Electrophoretic data processing device and electrophoretic data processing method

Abstract

To improve the analytical accuracy of the electrophoresis apparatus (2), it includes: a signal charge data acquisition unit (101) that acquires the signal value output from the CCD image sensor when the signal of each wavelength component of the fluorescence based on the fluorescent marker is detected by multiple CCD image sensors and the pixel data after the signal is converted into an electrical signal is output; a merging processing unit (102) that merges a predetermined number of pixels into one bin; a color conversion processing unit (104) that calculates the signal intensity of each fluorescent marker based on the generated bin; a color signal evaluation processing unit (105) that calculates an evaluation value, i.e., a color signal evaluation value, representing the degree of deviation of the signal intensity of each fluorescent marker; and a merging region adjustment processing unit (107) that, when the color signal evaluation value is a predetermined value, performs bin adjustment by reducing the size of the bin corresponding to the peak value for the fluorescent marker with the largest value related to the peak value of the signal intensity, and performs bin adjustment by increasing the size of the bin corresponding to the peak value for the fluorescent marker with the smallest value related to the peak value of the signal intensity.

Description

Technical Field

[0001] This invention relates to the technology of electrophoresis data processing apparatus and electrophoresis data processing method. Background Technology

[0002] Capillary electrophoresis apparatus is known. Such an apparatus allows samples with multiple fluorescently labeled DNA to undergo electrophoresis inside a capillary. Excitation light is irradiated onto the detection area, and the fluorescence emitted by the sample is used as a signal for detection.

[0003] The fluorescence generated by the sample is dispersed along the wavelength direction and detected by a device that converts the optical signal into an electrical signal according to each wavelength region. Such devices include, for example, CCD (Charge Coupled Device) image sensors and CMOS (Complementary Metal-Oxide Semiconductor) image sensors.

[0004] When acquiring fluorescence signals, it is known that multiple light-receiving surfaces (corresponding to pixels) of an image sensor are simulated and processed as a single pixel, thereby increasing or decreasing the light-receiving area of ​​each pixel through binning.

[0005] Patent documents 1-3 disclose technologies related to such mergers.

[0006] Patent Document 1 discloses the following capillary array electrophoresis apparatus, fluorescence detection apparatus, and fluorescence signal intensity acquisition method: "A fluorescence detection apparatus 400 has multiple light-receiving surfaces that generate signal charges by being irradiated with a fluorescence signal 405. The fluorescence signal intensity is acquired based on the multiple signal charges generated on the light-receiving surfaces. The fluorescence detection apparatus 400 acquires the fluorescence signal intensity by performing either hardware merging or software merging. The hardware merging acquires the fluorescence signal intensity by simultaneously transforming multiple signal charges, while the software merging acquires the fluorescence signal intensity by successively transforming the signal charges into fluorescence signal intensities and adding the transformed fluorescence signal intensities" (see abstract).

[0007] Patent Document 2 discloses a fluorescence analysis apparatus and method as follows: "A fluorescence analysis apparatus 1A comprises an excitation light irradiation system for irradiating a sample S with excitation light, a fluorescence detection system for detecting fluorescence from a fluorescent probe located within a measurement area, a photon counting unit 35 for counting photons based on the detection signal, an analysis condition setting unit 51 for setting analysis conditions for photon count measurement data, and a measurement result analysis unit 52 for performing fluorescence analysis. The setting unit 51 sets the bin width for merging measurement data and the reference photon count for the fluorescent probe 1 molecule. The analysis unit 52 merges the measurement data and analyzes the number of fluorescent probes located within the measurement area by referring to the reference photon count. Furthermore, the setting unit 51 sets the bin width using the photon count SN ratio and the change caused by the bin width of the reference SN ratio based on shot noise characteristics" (see abstract).

[0008] Patent document 3 discloses the following fluorescence observation device: "A fluorescence observation device 100 is provided, comprising: a fluorescence image acquisition unit 18 and a reference image acquisition unit 17 for acquiring a fluorescence image of a subject A or a reference image; a phase-division image generation unit 64 for generating a phase-division image by dividing an image based on a fluorescence image by an image based on a reference image; a display unit 20 for displaying a final fluorescence image based on the phase-division image; a correction processing unit 65 for performing correction processing on at least one of the reference image and the fluorescence image and / or the phase-division image before generating the phase-division image based on the phase-division image generation unit 64 or displaying the final fluorescence image based on the display unit 20; an observation condition determination unit 7 for determining the observation conditions of the subject A; and a correction condition setting unit 66 for setting the parameters involved in the correction processing of the correction processing unit 65 according to the observation conditions determined by the observation condition determination unit 7 (see abstract).

[0009] The combination of multiple merge regions applied during merging is called a merge pattern.

[0010] Existing technical documents

[0011] Patent documents

[0012] Patent Document 1: Japanese Patent Application Publication No. 2015-49179

[0013] Patent Document 2: Japanese Patent Application Publication No. 2009-192490

[0014] Patent Document 3: Japanese Patent Application Publication No. 2013-56001 Summary of the Invention

[0015] The problem that the invention aims to solve

[0016] According to the technology described in Patent Document 1, it is possible to increase the data acquisition speed and reduce the size of the acquired data. If the sole purpose is to reduce the data size, this can be easily achieved by fixing the area to be merged and merging at equal intervals. Furthermore, as described in Patent Documents 2 and 3, the S / N ratio can also be improved by changing the area where the fluorescence signals are merged. However, in adjusting the merging area with the goal of improving the S / N ratio, there is a possibility that the fluorescence sensitivity of each marker may deviate depending on the wavelength characteristics of the fluorescent marker.

[0017] In electrophoresis apparatus, fluorescence from multiple fluorescent labels needs to be detected and analyzed simultaneously. Therefore, if the deviation in fluorescence sensitivity is not suppressed, the analytical performance cannot be met.

[0018] When suppressing bias, it is necessary to adjust the merging pattern to best suit the group of fluorescent markers used. However, this adjustment requires highly skilled operators and involves time and expense.

[0019] The present invention was completed in view of this background, and the objective of the present invention is to improve the analytical accuracy of the electrophoresis apparatus.

[0020] Methods for solving problems

[0021] To address the aforementioned issues, the present invention provides an electrophoresis apparatus comprising: an acquisition unit that acquires pixel data output from each of the imaging elements when the apparatus, which uses multiple imaging elements to detect signals of each wavelength component of fluorescence based on the fluorescent markers and outputs pixel data that converts the signals into electrical signals; a binning generation unit that calculates a cumulative or representative value of a predetermined number of adjacent pixel data, sets the calculated cumulative or representative value as a binning value, thereby summing a predetermined number of adjacent pixel data into one bin; and a binning value extraction unit that extracts values ​​derived from the fluorescence of the fluorescent markers for each of the fluorescent markers. The set of binning values ​​for the fluorescent markers; a signal strength calculation unit that calculates the signal strength of each fluorescent marker based on the extracted set of binning values; a first evaluation value calculation unit that calculates an evaluation value, i.e., a first evaluation value, for each fluorescent marker representing the degree of deviation of the signal strength; and an adjustment unit that, when the first evaluation value meets a predetermined condition, performs binning adjustment by reducing the size of the bin with the largest binning value in the set of binning values, i.e., the maximum binning value, for the fluorescent marker with the smallest value related to the first peak, and performs binning adjustment by increasing the size of the bin with the maximum binning value, for the fluorescent marker with the smallest value related to the first peak.

[0022] Other solutions will be appropriately described in the implementation plan.

[0023] Invention Effects

[0024] According to the present invention, the analytical accuracy of the electrophoresis apparatus can be improved. Attached Figure Description

[0025] Figure 1 This is a diagram showing a structural example of the electrophoresis system according to the first embodiment.

[0026] Figure 2 This is a diagram showing the hardware structure of the electrophoresis data processing device.

[0027] Figure 3A This is a diagram (one of) illustrating an example of binning used in this embodiment.

[0028] Figure 3B This is a diagram (the second one) illustrating an example of merging used in this embodiment.

[0029] Figure 4A This is a diagram illustrating an example of the relationship between binning and wavelength.

[0030] Figure 4B This is a diagram illustrating an example of the accumulated value of a signal charge.

[0031] Figure 5 This is a flowchart illustrating an example of electrophoretic data processing in the first embodiment.

[0032] Figure 6 This is a flowchart showing the order of the merging processes performed in the first embodiment.

[0033] Figure 7 This is a flowchart showing the sequence of color transformation matrix calculation processes performed in the first embodiment.

[0034] Figure 8 This is a diagram representing an example of accumulated signal charge data.

[0035] Figure 9 This is a diagram showing an example of the standardized cumulative charge value of a signal.

[0036] Figure 10 This is a flowchart showing the sequence of color transformation processes performed in the first embodiment.

[0037] Figure 11 This is a diagram representing an example of fluorescence color signal data.

[0038] Figure 12 This is a flowchart showing the sequence of fluorescence color signal evaluation value calculation processing performed in the first embodiment.

[0039] Figure 13 This is a graph representing an example of the average signal strength.

[0040] Figure 14 This is a flowchart showing the processing order of the merged region adjustment process.

[0041] Figure 15A This is an example of a menu screen (one of the examples).

[0042] Figure 15B This is an example of a dialog box screen.

[0043] Figure 15C This is an example of a menu screen (one of the examples).

[0044] Figure 15D This is an example of a screen displaying fluorescence sensitivity adjustment.

[0045] Figure 16 This is a diagram showing an example of fluorescence color signal data representing the result after the sensitivity adjustment process of the first embodiment is completed.

[0046] Figure 17 This is a diagram showing a structural example of the electrophoresis system according to the second embodiment.

[0047] Figure 18 This is a flowchart illustrating an example of electrophoretic data processing performed in the second embodiment.

[0048] Figure 19 This is a diagram showing a structural example of the electrophoresis system according to the third embodiment.

[0049] Figure 20 This is a flowchart illustrating an example of electrophoretic data processing performed in the third embodiment.

[0050] Figure 21 This is a diagram showing an example of fluorescent color signal data that has been pulled up. Detailed Implementation

[0051] Hereinafter, embodiments of the present invention (referred to as "embodiments") will be described in detail with reference to the accompanying drawings. Furthermore, in all the drawings used to illustrate the embodiments, the same symbols are used to label the same elements, and repeated descriptions are omitted.

[0052] <First Embodiment>

[0053] First, refer to Figures 1 to 15D The first embodiment of the present invention will be described.

