in the hard disk 10 in the form of 16-bit TIFF (Tag Image File Format), and various converted image information generated from the raw image;

An image conversion module 60 for converting the raw image stored in the image storage module 50 into a test image, constructing an overlap image from the test image, and then storing the overlap image in the image storage module 50;

Edge detection module 70 for dividing the spot into segments in order to measure the expression level of the gene corresponding to each spot of the overlap image stored in the image storage module 50, and detecting the edge of the spot area in each segment,

Spot template generation module 80 for generating a spot template by applying the coordinates of the pixel in the spot based on the spot edge template detected by the edge detection module 70 to the mathematical model,

Spot simulation image generation module 90 for generating a spot simulation image by applying a random characteristic value to the spot template generated by the spot template generation module 80 and

And a microarray simulation image generation module 100 for reconstructing the spot simulation image generated by the spot simulation image generation module 90 and the background image generated by the background image forming module 20 into a full microarray image.

The mathematical model generation module 40 calculates the distribution of DNA in the spot on the slide glass of the actual microarray chip, and mathematically models the physical and chemical phenomena occurring during the fabrication of the microarray chip.

Looking at the fabrication process of a general microarray chip, the slide glass is first coated with a substrate containing an aldehyde (or amine) group to facilitate the binding of the DNA and the glass plate before printing the DNA library onto the slide glass.

In addition, each DNA molecule is attached to an aliphatic amine (or aldehyde) using synthetic primers. The amine (or aldehyde) -attached DNA is synthesized into a double-stranded DNA through a polymerase chain reaction (PCR) process, and the aliphatic amine (or aldehyde) is dehydrated to provide a substrate on the surface of the glass plate. By binding to an aldehyde (or amine) group in the DNA, the DNA can be fixed to the slide glass. This process occurs while the DNA solution dries on the surface of the substrate.

Thereafter, the aldehyde (or amine) group remaining without reacting to the slide glass is removed to minimize the background fluorescence intensity.

The mathematical modeling of this content is as follows.

The volume V and surface area S when the DNA solution is added to the slide glass as a function of the radius r of the droplet are as follows.

(Equation 1)

Where K _V is the volume constant, K _S is the area constant, and t is the time.

At this time, assuming that the rate of decrease in volume due to evaporation of water is proportional to the surface area, this can be expressed as Equation 2 below.

(Equation 2)

Where k is the proportionality constant.

Then, the following equation (3) can be obtained from the above equations (1) and (2).

(Equation 3)

Where K _R is the radius constant and r ₀ is the radius of the droplet when t = 0.

Through Equation 3, the radius of the droplet decreases linearly as the DNA solution is dried.

On the other hand, if the radius of the droplet is r and the time is t, it is assumed that the amount of DNA P (r) adhered to the slide glass by the evaporation of moisture from the surface of the droplet is proportional to the concentration C (t) of the droplet. Equation 4 can be obtained.

(Equation 4)

Where K _C is the concentration constant.

Therefore, the concentration of DNA remaining in the droplets is expressed by Equation 5 below.

(Equation 5)

Therefore, a mathematical model representing the distribution of DNA in the spot on the slide glass as shown in Equation 6 can be derived from Equations 4 and 5 above.

(Equation 6)

Meanwhile, the random characteristic value generation module 30 generates physical characteristic values added in the hybridization process of the experimental group and the control mRNA, which is illustrated in FIG. 2.

As shown in FIG. 2, first, the mRNA taken from the samples of the experimental and control groups after the preparation of the microarray chip is competitively hybridized with the DNA library on the chip. That is, when the experimental group and the control group is m (m = 1, 2) and the serial number of the spot is n (n = 1, 2, ..., l), a _m is the total mRNA amount of the experimental group or the control group, θ _mn If the ratio of the nth gene to the total mRNA amount of the expressed gene, a _m θ _mn is the amount of probe (Probe) that can be hybridized to the n-th spot. If the target DNA amount corresponding to the n-th spot is d _n , a _m θ _mn d _n becomes the fluorescence intensity of the n-th spot after hybridization.