[0054] [Electrophoresis System Z]

[0055] Figure 1This is a diagram showing a structural example of the electrophoresis system Z according to the first embodiment.

[0056] The electrophoresis system Z includes an electrophoresis data processing device 1 and an electrophoresis device 2.

[0057] (Electrophoresis apparatus 2)

[0058] Electrophoresis apparatus 2 performs electrophoresis on a biological sample, irradiates a fluorescent label in the sample with excitation light, generates fluorescence from the sample, and detects the fluorescence signal. That is, electrophoresis apparatus 2 is equipped with an electrophoresis device 2 that moves the sample and multiple fluorescent labels. Furthermore, in this embodiment, the sample to be measured in electrophoresis apparatus 2 is a DNA molecule endowed with multiple fluorescent labels. These DNA molecules are fluorescently labeled with base information (“ATGC”) and characteristic sequence structures (e.g., the continuity of “T”). As electrophoresis apparatus 2, a capillary electrophoresis device or the like is used.

[0059] Furthermore, the electrophoresis apparatus 2 includes a wavelength dispersion section 201, a signal charge acquisition section 202, and a signal charge data output section 203.

[0060] The wavelength dispersion section 201 is, for example, a diffraction grating that disperses fluorescence generated by a fluorescent marker in the wavelength direction.

[0061] The signal charge acquisition unit 202 detects the fluorescence signal (fluorescence detection) dispersed in the wavelength direction by the wavelength dispersion unit 201 and converts it into an electrical signal. That is, it detects the signal of the wavelength component of the fluorescence generated by the fluorescent label dispersed by the wavelength dispersion unit 201. The signal charge acquisition unit 202 is configured, for example, a CCD image sensor or a CMOS image sensor (imaging element). In this embodiment, the signal charge acquisition unit 202 is configured as a CCD image sensor. Furthermore, the fluorescence detection of the signal charge acquisition unit 202 is performed arbitrarily in a time sequence as the electrophoresis time elapses. That is, fluorescence detection is performed multiple times at predetermined time intervals during electrophoresis. One embodiment of fluorescence detection is defined as one scan.

[0062] The signal charge data output unit 203 outputs the pixel data (signal charge data) output from the CCD image sensor (imaging element) constituting the signal charge acquisition unit 202 to the electrophoretic data processing device 1.

[0063] (Electrophoresis data processing device 1)

[0064] The electrophoresis data processing device 1 uses the signal charge data for each time series received from the electrophoresis device 2 to output a merge pattern optimized for the fluorescent marker to be used. That is, the electrophoresis data processing device 1 determines whether the default (pre-set) merge pattern is optimal; if not, it corrects the merge pattern. Alternatively, if the merge pattern is optimal, the electrophoresis data processing device 1 outputs that merge pattern.

[0065] Furthermore, the electrophoresis data processing device 1 includes a signal charge data acquisition unit 101, a merging processing unit 102, a color transformation matrix calculation processing unit 103, a color transformation processing unit 104, a color signal evaluation processing unit 105, a judgment processing unit 106, a merging area adjustment processing unit 107, a merging pattern output unit 108, and an input / output processing unit 109.

[0066] The signal charge data acquisition unit 101 (acquisition unit) receives the signal charge data output by the electrophoresis apparatus 2. That is, it acquires the pixel data, i.e., the signal charge data, output by the CCD image sensor (image capture device) of the electrophoresis apparatus 2 from each CCD image sensor (image capture device).

[0067] The binning processing unit 102 (bin generation unit) performs binning processing. At this time, the binning processing unit 102 divides the acquired signal charge data into bins 400 (see reference 400) according to a binning pattern (e.g., a preset default binning pattern). Figures 3A to 4A For each sub-bin, a cumulative signal value of 400 is generated, and the output is the cumulative signal charge data (sub-bin value). Alternatively, representative value conversion can be performed instead of accumulation. Representative value conversion will be discussed later.

[0068] In addition, regarding the 400-unit sub-box (refer to...) Figure 3A (As will be described later), the values ​​(signal values) of a predetermined number of adjacent pixel data are aggregated into a bin 400. Furthermore, the merging pattern is a pattern related to the aggregation method of the pixel data in the bin 400. The merging pattern and the processing performed by the merging processing unit 102 will be described later.

[0069] In this way, the merging processing unit 102 calculates the cumulative or representative value of the values ​​of a predetermined number of adjacent pixel data, and sets the calculated cumulative or representative value as the binning value, thereby summarizing a predetermined number of adjacent pixel data into one bin.

[0070] The color transformation matrix calculation and processing unit 103 (bin value extraction unit) generates and outputs a color transformation matrix "C" based on the signal charge accumulation data output from the merging processing unit 102. The processing performed by the color transformation matrix calculation and processing unit 103 will be described later. In this embodiment, "color" refers to the fluorescence color based on the fluorescent marker. The color transformation matrix calculation and processing unit 103 extracts F (signal charge accumulation data) from the fluorescent marker for each fluorescent marker by calculating the color transformation matrix "C".

[0071] The color conversion processing unit 104 (signal strength calculation unit) calculates the signal components originating from the fluorescent markers based on the signal charge accumulation data output by the merging processing unit 102 and the color conversion matrix "C" output by the color conversion matrix calculation processing unit 103. The signal components originating from the fluorescent markers are composed of the signal intensities of each fluorescent marker (details will be described later). Then, the color conversion processing unit 104 outputs the calculated signal components originating from the fluorescent markers (the signal intensities of each fluorescent marker) as fluorescent color signal data. In this way, the color conversion processing unit 104 calculates the signal intensity of each fluorescent marker based on the extracted set of binning values ​​(signal charge accumulation data). The processing performed by the color conversion processing unit 104 will be described later.

[0072] The color signal evaluation processing unit 105 calculates a fluorescence color signal evaluation value (first evaluation value) based on the fluorescence color signal data output by the color conversion processing unit 104. The fluorescence color signal evaluation value indicates the degree of deviation in the signal intensity of each fluorescent marker. Specifically, the color signal evaluation processing unit 105 determines whether the fluorescence color signal evaluation value is less than a predetermined threshold. Therefore, the color signal evaluation processing unit 105 determines whether the degree of deviation in the signal intensity of each fluorescent marker is less than the predetermined threshold. That is, the color signal evaluation processing unit 105 determines whether the deviation in the signal intensity of each fluorescent marker is suppressed. Then, if the fluorescence color signal evaluation value is less than the predetermined threshold (the predetermined condition is met), since the change in the signal intensity of each fluorescent marker is suppressed, the color signal evaluation processing unit 105 determines that the current merged pattern is optimal. Conversely, if the fluorescence color signal evaluation value is above the predetermined threshold (the predetermined condition is not met), since the deviation in the signal intensity of each fluorescent marker is not suppressed, the color signal evaluation processing unit 105 determines that the merged pattern needs to be corrected. Thus, the fluorescence color signal evaluation value, indicating the degree of deviation in the signal intensity of each fluorescent marker, is an evaluation value used to determine whether the current merged pattern is optimal.

[0073] Furthermore, the processing performed by the color signal evaluation processing unit 105 will be described later.

[0074] The determination processing unit 106 determines whether the fluorescence color signal evaluation value calculated by the color signal evaluation processing unit 105 is above or below a threshold. Based on this, the determination processing unit 106 determines whether the current merged pattern is optimal. The processing performed by the determination processing unit 106 will be described later.

[0075] When the determination processing unit 106 determines that the fluorescence color signal evaluation value is less than a threshold, meaning that the current merged pattern is not optimal, the merged area adjustment processing unit 107 adjusts the merged pattern. The processing performed by the merged area adjustment processing unit 107 will be described later.

[0076] If the determination and processing unit 106 determines that the fluorescence color signal evaluation value is above the threshold, that is, the current merged pattern is the best, the merged pattern output unit 108 outputs the current merged pattern to the outside.

[0077] Input / output processing unit 109 to display device 115 (see reference) Figure 2 Output Figures 15A to 15D The following are screens 600, 610, and 620. Additionally, the input / output processing unit 109 receives data via input device 114 (see reference 114). Figure 2 The information input. In addition, the processing of each section 101 to 108 begins upon the instruction of the input / output processing unit 109.

[0078] [Hardware Structure]

[0079] Figure 2 This is a diagram showing the hardware structure of the electrophoresis data processing device 1.

[0080] The electrophoresis data processing apparatus 1 includes a memory 111, a CPU (Central Processing Unit) 112, and a storage device 113 such as an HD (Hard Disk). Additionally, the electrophoresis data processing apparatus 1 includes an input device 114 such as a keyboard and mouse, a display device 115 such as a monitor, and a communication device 116. The communication device 116 acquires data from the electrophoresis apparatus 2.

[0081] The program stored in storage device 113 is loaded into memory 111. Then, the loaded program is executed by CPU 112. This is how the specific implementation is achieved. Figure 1 The sections shown are 101 to 108.

[0082] In addition, Figure 1 In the example shown, each part 101-108 is independent, but it can also be composed of one or more constituent elements as needed. For example, each part 101-108 can also be configured to be processed by one or more central processing units (CPU 112). That is, in Figure 1In the example shown, the electrophoresis data processing apparatus 1 has all of the sections 101 to 108, but multiple structures may be provided in a device other than the electrophoresis data processing apparatus 1. For example, the electrophoresis apparatus 2 may have a merging processing section 102, or the color transformation matrix calculation processing section 103 may be provided in a device different from the electrophoresis data processing apparatus 1.

[0083] [merge]

[0084] Figure 3A as well as Figure 3B This is a diagram illustrating an example of binning used in this implementation.

[0085] Figure 3A The diagram shows 3×6 CCD pixels 301. Additionally, in... Figure 3A In the diagram, the values ​​shown inside each CCD pixel 301 are the signal values ​​detected by each CCD pixel 301 (values ​​possessed by pixel data).

[0086] In fluorescence detection using a CCD image sensor, a method known as merging is employed: a predetermined number of adjacent CCD pixels 301 are processed as a single bin 400 (pixel data is grouped into one bin) to increase the light-receiving area of ​​each pixel. During merging, the areas of the bins 400 to be merged within the CCD pixels 301 are predetermined. The combination (grouping method) of CCD pixels 301 within each bin 400 applied during merging is called a merging pattern.

[0087] exist Figure 3A In the example shown, the section indicated by the slash is compartment 400. For example... Figure 3A As shown, each sub-box 400 is composed of multiple CCD pixels 301.

[0088] For example, such as Figure 3A As shown, the left-side sub-bin 401 is composed of 3 CCD pixels 301, the central sub-bin 402 is composed of 6 CCD pixels 301, and the right-side sub-bin 403 is composed of 3 CCD pixels 301.

[0089] like Figure 3A As shown in the example, the number of CCD pixels 301 contained in each bin 400 can also be different. Furthermore, as... Figure 3A As shown in CCD pixel 301a, there may be CCD pixels 301 that are not included in the bin 400.

[0090] Figure 3B This is a graph representing the cumulative signal charge values ​​in each of the 400 sub-boxes.

[0091] exist Figure 3BIn the middle, compartments 401 to 403 are equivalent to Figure 3A The shown compartments 401 to 403 are compartments 400. Additionally, in... Figure 3B In the diagram, the values ​​shown in bins 401 to 403 represent the cumulative signal charge value (bin value) in bin 400. The cumulative signal charge value in bins 401 to 403 is the cumulative value of the signal values ​​(values ​​possessed by pixel data) output by the CCD pixels 301 constituting bin 400.

[0092] Such bins 400 are generated by the merging processing unit 102. That is, the merging processing unit 102 aggregates the signal values ​​of a predetermined number of adjacent CCD pixels 301 (aggregates the data of a predetermined number of adjacent pixels) and uses them as one bin 400.

[0093] For example, Figure 3B The signal charge accumulation value (“30”) in the shown compartment 401 is the constituent of Figure 3A The cumulative signal values ​​("9", "11", "10") of each CCD pixel 301 in the shown bin 401 are calculated. The same applies to bins 402 and 403. Thus, the cumulative signal charge value is the cumulative value of the values ​​(signal values) possessed by the pixel data in each bin 400.

[0094] In this way, a predetermined number of adjacent CCD pixels 301 (pixel data) output from imaging elements such as CCD image sensors are aggregated into one bin 400.

[0095] [Relationship between 400-cell binning and wavelength]

[0096] Figure 4A This is a graph showing the relationship between the 400° cell and the wavelength. Refer to the relevant documentation for further information. Figure 1 .

[0097] As described above, the fluorescence after wavelength dispersion in the electrophoresis apparatus 200 is detected by the CCD pixel 301 constituting the signal charge acquisition unit 202.

[0098] exist Figure 4A In the figure, graph G1 shows the wavelength spectrum of the fluorescence after wavelength dispersion by electrophoresis apparatus 200. Furthermore, in graph G1, the horizontal axis represents wavelength, and the vertical axis represents fluorescence intensity.

[0099] like Figure 4A As shown, a CCD pixel 301 (i.e., a CCD image sensor) is arranged in the wavelength direction in the signal charge acquisition unit 202.

[0100] That is, in this embodiment, the signal value detected by each CCD pixel 301 is equivalent to the fluorescence intensity in the wavelength direction.

[0101] In addition, Figure 4A In the example shown, each bin 400 is composed of three CCD pixels 301. Incidentally, the values ​​recorded in each CCD pixel 301 are the signal values ​​output by that CCD pixel 301. For example... Figure 4A As shown, multiple CCD image sensors (imaging elements) detect the signal of each wavelength component of fluorescence based on fluorescent labels, thereby outputting pixel data that converts the signal into an electrical signal.

[0102] In addition, Figure 4A The example shown illustrates a case where the signal charge acquisition unit 202 can acquire a wavelength region of 500nm to 700nm. Furthermore, the CCD pixel 301 is configured to allocate a wavelength region of 10nm to each bin 400. That is, bin 411 is allocated a wavelength of 500 to 510nm, bin 412 is allocated a wavelength of 510 to 520nm, ..., and bin 430 is allocated a wavelength of 690 to 700nm. This illustrates an example of a merged pattern where the wavelength region of 500nm to 700nm is divided by 20 bins 400. Additionally, the symbol 500 represents bin numbers 1 to 20. Each bin number is a unique number assigned to bins 411 to 430. Of course, in a merged pattern, as... Figure 4A As shown, the number of sub-divisions 400 does not need to be limited to 20. Furthermore, the wavelength acquired by the signal charge acquisition unit 202 may not be the entire wavelength range (in...). Figure 4A In the example, it is 500-700nm).

[0103] Figure 4B It means Figure 4A A diagram showing an example of the cumulative signal charge value (bin value) in the shown bin 400.

[0104] Figure 4B The compartments 411 to 430 shown are equivalent to Figure 4A The shown compartments are 411 to 430. Furthermore, the values ​​displayed inside compartments 411 to 430 represent the accumulated signal charge values ​​for each of compartments 411 to 430. And, in Figure 4B In the middle, the values ​​shown inside each of the sub-compartments 411 to 430 become the values ​​in Figure 4A The sum of the cumulative signal charge values ​​(cumulative value) output by the CCD pixels 301 that constitute the sub-boxes 411 to 430 respectively.

[0105] [Overall Processing]

[0106] Figure 5 This is a flowchart illustrating an example of electrophoretic data processing in the first embodiment.

[0107] Appropriate reference Figure 1 and Figure 2 .

[0108] First, the input / output processing unit 109 performs screen display processing (S0) to display a screen on the display device 115. Regarding the screen displayed in step S0, Figures 15A to 15D This will be discussed later.

[0109] When the input / output processing unit 109 indicates the start of processing, the signal charge data acquisition unit 101 acquires signal charge data from the electrophoresis apparatus 2 (S1). The signal charge data is data (pixel data) output from the signal charge data output unit 203 of the electrophoresis apparatus 2. Specifically, it is... Figure 3A , Figure 4B The signal value (the value possessed by the pixel data) shown by the CCD pixel 301. That is, the signal charge data acquisition unit 101 (acquisition unit) acquires the CCD pixel 301 (pixel data) output from each CCD image sensor (imaging element).

[0110] Next, the merging processing unit 102 performs merging processing (S2). Step S2 will be explained later.

[0111] Then, the color transformation matrix calculation and processing unit 103 performs color transformation matrix calculation and processing (S3). Step S3 will be explained later.

[0112] Next, the color conversion processing unit 104 performs color conversion processing (S4). Step S4 will be explained later.

[0113] Furthermore, the color signal evaluation processing unit 105 performs color signal evaluation processing (S5). Step S5 will be described later. In step S5, the color signal evaluation processing unit 105 calculates the fluorescence color signal evaluation value.

[0114] Then, the determination processing unit 106 determines whether the fluorescence color signal evaluation value calculated by the color signal evaluation processing unit 15 meets the predetermined conditions (S6). Step S6 will be explained later.

[0115] If the fluorescence color signal evaluation value does not meet the predetermined conditions (S6→No), the merging region adjustment processing unit 107 performs merging adjustment processing (S7). Afterwards, the electrophoresis data processing apparatus 1 returns the processing to step S2. The processing of step S7 will be described later.

[0116] When the fluorescence color signal evaluation value meets the predetermined conditions (S6→Yes), the merged pattern output unit 108 outputs the merged pattern.

[0117] The following is about Figure 5 Each of the processes shown is explained in detail.

[0118] [Merge Processing]

[0119] Figure 6 This is a flowchart showing the order of the merging processes performed in the first embodiment. Figure 6 The process shown is the merging processing unit 102 (see reference). Figure 1 The processing performed indicates Figure 5 The detailed sequence of steps S2.

[0120] like Figure 1 The merging processing unit 102 performs merging processing on the signal charge data and outputs the cumulative signal charge data.

[0121] Additionally, please refer to the following explanations as appropriate. Figures 1 to 4B .

[0122] First, the merging processing unit 102 determines the data stored in the storage device 113 (see [link]). Figure 2 The merging pattern in the image divides the signal charge data in the wavelength direction to set up bin 400 (S201). That is, the merging processing unit 102 merges a predetermined number of adjacent CCD pixels 301 based on a preset default merging pattern (merging pixel data into one bin 400). For example, as Figure 4A As shown, the merging processing unit 102 groups multiple CCD pixels 301 into bins 400 based on a default merging pattern. Furthermore, in the merging pattern initially applied by the merging processing unit 102, the size of the segmented regions is not limited. For example, the CCD pixels 301 can be segmented one by one, and the segmentation interval can be variable. However, a default merging pattern can be set, allowing the number of CCD pixels 301 constituting the bins 400 to be adjusted through the merging adjustment process described later.

[0123] Next, the merging processing unit 102 accumulates or represents the signal values ​​of the CCD pixels 301 that constitute the bins 400 divided in step S201 of setting the bins 400 (S202). As a method of representation, there are calculations of average value, median value, maximum value, minimum value, etc.

[0124] For example, when calculating the average value, the merging processing unit 102 calculates the average value for the signal values ​​of the CCD pixels 301 constituting each sub-bin 400. Furthermore, when calculating the median value, the merging processing unit 102 calculates the median value for the signal values ​​of the CCD pixels 301 constituting each sub-bin 400. Moreover, when calculating the maximum and minimum values, the merging processing unit 102 calculates the maximum and minimum values ​​of the signal values ​​of the CCD pixels 301 constituting each sub-bin 400.

[0125] In Figure 3, Figure 4AIn the example shown, the signal values ​​of the CCD pixels 301 constituting each bin 400 are the same, but in reality, deviations occur. In this case, the merging processing unit 102 can calculate the average, center value, maximum value, or minimum value of the CCD pixels 301 constituting each bin 400. The user can decide whether to perform accumulation or representation in each bin 400.

[0126] Furthermore, the processing in step S202 is equivalent to Figure 4B The processing is shown. Additionally... Figure 4A and Figure 4B The example shown is one in which accumulation was performed in step S202 (e.g.) Figure 4B That's right Figure 4A (The signal value is accumulated). In this embodiment, the accumulation is performed in step S202.

[0127] In this way, the merging processing unit 102 calculates the cumulative or representative value of the signal values ​​(values ​​possessed by pixel data) of a predetermined number of adjacent CCD pixels 301, and sets the calculated cumulative or representative value as the bin value (signal charge cumulative value in this embodiment), thereby summing the predetermined number of adjacent pixel data into one bin. Furthermore, in this embodiment, the merging processing unit 102 calculates the signal charge cumulative value as the cumulative value of the signal values ​​(values ​​possessed by pixel data) of the CCD pixels 301 for each bin 400.

[0128] Then, the merging processing unit 102 outputs the accumulated (or representative) signal charge value accumulated in step S202 as signal charge accumulation data to the color transformation matrix calculation processing unit 103 and the color transformation processing unit 104 (S203).