In the experiment, it is a rule to mix the same amount of mRNA of the experimental group and the control group, but in many cases, the exact amount is not mixed due to experimental errors. As a result, the relative gene expression in the experimental or control group appears to be higher than it actually is. Therefore, in order to correct this, normalization is required for image analysis. By properly adjusting the a _m value, the normalization performance of the image analysis system can be evaluated or a proper normalization method can be found.

Meanwhile, the final value to be obtained in the microarray image analysis is the ratio of gene expression of the experimental group to the control group, that is, θ _2n / θ _1n . However, since the image analysis system uses a method of indirectly confirming the expression ratio of genes as a ratio of fluorescence intensity, an error occurs in the actual value and the analysis result. Therefore, in the system of the present invention, θ _mn is generated using Gaussian White Noise and a random number. This is expressed as follows.

(Equation 7)

Where σ ₁ is the standard deviation of Gaussian white noise and σ ₂ is the random number of standard deviations. Using σ ₁ and σ _2, we can generate significant genes appropriately, and then evaluate the performance of the system by comparing them with the results analyzed by the image analysis system. It can help develop an accurate image analysis system.

d _n is the target DNA amount at which the mRNA of the experimental group and the control group is hybridized, which corresponds to the amount of DNA stuck to the spot of the microarray chip, and also the DNA concentration multiplied by the volume of the droplet before the DNA droplet is dried. do. Therefore, this can be expressed as

(Equation 8)

Meanwhile, the image conversion module 60 converts the 16-bit raw image by Cy3 and Cy5 into an 8-bit test image and an overlap image in order to increase the image processing speed and present it to the user at an appropriate point in time.

Usually, cDNA microarray chips are scanned twice with two different wavelengths of laser to detect Cy3 and Cy5 fluorescence bases, where the position of the chip in the two scanned images is likely to be inconsistent by a number of factors.

Accordingly, the image conversion module 60 generates an overlap image of the two images after performing an automated position correction process that matches the positions of the spots of the two images prior to the image processing.

Therefore, the edge detection module 70 performs a segmentation process of dividing each spot into segments in order to measure the expression level of a gene corresponding to each spot, and detects spot edges by detecting spot regions in each segment.

At this time, the segment coordinates of the spot are stored in an array form, and index information for each segment is input.

The spot template generation module 80 obtains the points on the contour and the center of the spot by using the spot edge template acquired by the edge detection module 70. After setting the new coordinates inside the spot, it is applied to the mathematical model generation module 40 to generate the spot template.

The spot template generation module 80 is shown in FIG. 3.

As shown in FIG. 3, the distance ζ _i from a point ξ _i , η _i on the edge of the spot to the center Cx, Cy of the spot is expressed by Equation 9 below.

(Equation 9)

Further, the coordinates (x _ij , y _ij ) of the pixels in the spot and the distance r _ij from the center of the spot to each pixel are as shown in Equation 10 below.

(Equation 10)

Based on the mathematical models of Equations 9, 10 and 6 above, a spot template representing the amount of DNA fixation for each pixel in the spot can be obtained as shown in Equation 11 below.

(Equation 11)

In addition, by substituting Equation 8 representing the mRNA hybridization target DNA amount of the experimental group and the control group in Equation 11 above, the gene fixation amount of the pixel in the nth spot can be obtained as in Equation 12 below.

(Equation 12)

The spot simulation image generation module 90 applies the random characteristic value generated by the random characteristic value generation module 30 to the spot template obtained by the spot template generation module 80 to determine the experimental group and the control group as shown in Equation 13 below. A spot simulation image representing the fluorescence intensity values of each spot is generated.

(Equation 13)

Meanwhile, the microarray simulation image generation module 100 generates a spot array image by adding location information to the spot simulation image generated from the spot template, and the background image forming module 20 generates the background fluorescence intensity b _m and the background noise b _m. 'To create a background image.

Here, the background fluorescence intensity b _m is used by using an average value of the local background of the actual image or generating an arbitrary value. In addition, the background noise b _m ′ is obtained by extracting only a portion of the fluorescence intensity of the image from which the spot region is removed from the actual image. The spot array image and the background image thus generated are added to generate a microarray simulation image.

The operation of the microarray simulation image generation system configured as described above will be described with reference to the accompanying drawings.

4 is a flowchart of a method of generating a microarray simulated image according to an embodiment of the present invention.