[0129] Then, the electrophoresis data processing device 1 returns the processing to... Figure 5 Step S3.

[0130] [Color Transformation Matrix Calculation and Processing]

[0131] Figure 7 This is a flowchart showing the sequence of color transformation matrix calculation processes performed in the first embodiment. Figure 7 The process shown is Figure 1 The processing performed by the color transformation matrix calculation and processing unit 103 (binning value extraction unit) indicates... Figure 5 The detailed sequence of steps S3. Additionally, Figure 7 For a specific example of the processing shown, please refer to [reference needed]. Figure 8 and Figure 9 To be described later.

[0132] In the color transformation matrix calculation process, the color transformation matrix calculation processing unit 103, as shown in... Figure 1 As described above, the color transformation matrix "C" is calculated based on the accumulated signal charge data. The color transformation matrix "C" is calculated from the accumulated signal charge data with peaks, consisting only of specific fluorescent markers. The color transformation matrix "C" will be discussed later.

[0133] First, the color transformation matrix calculation and processing unit 103 extracts the position of the fluorescent marker-specific peak (second peak) within the signal charge accumulation data (S301). In other words, the color transformation matrix calculation and processing unit 103 extracts the fluorescent marker-specific peak (second peak) within the signal charge accumulation data. That is, the color transformation matrix calculation and processing unit 103 extracts the fluorescent marker-specific peak (the peak corresponding to the fluorescent marker, i.e., the second peak) from the time series of the signal charge accumulation value.

[0134] Next, the color transformation matrix calculation and processing unit 103 obtains the cumulative signal charge value of each CCD segmentation region (division 400) constituting the peak (S302). That is, for each peak (second peak) unique to the fluorescent marker, the color transformation matrix calculation and processing unit 103 extracts the cumulative signal charge value of the peak (second peak) constituting the fluorescent marker.

[0135] Next, the color transformation matrix calculation and processing unit 103 normalizes the accumulated signal charge values ​​of each wavelength component (S303). The order of normalization will be described later.

[0136] Then, the color transformation matrix calculation and processing unit 103 determines whether the processing steps S301 to S303 have been completed for all fluorescent labels (S304).

[0137] If steps S301 to S303 are not completed for all fluorescent labels (S304 → No), the color transformation matrix calculation processing unit 103 returns the processing to step S301. Then, the color transformation matrix calculation processing unit 103 performs steps S301 to S303 on the fluorescent labels that were not processed by steps S301 to S303.

[0138] On the other hand, after processing steps S301 to S303 on all fluorescent labels (S304 → Yes), the color transformation matrix calculation and processing unit 103 generates a matrix of the number of fluorescent labels × the number of bins after normalization of each wavelength component (S305).

[0139] Then, the color transformation matrix calculation processing unit 103 outputs the matrix generated in step S305 as the color transformation matrix C to the color transformation processing unit 104 (S306).

[0140] Then, the electrophoresis data processing device 1 returns the processing to... Figure 5 Step S4.

[0141] Figure 8 This is a graph representing an example of accumulated signal charge data. That is, in Figure 8 The image shows an example of signal charge accumulation data obtained by the color transformation matrix calculation processing unit 103 from the merging processing unit 102.

[0142] exist Figure 8 In the diagram, the horizontal axis represents the time elapsed during electrophoresis (actually, the number of scans). The vertical axis represents the cumulative signal charge. That is, as shown... Figure 8 As shown, the signal charge accumulation data is a time series of the signal charge accumulation value.

[0143] in addition, Figure 8 The peak values ​​501–504 shown represent the peak values ​​corresponding to each fluorescent label. In this embodiment, as... Figure 8 As shown, four fluorescent markers are used. These four fluorescent markers are appropriately designated as a first fluorescent marker, a second fluorescent marker, a third fluorescent marker, and a fourth fluorescent marker. The first fluorescent marker corresponds to peak value 501, and the second fluorescent marker corresponds to peak value 502. Similarly, the third fluorescent marker corresponds to peak value 503, and the fourth fluorescent marker corresponds to peak value 504. Peak values ​​501 to 504 correspond to the aforementioned second peak value. Thus, the color transformation matrix calculation and processing unit 103 extracts the peak values ​​corresponding to the fluorescent markers, namely peak values ​​501 to 504 (the second peak value), from the time series of the accumulated signal charge value.

[0144] In addition, Figure 8 In the diagram, the multiple lines shown in peak values ​​501 to 504 represent the cumulative signal charge values ​​in each bin 400. Thus, peak values ​​501 to 504 are obtained by extracting the cumulative signal charge values ​​(bin values) from the fluorescent markers for each fluorescent marker.

[0145] For example, such as Figure 8 As shown, when using signal charge accumulation data containing four fluorescent markers, the color transformation matrix calculation processing unit 103 extracts the signal charge accumulation values ​​(signal charge accumulation values ​​constituting the second peak value) of 20 bins 400 for each of the peaks 501 to 504 constituting the fluorescent markers. That is, the color transformation matrix calculation processing unit 103 extracts the signal charge accumulation values ​​constituting peaks 501 to 504 (second peak value) for each peak 501 to 504 (second peak value). Furthermore, this processing is equivalent to... Figure 7 Step S302. Furthermore, the detection peak value is 501–504. Figure 7 Step S301.

[0146] Next, the color transformation matrix calculation processing unit 103 normalizes the signal charge accumulation value to [0, 1] by dividing the accumulated signal charge value of each of the 20 sub-bins 400 by the maximum value of the accumulated signal charge value. Normalization is performed on each peak value 501 to 504. Furthermore, this processing is equivalent to... Figure 7 Step S303.

[0147] The color transformation matrix calculation and processing unit 103 performs peak value extraction and normalization on the four fluorescent labels respectively, from 501 to 504. Figure 7 Step S304). As a result, the color transformation matrix calculation and processing unit 103 extracts a set of signal charge accumulation values ​​(bin values) from each fluorescent marker.

[0148] Figure 9 This represents the results of peak extraction and normalization performed on the four fluorescent labels respectively.

[0149] Figure 9 The spectrum 511–514 is shown, plotted with wavelength components (bin number) on the horizontal axis and the normalized cumulative signal charge value on the vertical axis. Spectra 511–514 correspond to four fluorescent markers. The color transformation matrix calculation and processing unit 103 calculates the number of fluorescent markers (in…) Figure 9 In the example shown, a 4×20 matrix consisting of 4 components ("4") and the number of bins in the wavelength direction ("20" in this embodiment) is used as the color transformation matrix "C" (transformation matrix) to generate (calculate). Figure 9 The spectrum shown is 511-514 (equivalent to Figure 7 (Steps S305 and S306 in the process). The color transformation matrix calculation and processing unit 103 stores the generated color transformation matrix "C" in the storage unit. That is, the color transformation matrix "C" is a matrix that has a cumulative signal charge value as the value of each component, with each extracted peak 501 to 504 (second peak) as the row component and the bins 400 as the column component. In addition, in this embodiment, the matrix is ​​represented by an uppercase letter in parentheses, as in "C" (where the parentheses are removed in the calculation formula). The spectra 511 to 514 are respectively the spectra obtained by extracting the cumulative signal charge values ​​(bin values) from the fluorescent markers for each fluorescent marker.

[0150] [Color Transformation Processing]

[0151] Next, the color transformation processing of the color transformation processing unit 104 (signal strength calculation unit) will be explained.

[0152] Color conversion processing unit 104 is used in Figure 7The color transformation matrix "C" calculated in the processing shown transforms the cumulative signal charge data into fluorescent color signal data derived from each fluorescent label contained in the sample.

[0153] Specifically, the color conversion processing unit 104 generates fluorescence color signal data using the following method.

[0154] Additionally, the signal charge accumulation matrix is ​​set to "F" (a matrix of scan number × bin number). The signal charge accumulation matrix "F" is... Figure 8 The signal charge accumulation data shown is obtained by setting it as a matrix of scan number × bin number. That is, the signal charge accumulation matrix "F" is a matrix that sets the scan number of the time series of signal charge accumulation values ​​as the row component, sets the bin number 400 as the column component, and has the signal charge accumulation value as the value of each component.

[0155] Then, the color transformation matrix is ​​set as a matrix represented by "C" (number of fluorescent markers × number of bins) (the set of extracted bin values), and the fluorescent color signal data generated therefrom is set as a matrix represented by "P" (number of scans × number of colors). Moreover, the following equations (1) and (2) hold. The color transformation processing unit 104 calculates the inverse matrix of the color transformation matrix "C" (transformation matrix) as shown in equation (2), and multiplies the inverse matrix of the calculated color transformation matrix "C" by "F" from the right, thereby calculating the signal component "P" originating from each fluorescent marker.

[0156] F = PC ···(1)

[0157] FC -1 =PCC -1 =P ···(2)

[0158] However, when the color transformation matrix "C" and the signal charge accumulation matrix "F" are defined by their respective transpose matrices, the signal component "P" derived from the fluorescent label is calculated by multiplying the inverse matrix of the color transformation matrix "C" from the left by "F".

[0159] The signal component "P" derived from the fluorescent marker, calculated through such an operation, has a time series of the signal intensity of each fluorescent marker as its component. That is, the color conversion processing unit 104 obtains the time series of the signal intensity of each fluorescent marker by performing the operation of equation (2). As a result, the color conversion processing unit 104 calculates the signal intensity of each fluorescent marker based on the cumulative signal data (the set of extracted bin values).

[0160] (flow chart)

[0161] Next, refer to Figure 10 This describes the color transformation processing performed by the color transformation processing unit 104.

[0162] Figure 10 This is a flowchart showing the sequence of color transformation processes performed in the first embodiment. Additionally, Figure 10 The processing shown is as follows Figure 5 The detailed sequence of steps S4.

[0163] First, the color transformation processing unit 104 calculates the inverse matrix of the color transformation matrix "C" (in equation (2)). -1 (S401) In terms of the number of elements in a matrix, a pseudo-inverse matrix can be used instead of an inverse matrix.

[0164] Next, the color transformation matrix is ​​right-multiplied by the inverse of the color transformation matrix "C" (S402) of the signal component "P" (signal charge accumulation data) originating from the fluorescent label. This process is equivalent to equation (2) above.

[0165] Then, the color conversion processing unit 104 outputs the data calculated in step S402 (the signal component "P" from the fluorescent marker in formula (2)) as fluorescent color signal data to the color signal evaluation processing unit 105 (S403).

[0166] Then, the electrophoresis data processing device 1 returns the processing to... Figure 5 Step S5.

[0167] (Fluorescence color signal data)

[0168] Figure 11 This is a diagram representing an example of fluorescence color signal data.

[0169] Figure 11 The horizontal axis represents the time elapsed during electrophoresis (actually the number of scans), and the vertical axis represents the signal strength. Figure 11 The matrix "P" representing the signal components derived from the fluorescent label, as shown in equation (2), is presented as a graph. Figure 11 In the signal strength shown, with Figure 8 Unlike other methods, the information in the sub-bin 400 disappears, becoming a relationship between time and signal strength. Furthermore, in this embodiment, the information of the CCD pixel 301 is referred to as the "signal value," and the information in the sub-bin 400 is referred to as the "signal charge accumulation value." Figure 11 The information displayed regarding the fluorescence color signal data is called "signal intensity".

[0170] like Figure 11 As shown, the matrix "P" of signal components derived from fluorescent labels contains information related to the signal intensities 521 to 524 derived from each fluorescent label.

[0171] [Calculation and Processing of Fluorescence Color Signal Evaluation Values]

[0172] Next, refer to Figure 12 and Figure 13 The calculation and processing of fluorescence color signal evaluation values ​​in the color signal evaluation processing unit 105 will be explained.

[0173] like Figure 1 The color signal evaluation processing unit 105 calculates the fluorescence color signal evaluation value based on the fluorescence color signal data.

[0174] (flow chart)

[0175] Figure 12 This is a flowchart illustrating the sequence of fluorescence color signal evaluation value calculation processing performed in the first embodiment. Additionally, Figure 12 express Figure 5 The detailed sequence of steps S5.

[0176] First, the color signal evaluation processing unit 105 extracts the peak intensity from each fluorescent marker from the fluorescence color signal data (S501). As described above, the fluorescence color signal data refers to the matrix "P" of signal components from the fluorescent markers calculated by equation (2), such as... Figure 11 As shown. Peak intensity refers to the peak value of the signal intensity originating from each fluorescent label. When extracting peak intensity, the color signal evaluation processing unit 105 uses fluorescence color signal data, which is obtained using samples with molecular weights that are known to form peaks in each fluorescent label and are equal to or more closely equal to those of the fluorescent labels. That is, using samples with molecular weights that are known to form peaks and are equal to or more closely equal to those of the fluorescent labels, the peak value is estimated and its peak intensity is extracted.

[0177] Next, the color signal evaluation and processing unit 105 calculates the signal intensities 521 to 524 (refer to) originating from each fluorescent marker. Figure 11 The average signal intensity of the signal (a value related to the peak value of the signal intensity, i.e., the first peak value, and a value related to the peak value of the signal intensity) (S502). For example, the average signal intensity of the peak value appearing in the signal originating from the first fluorescent label is set as INT(P1). Similarly, it is set as INT(P2), INT(P3), and INT(P4) corresponding to the second, third, and fourth fluorescent labels. For example, the color signal evaluation processing unit 105 calculates Figure 11 The average value of the signal strength 521 is taken as INT(P1). Similarly, the color signal evaluation processing unit 105 calculates... Figure 11 The average values ​​of the signals 522 to 524 are taken as INT(P2) to INT(P4).

[0178] Next, the color signal evaluation processing unit 105 extracts the maximum value as INT(Max) and the minimum value as INT(Min) from each INT(P1) to INT(P4).

[0179] Then, the color signal evaluation processing unit 105 uses the extracted features to calculate the signal intensity ratio X (S503) as shown in the following formula (3).

[0180] Xl NT(Mi n)NT(Ma×)(3)

[0181] Then, the color signal evaluation processing unit 105 outputs the signal intensity ratio X calculated in step S503 as the fluorescence color signal evaluation value (evaluation value, first evaluation value) (S504). The fluorescence color signal evaluation value calculated in this way represents... Figure 11 The evaluation values ​​for the deviation of the signal strength 521 to 524 are shown.

[0182] Then, the electrophoresis data processing device 1 returns to Figure 5 The processing of step S6.

[0183] For example, Figure 13 Indicates based on Figure 11 The average signal intensity is calculated from the fluorescence color signal data shown.

[0184] Figure 13 This is a graph representing an example of the average signal strength.

[0185] Figure 13 express Figure 12 The processing result of step S502.

[0186] Figure 13 The average signal intensity 531 shown is the average signal intensity originating from the first fluorescent label (INT(P1) = "10300"). The average signal intensity 532 is the average signal intensity originating from the second fluorescent label (INT(P2) = "15500"). Furthermore, the average signal intensity 533 is the average signal intensity originating from the third fluorescent label (INT(P3) = "6000"). And, the average signal intensity 534 is the average signal intensity originating from the fourth fluorescent label (INT(P4) = "9700"). The processing of calculating these average signal intensity 531 to 534 is equivalent to... Figure 12 Step S502.

[0187] In addition, according to Figure 13The average signal strengths shown are: INT(Max) = INT(P2) (average signal strength 522) = 15500, and INT(Min) = INT(P3) (average signal strength 523) = 6000. Therefore, the signal strength ratio X is 6000 / 15500 = 0.39. This processing is equivalent to... Figure 12 Step S503. Then, as described above, the color signal evaluation processing unit 105 outputs the calculated signal intensity ratio X as the fluorescence color signal evaluation value. Figure 12 Step S504).

[0188] [Decision Processing]

[0189] Next, the explanation Figure 5 The determination processing of the determination processing unit 106 in step S6.

[0190] Based on the fluorescence color signal evaluation value, the determination processing unit 106 transfers the subsequent processing to the merging region adjustment processing. Figure 5 Step S7), or transfer to the merge pattern output processing ( Figure 5 Step S8). If the fluorescence color signal evaluation value (signal intensity ratio X) is less than a predetermined threshold (S6 → No: predetermined condition met), the current merged pattern is determined to be not optimal, and the next process becomes the merged region adjustment process. Figure 5 Step S7). On the other hand, if the fluorescence color signal evaluation value is above the threshold (S6 → Yes: the predetermined condition is not met), it is determined that the current merged pattern is the best, and the next process becomes the merged pattern output process. Figure 5 Step S8).

[0191] [Regional Merging Adjustment Process]

[0192] Next, refer to Figure 14 The merger area adjustment processing performed by the merger area adjustment processing unit 107 will be explained.

[0193] The merging region adjustment processing unit 107 adjusts the merging pattern used to divide wavelength regions. In the merging region adjustment processing unit 107, the average signal intensity used in calculating the fluorescence color signal evaluation value is employed. Figure 13 ), Figure 4A The relationship between the fluorescence wavelength distribution shown and the 400-cell sub-division is as follows: Figure 9 The standardized cumulative signal charge value is shown.

[0194] (flow chart)

[0195] Figure 14 This is a flowchart illustrating the processing order of the merged region adjustment process. Additionally, Figure 14 The processing shown is as follows Figure 5 The detailed sequence of steps S7.

[0196] First, the merging region adjustment processing unit 107 extracts the average signal intensity of the fluorescence color signal data (the value related to the first peak, the value related to the peak of the signal intensity) to become the minimum (smallest) fluorescent marker (S701). Figure 13 In the example of fluorescence color signal data shown, the average signal intensity 533 (INT(P3)) is extracted as the third fluorescent marker.

[0197] Next, the merging region adjustment processing unit 107 performs a bin width amplification process (the size of bin 400) to enlarge the region corresponding to the wavelength at which the fluorescent marker extracted in step S701 becomes stronger (S702). That is, the merging region adjustment processing unit 107 amplifies the bin width of the fluorescent marker extracted in S701 to increase the cumulative value of the peak signal charge.

[0198] For example, the merged area adjustment processing unit 107 will be equivalent to Figure 9 The width of the bin 400 at the peak of the third fluorescent label (spectrum 513) (the largest bin value among the bin values) is increased by 10% to 80%. Furthermore, the merging region adjustment processing unit 107 also reduces the width of the bins 400 adjacent to the increased bin 400. By performing this processing, the effect of the increased width of the bin 400 on other bins 400 can be suppressed.

[0199] That is, in Figure 9 In the normalized spectrum 513 corresponding to the third fluorescent label, the bin number "7" is the peak value. Therefore, in step S702, the merging region adjustment processing unit 107 amplifies the bin width of bin 400 with bin number "7". Furthermore, this amplification of bin width is also applicable to other fluorescent labels.

[0200] Next, the merging region adjustment processing unit 107 extracts the average signal intensity of the fluorescence color signal data (the value related to the first peak) to become the maximum (largest) fluorescent marker (S703). Figure 13 In the example of fluorescence color signal data shown, the average signal intensity 532 (INT(P2)) is extracted as the second fluorescent marker.

[0201] Then, the merging region adjustment processing unit 107 performs a bin width reduction process (the size of bin 400) to reduce the bin width so that the region corresponding to the wavelength at which the extracted fluorescent marker becomes stronger is reduced (S704). That is, the merging region adjustment processing unit 107 reduces the bin width for the fluorescent marker extracted in step S703 in a way that the cumulative value of the peak signal charge is reduced.

[0202] For example, the merged area adjustment processing unit 107 is equivalent to Figure 9 The bin number at the peak (maximum bin value) of the second fluorescent marker (spectrum 512) is reduced by 10-80%. Furthermore, the merging region adjustment processing unit 107 enlarges the width of bins 400 adjacent to the reduced bins 400. By performing this processing, the effect of the increased width of bins 400 on other bins 400 can be suppressed.

[0203] exist Figure 9 In the example shown, the bin number "5" of the normalized spectrum 512 that corresponds to the second fluorescent label is the peak value. Therefore, in step S704, the merging region adjustment processing unit 107 reduces the bin width of bin 400 with bin number "5". Furthermore, this reduction in bin width also applies to other fluorescent labels.

[0204] Furthermore, the merged region adjustment processing unit 107 can also reduce the bin width in step S704 without acquiring a region corresponding to the wavelength at which the extracted fluorescent marker becomes stronger. That is, reducing the width of the bin 400 can also include deleting bins 400. For example, bins 400 belonging to the top of the peak can be retained, and bins 400 adjacent to the top of the peak can be deleted. By performing such processing, the effect of increasing the width of the bins 400 on other bins 400 can be suppressed.