As shown in FIG. 4, first, a mathematical model representing a distribution of DNA in a spot on a slide glass is derived, and a random characteristic value, which is a physical characteristic value added during the hybridization of experimental and control mRNAs, is generated (S1).

In addition, raw images extracted by Cy3 and Cy5 having a 16-bit TIFF form are extracted from the hard disk 10 and stored in the image storage module 50 (S2).

The image conversion module 60 converts the two original images into 8-bit test images (S3).

The edge detection module 70 divides the spot into segments in the 8-bit test image to measure the expression level of the gene corresponding to each spot and stores the segment coordinates of each spot in an array form (S4).

Then, the spot area is detected in each segment to detect the edge of the spot (S5).

The spot template generation module 80 generates a spot template by applying the spot edge template obtained through the edge detection module 70 to a mathematical model (S6).

The spot simulation image generation module 90 generates a spot simulation image based on the spot template and the random characteristic value obtained above (S7).

The microarray simulation image generation module 100 generates a spot array image by adding location information to the spot simulation image (S8), and combines the background image and the spot array image generated by combining the background fluorescence intensity and the background noise. Finally, a microarray simulation image is generated (S9).

5 is a detailed image processing process of the method for generating a microarray simulation image according to an embodiment of the present invention.

As shown in FIG. 5, the background image generation module 20 detects background fluorescence intensity and background noise for the background image (S11-1).

The edge detection module 70 prepares the first and second templates of 8-bit spaces for the spot array image and the background image (S11-2 and S11-5). The segment coordinate data of the spot by the overlap image of the bit and segmentation is retrieved (S11-3, S11-4).

In addition, the mathematical model generation module 40 generates a mathematical model for the spot template (S11-6), and the random characteristic value generation module 30 generates a random characteristic value (S11-7).

The edge detection module 70 extracts the n-th spot segment using the segment coordinates of the spot and the 8-bit overlap image (S12).

A spot edge is generated from the spot segment extracted from the above (S13).

A spot template is obtained by obtaining coordinates within a spot from the spot edges above, and applying a mathematical model extracted from the above (S14), and generating a spot simulation image by applying random characteristic values thereto (S15).

When the spot simulation image is generated in this way, the spot simulation image including the location information is implanted into the first template prepared for the spot array image (S16-1), and the background image generation module 20 is mounted on the second template prepared for the background image. A background image is formed by implanting the background fluorescence intensity and the background noise obtained from) (S16-2).

Finally, the microarray simulation image generation module 80 generates a microarray simulation image by adding the background image and the spot array image (S17).

The drawings and detailed description of the invention are merely exemplary of the invention, which are used for the purpose of illustrating the invention only and are not intended to limit the scope of the invention as defined in the appended claims or claims.

Therefore, those skilled in the art will understand that various modifications and equivalent other embodiments are possible from this. Therefore, the true technical protection scope of the present invention will be defined by the technical spirit of the appended claims.

As described above, when analyzing the genetic information of the microarray chip according to the microarray simulation image generation system of the present invention, after generating the segment coordinates of the spot in the gene chip consisting of a spot group in the form of a two-dimensional array, each spot and the background edge Is detected and the index and data of each segment can be linked to provide useful information to the user.

In addition, the present invention can separate the exact region of the spot by reconstructing the image based on the template obtained from the edge detection of the actual microarray image, and can generate a simulated image close to the actual image, thereby effectively reducing the data error rate and effectively Only extract the effect.

In addition, the present invention can evaluate the accuracy of the analysis system by comparing the actual values of the simulated images with data values obtained through the microarray image analysis system.

Claims (11)