[0205] Then, the merge area adjustment processing unit 107 generates a merge pattern reflecting the adjusted compartment width as a second merge pattern. Then, when the merge pattern before adjusting the compartment width is set as the first merge pattern, the merge area adjustment processing unit 107 updates the first merge pattern to the second merge pattern (merge pattern update: S705).

[0206] Electrophoresis data processing device 1 repeatedly executes the updated merging pattern (second merging pattern). Figure 5 The processing steps S2 to S6 are repeated until the determination processing unit 106 determines that the fluorescence color signal evaluation value is above a predetermined threshold. Finally, when the determination processing unit 106 determines that the fluorescence color signal evaluation value is above the predetermined threshold, the merged pattern output unit 108 outputs the final merged pattern to the outside. Figure 5 Step S8).

[0207] [Control Screen]

[0208] The following is for reference only. Figure 2 The screen displayed in the first embodiment will be described below. Additionally, the following... Figures 15A to 15D The images shown are 600, 610, and 620. Figure 2 The screen displayed in step S0.

[0209] Figure 15A This is an example of a menu screen (600).

[0210] like Figure 15A As shown, the menu screen 600 includes an analysis execution button 601 (which serves as the execution button for electrophoresis in the electrophoresis apparatus), an analysis sample setting button 602, a fluorescence sensitivity adjustment button 603 (which serves as the sensitivity adjustment execution button for each fluorescent label), and a maintenance button 604.

[0211] When the analysis execution button 601 is selected via the input device 114, the analysis of the sample based on electrophoresis begins.

[0212] The sample setting button 602 is used to set the sample.

[0213] In addition, when the fluorescence sensitivity adjustment button 603, which is displayed separately from the input and analysis execution button 601, is selected via the input device 114, the processing of the merging processing unit 102 to the merging area adjustment processing unit 107 begins.

[0214] Furthermore, maintenance button 604 is the button used to select input when performing maintenance on electrophoresis device 2.

[0215] exist Figure 15A In the middle, the mouse cursor M indicates that the fluorescence sensitivity adjustment is not yet complete, and the input device 114 (refer to) is used to input the signal. Figure 2 (This refers to the case where the "Analyze and Execute" button 601 was selected.) Figure 11 As shown, fluorescence color signal data with varying intensities of each fluorescent marker are obtained. The state of incomplete fluorescence sensitivity adjustment refers to the state where the fluorescence sensitivity adjustment button 603 is not selected and the processing based on the merging processing unit 102 to the merging region adjustment processing unit 107 has not started (before the processing of the bin generation unit, signal intensity calculation unit, and adjustment unit).

[0216] Additionally, if the input parsing execution button 601 is selected via input device 114 before the fluorescence sensitivity adjustment is complete, the following will be displayed: Figure 15B The dialog box screen 610 shown prompts attention and adjusts fluorescence sensitivity (displaying the processing of the box generation unit, signal strength calculation unit, and adjustment unit).

[0217] And, as Figure 15B As shown, the dialog box screen 610 displays a "Yes" button 611 and a "No" button 612.

[0218] When the “Yes” button 611 is selected via the input device 114 in the dialog box screen 610, the electrophoresis-based analysis of the sample is performed.

[0219] Additionally, when in dialog box screen 610 via input device 114 (in Figure 15B When the mouse cursor (M) selects the "No" button (612), return to... Figure 15A The menu screen shown is 600.

[0220] Figure 15C This indicates that the input device 114 (in) Figure 15C The image shows the menu screen 600 where the state of the fluorescence sensitivity adjustment button 603 is selected (represented by the mouse cursor M).

[0221] in addition, Figure 15C The structure of the menu screen 600 shown is similar to Figure 15A Same, therefore in Figure 15C Chinese annotation and Figure 15A Same symbols, with explanations omitted.

[0222] like Figure 15C As shown, when the input fluorescence sensitivity adjustment button 603 is selected (the sensitivity adjustment execution button is selected via the input section), the screen switches to... Figure 15D The fluorescence sensitivity adjustment screen shown is 620.

[0223] The fluorescence sensitivity adjustment screen 620 displays a sample content input window 621 and a setting confirmation button 622. In the sample content input window 621, the user inputs the type of sample for adjustment via the input device 114, or selects it via a drop-down menu (not shown). The sample for adjustment is a DNA molecule with multiple fluorescent labels. When the sample for adjustment is placed on the electrophoresis apparatus 2, the user selects the setting confirmation button 622 corresponding to the sample content input window 621 for the adjusted sample via the input device 114.

[0224] Thus, after setting the sample required for fluorescence sensitivity adjustment in electrophoresis apparatus 2, the user begins using the set adjustment sample by selecting the start input button 623. Figure 5 The process is as shown. Thus, by selecting the fluorescence sensitivity adjustment button 603 (sensitivity adjustment execution button) via the input device 114 (input section), the process begins. Figure 5 The following steps are processed: S1 and below. Additionally, in... Figure 15D In the image, the mouse cursor M represents the user's input of the start button 623.

[0225] In addition, such as Figure 15D As shown, multiple adjustment samples can be set.

[0226] Figures 15A to 15D The screens 610, 610, and 620 shown are processed by the input / output processing unit 109 (see reference). Figure 1 Displayed on display device 115 (refer to) Figure 2 Additionally, the input / output processing unit 109 obtains data via the input device 114 (see reference 114). Figure 2 The information input. That is, the information obtained by the input / output processing unit 109 based on... Figure 15D The start button 623 shown indicates the start of sensitivity adjustment for the input input (selection is performed via sensitivity adjustment of the input unit), and the input / output processing unit 109 processes the signal charge data acquisition unit 101 (see reference). Figure 1 This indicates that processing has begun.

[0227] In a typical electrophoresis system Z, Figure 15A , Figure 15C The fluorescence sensitivity adjustment button 603 shown is not displayed on the menu screen 600. Furthermore, in a typical electrophoresis system Z, it is not displayed. Figure 15B The dialog box shown is 610. Figure 15D The fluorescence sensitivity adjustment screen shown is 620. Additionally, via the display... Figures 15A-15C The displayed screen resolutions (600, 610, 620) allow users to easily... Figure 5 The processing shown.

[0228] [Fluorescence color signal data]

[0229] Figure 16 This is a diagram showing an example of fluorescence color signal data representing the result of the sensitivity adjustment process completed in this embodiment.

[0230] Figure 16 The input was selected after the fluorescence sensitivity adjustment was completed. Figure 15A and Figure 15C When the analysis execution button 601 is pressed, the fluorescence color signal data is finally displayed on the display device 115.

[0231] Figure 16 The horizontal and vertical axes in the middle Figure 11 Since they are the same, the explanation is omitted.

[0232] Figure 16 The signal strengths shown, 541 to 544, indicate that... Figure 11 The signal intensities of the fluorescent markers corresponding to signal intensities 521–524 are shown.

[0233] exist Figure 16 In, with Figure 11 Compared to signal strengths 521 to 524, each signal strength 541 to 544 is approximately the same.

[0234] As described in Patent Document 1, merging at equal intervals can reduce the amount of data. However, due to the different wavelength characteristics of the fluorescent tags, the intensity of the fluorescence color separation signal will deviate even if the concentration ratio of each fluorescent tag is the same. If this deviation is large, the concentration range of the fluorescent tags that can be detected becomes narrower. Therefore, it is necessary to adjust the merging pattern appropriately, but so far, the appropriate merging pattern adjustment has been performed manually.

[0235] According to the first embodiment, based on the signal value of the CCD pixel 301, the electrophoretic data processing apparatus 1 retrieves and outputs the optimal merging pattern for suppressing signal strength deviations. This reduces the burden on the user and reliably obtains signal strength with suppressed deviations.

[0236] That is, through the electrophoresis system Z of the first embodiment, such as Figure 16 As shown, fluorescence color signal data with suppressed signal intensity deviations of each fluorescent marker can be obtained.

[0237] In addition, such as Figure 5 As shown, repeat steps S2 to S7 until the result is "yes" in step S6. In this way, regardless of the default merging pattern, the optimal merging pattern for suppressing signal strength deviations can be obtained.

[0238] Thus, according to this embodiment, an effective merging pattern can be calculated accurately and as quickly as possible for the group of fluorescent markers used, and sensitivity deviations of the fluorescent markers can be suppressed.

[0239] As described in Patent Documents 2 and 3, even when adjusting the binning 400 to improve the S / N ratio, deviations in the signal intensity of the fluorescent marker can sometimes occur. If a deviation in the signal intensity of the fluorescent marker occurs, the data analysis results will also be biased, which is therefore undesirable. In this embodiment, suppressing deviations in the signal intensity of the fluorescent marker is prioritized over improving the S / N ratio. This allows for the suppression of deviations in the data analysis results, enabling high-precision data analysis compared to simply improving the S / N ratio.

[0240] <Second Implementation>

[0241] Next, refer to Figure 17 and Figure 18 The second embodiment of the present invention will be described.

[0242] [System Architecture]

[0243] Figure 17 This is a diagram showing a structural example of the electrophoresis system Za according to the second embodiment.

[0244] exist Figure 17 In the middle, to and Figure 1 The same structure is labeled with the same symbols and the explanation is omitted.

[0245] exist Figure 17 In, with Figure 1 The difference lies in the addition of a color transformation matrix evaluation processing unit 121 to the electrophoresis data processing apparatus 1a. The processing performed by the color transformation matrix evaluation processing unit 121 will be described later. Furthermore, the color transformation matrix evaluation processing unit 121 stores data... Figure 2 The program in the storage device 113 shown is loaded into the memory 111 and executed by the CPU 112 to be implemented.

[0246] [Overall Processing]

[0247] Figure 18 This is a flowchart illustrating an example of electrophoresis data processing performed in the second embodiment.

[0248] exist Figure 18 In the middle, to and Figure 5 The same treatment is marked with the same symbols and the explanation is omitted.

[0249] Figure 18 The processing shown is the same as Figure 5 The difference lies in the fact that a color transformation matrix evaluation process (S5A) is performed after step S5. Step S5A will be described later. Furthermore, steps S6A and S7A will also be described later.

[0250] [Color Transformation Matrix Evaluation Processing]

[0251] right Figure 18 The steps of S5A (color transformation matrix evaluation processing) will be explained.

[0252] The color transformation matrix evaluation processing unit 121 (second evaluation value calculation unit) calculates the color transformation matrix evaluation value (second evaluation value) based on the color transformation matrix "C" calculated by the color transformation matrix calculation processing unit 103. For example, the condition number of the color transformation matrix "C" can be used as the color transformation matrix evaluation value. When the color transformation matrix is ​​set to "C", the condition number k(C) of the color transformation matrix "C", i.e., the color transformation matrix evaluation value, is calculated based on the following equation (11) which is the color transformation matrix evaluation formula. Of course, the color transformation matrix evaluation value can also use indicators other than the condition number shown in equation (4). Furthermore, ||C|| represents the square norm value of C. Such a color transformation matrix evaluation value represents the calculation accuracy when calculating the signal component "P" (signal intensity of each fluorescent label) originating from the fluorescent label in equation (2). Thus, the color transformation matrix evaluation processing unit 121 calculates the color transformation matrix evaluation value (second evaluation value) based on the color transformation matrix "C" (transformation matrix), representing the calculation accuracy when calculating the signal component "P" (signal intensity of each fluorescent label) originating from the fluorescent label.

[0253] k(C) = ||C -1 ||·||C|| ···(11)

[0254] Then, the determination processing unit 106 in Figure 18 In step S6A, based on the fluorescence color signal evaluation value and the color transformation matrix evaluation value, it is determined that the next processing step will be transferred to the merging region adjustment processing. Figure 18 Step S7A) and merged pattern output processing ( Figure 18 Which of the steps in S8) is it? Figure 18 In step S6, if either the fluorescence color signal evaluation value or the color transformation matrix evaluation value fails to meet a predetermined benchmark ( Figure 18 S6A → No; if the first and second evaluation values ​​meet the predetermined conditions, the next step is a merge adjustment process. Figure 18 Step S7A). Furthermore, if both the fluorescence color signal evaluation value and the color transformation matrix evaluation value meet predetermined criteria ( Figure 18 S6A → Yes), the next process becomes the processing of the merged pattern output unit 108 ( Figure 18 (Step S8). The predetermined benchmark is, for example, below a predetermined threshold.

[0255] exist Figure 18 In step S7A, the merged area adjustment processing unit 107, in addition to... Figure 5In addition to the binning adjustment performed in step S7, a process is also performed to improve the calculation accuracy compared to the current calculation accuracy. This improvement in calculation accuracy refers to changing from single-precision calculation to double-precision calculation, etc.

[0256] Furthermore, in the second embodiment, in Figure 18 In step S6A, both the fluorescence color signal evaluation value and the color transformation matrix evaluation value are determined simultaneously, but the determination can also be performed in two stages. That is, if the fluorescence color signal evaluation value is above a predetermined threshold in step S6 (S6A → Yes), the determination processing unit 106 can determine whether the pull-up evaluation value is above the predetermined threshold. Moreover, if the color transformation matrix evaluation value is below the predetermined threshold, the merging region adjustment unit 107 (adjustment unit) performs processing to improve the calculation accuracy compared to the current calculation accuracy. Afterwards, the electrophoresis data processing apparatus 1 returns the processing to step S2.

[0257] On the other hand, if the evaluation value of the color transformation matrix is ​​above a predetermined threshold, step S8 is performed.

[0258] According to the second embodiment, the reduction in calculation accuracy can be suppressed.

[0259] <Third Implementation Method>

[0260] Next, refer to Figures 19-21 The third embodiment of the present invention will now be described.

[0261] [System Architecture]

[0262] Figure 19 This is a diagram illustrating a structural example of the electrophoresis system Zb according to the third embodiment.

[0263] exist Figure 19 In the middle, to and Figure 1 The same structure is labeled with the same symbol, and the explanation is omitted.

[0264] exist Figure 19 In the electrophoresis system Zb shown, with Figure 1 The difference in the electrophoresis system Z shown is that the electrophoresis data processing device 1b has an up-pulling evaluation processing unit 131. The processing performed by the up-pulling evaluation processing unit 131 will be described later. Furthermore, the up-pulling evaluation processing unit 131 processes data stored in... Figure 2 The program in the storage device 113 shown is loaded into the memory 111 and executed by the CPU 112 to be implemented.

[0265] [Overall Processing]

[0266] Figure 20 This is a flowchart illustrating an example of electrophoretic data processing performed in the third embodiment.

[0267] exist Figure 20 In the middle, to and Figure 5 The same treatment is marked with the same symbols and the explanation is omitted.

[0268] Figure 20 The processing shown is the same as Figure 5 The difference lies in the fact that an evaluation process (S5B) is performed after step S5. Step S5B will be described later. Furthermore, steps S6B and S7B will also be described later.

[0269] [Review processing]

[0270] right Figure 20 The following steps will be explained in S5B (pull-up evaluation processing).

[0271] Pullup evaluation processing unit 131 calculates the pullup evaluation value (third evaluation value) based on the fluorescence color signal data generated by color transformation processing unit 104. In the fluorescence color signal data, due to color transformation processing, sometimes the signal intensity of a specific fluorescent marker overlaps with the signal intensity of other fluorescent markers. The signal intensity of the main fluorescent marker is set to INT (Main). In addition, the signal intensity of other overlapping (minor) fluorescent markers is set to INT (Sub). In this case, the pullup evaluation value is represented by the following formula (21).

[0272] INT(Sub)INT(Main)(5)

[0273] [Fluorescence color signal data]

[0274] Figure 21 This is a diagram illustrating an example of the fluorescent color signal data generated by the pull-up mechanism.

[0275] Figure 21 The horizontal and vertical axes shown are... Figure 11 Since the horizontal and vertical axes shown are the same, the explanation is omitted.

[0276] In addition, Figure 21 In the range, a signal strength of 541–544 is equivalent to Figure 11 The signal strengths shown are 521 to 524. Additionally, in... Figure 21 In the diagram shown, the main signal strengths of 541 to 544 represent the state where the deviation has been suppressed.

[0277] Figure 21In this process, the signal intensity of the second fluorescent label (signal intensity 542: signal intensity of the first fluorescent label) overlaps with the signal intensity 541a (signal intensity of the second fluorescent label). Furthermore, the average signal intensity of the second fluorescent label is INT(Main) = 10000. Additionally, the average signal intensity of the first fluorescent label is INT(Sub) = 2000. In this case, the pull-up evaluation value calculated using equation (5) is calculated to be 0.2. Furthermore, the pull-up evaluation processing unit 131 determines the larger of the overlapping signal intensities as primary and the smaller as secondary. Thus, the pull-up evaluation value is the ratio of the primary signal intensity (first fluorescent label) to the secondary signal intensity (first fluorescent label).

[0278] exist Figure 20 In step S6B, the determination processing unit 106 makes a determination based on the fluorescence color signal evaluation value and the pull-up evaluation value. The determination then moves the next processing step to the merging region adjustment processing. Figure 20 Step S7B) or transfer to the merge pattern output processing ( Figure 20 The determination in step S8). The determination processing unit 106 determines if either the fluorescence color signal evaluation value or the pull-up evaluation value fails to meet a predetermined benchmark. Figure 20 S6B → No: If the predetermined conditions are met, the next process becomes the merge adjustment process. Figure 20 Step S7B). Under the condition that both the fluorescence color signal evaluation value and the pull-up evaluation value meet the predetermined benchmark ( Figure 20 S6B → Yes), the next process becomes the processing of the merged pattern output unit 108 ( Figure 20 (Step S8). The predetermined benchmark is, for example, below a predetermined threshold.

[0279] exist Figure 20 In step S7B, the merged area adjustment processing unit 107, in addition to... Figure 5 In addition to the processing (bin adjustment) performed in step S7, the bin width (size of bin 400) is also reduced to decrease the cumulative signal charge value that generates the peak in the main fluorescent marker (first fluorescent marker) that is pulled up.

[0280] Furthermore, in the third embodiment, in Figure 20In step S6B, both the fluorescence color signal evaluation value and the pull-up evaluation value are determined simultaneously, but the determination can also be performed in two stages. That is, if the fluorescence color signal evaluation value is above a predetermined threshold in step S6B (S6B → Yes), the determination processing unit 106 can determine whether the pull-up evaluation value is above the predetermined threshold. Then, if the pull-up evaluation value is below the predetermined threshold, the merging region adjustment processing unit 107 shrinks the bins 400 near the peak of the signal intensity in the main fluorescent marker that generates the pull-up. In addition, the merging region adjustment processing unit 107 enlarges the bins 400 adjacent to the shrunken bins 400. After that, the electrophoresis data processing apparatus 1 returns the processing to step S2.

[0281] On the other hand, if the pull-up evaluation value is above the predetermined threshold, step S8 is performed.

[0282] According to the third embodiment, the effect of upward pull can be suppressed.

[0283] In addition, the electrophoresis data processing device 1 may also have Figure 17 The color transformation matrix evaluation processing unit 121 and shown Figure 19 The upward evaluation processing unit 131 shown is for both parties.

[0284] In this structure, the determination processing in the determination processing unit 106 (equivalent to...) Figure 5 In step S6), if any one of the fluorescence color signal evaluation value, color transformation matrix evaluation value, and pull-up evaluation value fails to meet the predetermined benchmark (equivalent to...), Figure 5 S6→No), the next process is transferred to the merge adjustment process (equivalent to S6→No). Figure 5 Step S7). Additionally, if the fluorescence color signal evaluation value, color transformation matrix evaluation value, and pull-up evaluation value all meet predetermined criteria (equivalent to...), then... Figure 5 S6→ is), the next processing step is to merge the pattern output (equivalent to Figure 5 Step S8).

[0285] This invention is not limited to the embodiments described above, but includes various modifications. For example, the embodiments described above are detailed for the purpose of easily understanding and illustrating the invention, and are not limited to having all the structures described. Furthermore, a portion of the structure of one embodiment can be replaced with the structure of another embodiment, and the structure of another embodiment can be added to the structure of one embodiment. Additionally, regarding a portion of the structure of each embodiment, other structures can be added, deleted, or replaced.

[0286] Furthermore, the aforementioned structures, functions, components 101-108, 121, 131, storage device 113, etc., can also be implemented in hardware, for example, using integrated circuit design, by means of some or all of them. Additionally, as... Figure 2 As shown, the aforementioned structures and functions can also be implemented in software by having a processor such as CPU112 interpret and execute the programs that implement each function. In addition to being stored in HD (Hard Disk), the programs, tables, files, and other information that implement each function can also be stored in memory, SSD (Solid State Drive), or other recording devices, or in recording media such as IC (Integrated Circuit) cards, SD (Secure Digital) cards, and DVD (Digital Versatile Disc).