A mathematical model generation module for deriving a mathematical model of a gene distribution in a spot of a gene solution loaded on a slide glass; An image storage module for storing various image information including a raw image (Image) for a microarray chip composed of a gene set extracted from a sample of a test group and a control group tagged by fluorescent bases of different colors; An image conversion module for converting an original image of the microarray chip stored in the image storage module into a test image, constructing an overlap image from the test image, and storing each image in the image storage module; An edge detection module for detecting edges in the spot and the background area by separating the spot into segments to measure the expression level of a gene corresponding to each spot in the test image stored in the image storage module; A spot template generation module generating a spot template by applying the coordinates of a pixel in a spot set based on the spot edge template detected by the edge detection module to the mathematical model; Random characteristic value generation module for generating a random characteristic value indicating the fluorescence intensity of the spot after hybridization of the experimental group and the control mRNA; A spot simulation image generation module generating a spot simulation image by applying the random characteristic value to the spot template generated by the spot template generation module; And Microarray simulation image generation module for reconstructing the entire microarray image using the spot simulation image generated by the spot simulation image generation module Microarray simulation image generation system comprising a. The method of claim 1, And a mathematical model derived from the mathematical model generating module satisfies the following equation. Where P (r) is the gene distribution in the spot on the slide glass, C (0) is the initial droplet concentration, K _C is the concentration constant K _V is the volume constant, r ₀ is the radius of the initial droplet, r _t is the radius of the droplet when time t. The method of claim 1, The spot template generated by the spot template generating module satisfies the following equation. In the above formula, P _ij is a gene fixation amount of pixels (x _ij , y _ij ) in the spot, C (0) is the initial droplet concentration, K _C is the concentration constant K _V is the volume constant, ζ _i is the distance from the point on the edge of the spot (ξ _i , η _i ) to the center of the spot (C _x , C _y ), r _ij is the distance from the center of the spot to the pixels in the spot (x _ij , y _ij ). The method of claim 1, And a random characteristic value derived from the random characteristic value generation module satisfies the following equation. Wherein d _n is the target gene mass of the nth spot, C ₀ is the concentration of the initial droplet, K _V is the volume constant, ζ _i is the distance from the point on the edge of the spot (ξ _i , η _i ) to the center of the spot (C _x , C _y ). The method of claim 1, The spot simulation image generated by the spot simulation image generating module satisfies the following equation. In the formula S _mn is the fluorescence intensity value of the n-th spot of the experimental and control group, a _m is the total mRNA amount of the experimental group and the control group, θ _mn is the ratio of the n th gene of the total amount of mRNA expressed, d _n is the target gene mass of the nth spot, K _C is the concentration constant K _V is the volume constant, ζ _i is the distance from the point on the edge of the spot (ξ _i , η _i ) to the center of the spot (C _x , C _y ), r _ij is the distance from the center of the spot to the pixels in the spot (x _ij , y _ij ). The method of claim 1, And a background image generating module for generating a background image through the background fluorescence intensity and the background noise. The method of claim 6, And reconstructing the entire microarray image by combining the spot simulation image and the background image. A first step of deriving a mathematical model of a gene distribution in a spot of a gene solution loaded on a slide glass; A second step of storing various image information including a raw image (Image) for a microarray chip consisting of a set of genes extracted from a sample of a test group and a control group tagged with fluorescent bases of different colors; Converting the original image into a test image, constructing an overlap image from the test image, and storing each image in the image storage module; A fourth step of separating spots into segments in order to measure the expression level of a gene corresponding to each spot in the test image, and detecting spot edges by detecting spot regions from each segment; Generating a spot template by applying the detected spot edge template to a mathematical model; Generating a random characteristic value representing the fluorescence intensity of the spot after hybridization of the experimental group and the control mRNA; A seventh step of generating a spot simulation image by applying the random characteristic value to the spot template; And Eighth step of reconstructing the spot simulation image into a full microarray image Microarray simulation image generation method comprising a. The method of claim 8, The fifth step, Setting a new coordinate of a pixel in the spot by finding the center of the spot and the point on the edge of the spot; And Generating a spot template by applying a coordinate of a pixel in the spot to a mathematical model Microarray simulation image generation method comprising a. The method of claim 8, The sixth step, Obtaining a total mRNA amount of an experimental group or a control group; Obtaining a ratio occupied by the n th gene in the total mRNA amount of the expressed gene; obtaining a target gene amount corresponding to the nth spot; Obtaining an amount of the probe capable of hybridizing to the nth spot from the total mRNA amount and the ratio of the nth gene; And Obtaining fluorescence intensity of n-th spot after hybridization from the amount of probe and the amount of target DNA Microarray simulation image generation method comprising a. The method of claim 8, The eighth step, Generating a spot array image by combining location information with a spot simulation image; And Combining a background image with the spot array image to form a microarray simulation image Microarray simulation image generation method comprising a.