[0287] Furthermore, in each embodiment, control lines and information lines refer to the lines deemed necessary for the description, but may not represent all control lines and information lines on the product. In reality, it can be assumed that almost all structures are interconnected.

[0288] Symbol Explanation

[0289] 1. Electrophoresis data processing device (1a, 1b)

[0290] 2 Electrophoresis apparatus

[0291] 101 Signal Charge Data Acquisition Unit (Acquisition Unit)

[0292] 102 Merging Processing Department (Box Generation Department)

[0293] 103 Color Transformation Matrix Calculation and Processing Unit (Binding Value Extraction Unit)

[0294] 104 Color Conversion Processing Unit (Signal Strength Calculation Unit)

[0295] 105 Color Signal Evaluation and Processing Department (First Evaluation Value Calculation Department)

[0296] 106 Judgment and Processing Department

[0297] 107 Merged Area Adjustment Processing Department (Adjustment Department)

[0298] 108 Combined Pattern Output Unit

[0299] 109 Input / Output Processing Unit (Display Processing Unit)

[0300] 113 storage device

[0301] 114 Input Device (Input Section)

[0302] 115 Display device (display unit)

[0303] 121 Color Transformation Matrix Evaluation Processing Unit (Second Evaluation Value Calculation Unit)

[0304] 131 Upward Evaluation Processing Department (Third Evaluation Value Calculation Department)

[0305] 201 wavelength dispersion

[0306] 202 Signal Charge Acquisition Unit (Imaging Element)

[0307] 203 Signal Charge Data Output Section

[0308] 301 CCD pixels

[0309] 400, 401-403, 411-430 (divided into boxes)

[0310] Peak values ​​between 501 and 504 (second peak value)

[0311] Spectra from 511 to 514 (including the first peak)

[0312] Signal strength of 521~524, 541~544, 541a

[0313] Average signal strength from 531 to 534 (value related to the first peak value)

[0314] 600 Menu Screen

[0315] 601 Execution Button (Electrophoresis Execution Button)

[0316] 602 Sample Setting Button

[0317] 603 Fluorescence Sensitivity Adjustment Button

[0318] 604 Maintenance Button

[0319] 610 Dialog Box Screen (Displaying prompts for processing by the distribution box generation unit, signal strength calculation unit, and adjustment unit)

[0320] 620 Fluorescence Sensitivity Adjustment Screen

[0321] 621 Sample Content Input Window

[0322] 622 Set Confirm Button

[0323] 623 Start button

[0324] Z, Za, Zb electrophoresis systems

[0325] S0 screen display processing (display processing steps)

[0326] Acquisition of S1 signal charge data (acquisition steps)

[0327] S2 Merging Process (Binding Generation Steps)

[0328] S3 color transformation matrix calculation and processing (binning value extraction step)

[0329] S4 color transformation processing (signal strength calculation steps)

[0330] S5 Color Signal Evaluation Processing (Evaluation Value Calculation Steps)

[0331] S7, S7A, and S7B are merged and adjusted (adjustment steps).

Claims

1. An electrophoresis data processing device, characterized in that, The electrophoresis data processing device has the following features: The acquisition unit acquires the pixel data output from each of the imaging elements when it outputs pixel data that converts the signal into an electrical signal by detecting the signal of each wavelength component of the fluorescence of the fluorescent label by multiple imaging elements of an electrophoresis apparatus that causes multiple fluorescent labels to swim together with the sample; The binning generation unit calculates the cumulative or representative value of the values ​​of a predetermined number of adjacent pixel data, sets the calculated cumulative or representative value as the binning value, thereby summarizing a predetermined number of adjacent pixel data into one bin. The binning value extraction unit extracts a set of binning values ​​derived from each fluorescent marker for each of the fluorescent markers; The signal strength calculation unit calculates the signal strength of each fluorescent marker based on the extracted set of bin values; The first evaluation value calculation unit calculates an evaluation value, namely the first evaluation value, representing the degree of deviation in the signal intensity for each of the fluorescent markers; and The adjustment unit, when the first evaluation value meets the predetermined conditions, performs a binning adjustment on the fluorescent marker with the largest value related to the peak value of the signal intensity (i.e., the first peak value), by reducing the size of the bin with the largest binning value in the set of binning values, i.e., the maximum binning value; and performs a binning adjustment on the fluorescent marker with the smallest value related to the first peak value, by increasing the size of the bin with the maximum binning value.

2. The electrophoresis data processing apparatus according to claim 1, characterized in that, The bin generation unit calculates the bin value by calculating the cumulative value of the pixel data, i.e., the cumulative signal charge value, for each bin. The binning value extraction unit extracts the peak value corresponding to the fluorescent marker, i.e., the second peak value, from the time series of the accumulated signal charge value. For each of the second peak values, it extracts the accumulated signal charge value constituting the second peak value. Each extracted second peak value is used as a row component, and the binning is used as a column component. A transformation matrix, which contains the accumulated signal charge value as the value of each component, is calculated. Thus, the set of binning values ​​originating from the fluorescent marker is extracted. The signal intensity calculation unit obtains the time series of the signal intensity of each fluorescent marker by multiplying the signal charge accumulation matrix by the inverse of the transformation matrix. Based on the extracted set of bin values, it calculates the signal intensity of each fluorescent marker. The signal charge accumulation matrix is ​​a matrix in which the number of scans of the fluorescence in the time series of the signal charge accumulation value is set as the row component, the bins are set as the column component, and the value of each component has the signal charge accumulation value.

3. The electrophoresis data processing apparatus according to claim 2, characterized in that, The electrophoresis data processing device includes a second evaluation value calculation unit, which calculates a second evaluation value, based on the transformation matrix, that is, an evaluation value related to the calculation accuracy when calculating the signal intensity of each fluorescent label. When the first evaluation value and the second evaluation value meet the predetermined conditions, the adjustment unit, in addition to performing the binning adjustment, also improves the calculation accuracy compared to the current calculation accuracy.

4. The electrophoresis data processing apparatus according to claim 1, characterized in that, The electrophoresis data processing apparatus includes a third evaluation value calculation unit, which calculates the ratio of the signal intensity of the first fluorescent label to the signal intensity of the second fluorescent label, i.e., a third evaluation value, when the signal intensity of the first fluorescent label (which is a predetermined fluorescent label) overlaps with the signal intensity of the second fluorescent label (which is another fluorescent label). When the first evaluation value and the third evaluation value meet the predetermined conditions, in addition to performing the binning adjustment, the adjustment unit also reduces the size of the bin corresponding to the maximum binning value for the first fluorescent marker.

5. An electrophoresis data processing device, characterized in that, The electrophoresis data processing device has the following features: The acquisition unit acquires the pixel data output from each of the imaging elements when it outputs pixel data that converts the signal into an electrical signal by detecting the signal of each wavelength component of the fluorescence of the fluorescent label by multiple imaging elements of an electrophoresis apparatus that causes multiple fluorescent labels to swim together with the sample; The binning generation unit calculates the cumulative or representative value of the values ​​of a predetermined number of adjacent pixel data, sets the calculated cumulative or representative value as the binning value, thereby summarizing a predetermined number of adjacent pixel data into one bin. The binning value extraction unit extracts a set of binning values ​​derived from each fluorescent marker for each of the fluorescent markers; The signal strength calculation unit calculates the signal strength of each fluorescent marker based on the extracted set of bin values; The evaluation value calculation unit calculates an evaluation value representing the degree of deviation of the signal intensity for each of the fluorescent markers; The adjustment unit, when the evaluation value meets the predetermined conditions, performs binning adjustment on the fluorescent marker with the largest value related to the peak of the signal intensity, by reducing the size of the bin with the largest bin value in the set of binning values, i.e., the maximum binning value; and performs binning adjustment on the fluorescent marker with the smallest value related to the peak of the signal intensity, by increasing the size of the bin with the maximum binning value. as well as The display processing unit displays the sensitivity adjustment execution button for each fluorescent marker on the display unit. The processing of the acquisition unit, the bin generation unit, the bin value extraction unit, the signal strength calculation unit, the evaluation value calculation unit, and the adjustment unit is performed by selecting the sensitivity adjustment execution button via the input unit.

6. The electrophoresis data processing apparatus according to claim 5, characterized in that, In addition to the sensitivity adjustment button, the display unit also displays an electrophoresis execution button, which serves as the electrophoresis execution button for the electrophoresis apparatus. Before the processing of the bin generation unit, the signal strength calculation unit, and the adjustment unit is performed, if the electrophoresis execution button is selected via the input unit, the display processing unit causes the display unit to display a prompt for the processing of the acquisition unit, the bin generation unit, the bin value extraction unit, the signal strength calculation unit, the evaluation value calculation unit, and the adjustment unit.

7. A method for processing electrophoresis data, characterized in that, Perform the following steps: The display shows the processing steps, and displays the sensitivity adjustment execution button for each fluorescent marker on the display section. In the acquisition step, when the multiple imaging elements of the electrophoresis apparatus, which causes multiple fluorescent labels to swim together with the sample to select via the sensitivity adjustment execution button of the input section, detect the signal of each wavelength component of the fluorescence of the fluorescent label and output pixel data that converts the signal into an electrical signal, the pixel data output from the imaging element is acquired from each of the imaging elements. The binning generation step involves calculating the cumulative or representative value of a predetermined number of adjacent pixel data, setting the calculated cumulative or representative value as the binning value, thereby summarizing a predetermined number of adjacent pixel data into one bin. The binning value extraction step involves extracting a set of binning values ​​derived from each fluorescent marker for each fluorescent marker. The signal intensity calculation step involves calculating the signal intensity of each fluorescent marker based on the extracted set of bin values. The evaluation value calculation step involves calculating an evaluation value representing the degree of deviation in the signal intensity for each of the fluorescent markers. The adjustment steps involve, when the evaluation value meets the predetermined conditions, performing a binning adjustment on the fluorescent marker with the largest value related to the peak signal intensity, which reduces the size of the bin with the largest binning value in the set of binning values, i.e., the maximum binning value; and performing a binning adjustment on the fluorescent marker with the smallest value related to the peak signal intensity, which increases the size of the bin with the maximum binning value.

8. The electrophoresis data processing method according to claim 7, characterized in that, The process of generating the sub-bin, extracting the sub-bin value, calculating the signal strength, calculating the evaluation value, and adjusting the sub-bin are repeated until the evaluation value no longer meets the predetermined conditions.

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