Information processing method, information processing apparatus, and information processing system

Abstract

To easily adjust a spectrum reference.SOLUTION: According to another embodiment of the present disclosure, there is provided an information processing method including calculating an intensity of light corresponding to each dye from light detected from each multi-dyed particle in a sample using a spectrum reference of each dye acquired from a single-dyed particle, calculating a leakage evaluation index indicating a degree of leakage of the light corresponding to each dye into light corresponding to another dye based on a distribution of the intensity of the light corresponding to each dye, and adjusting the spectrum reference of each dye based on the leakage evaluation index. The present technology can be applied to, for example, a flow cytometer.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present technology relates to an information processing method, an information processing device, and an information processing system. [Background technology]

[0002] A technique has been proposed in the past in which a two-dimensional plot is generated for two desired fluorescent dyes among multiple fluorescent dyes used to label a particle group, and the spectral reference (hereinafter referred to as SR) of the fluorescent dye corresponding to the fluorescent data of the two-dimensional plot is adjusted in accordance with user operations on the two-dimensional plot (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2021 / 153192 Summary of the Invention [Problem to be solved by the invention]

[0004] However, adjusting SR by user operation is cumbersome and time-consuming. In particular, with the recent trend toward multicolor FCMs (flow cytometers), it is predicted that adjusting SR by user operation will become even more cumbersome and time-consuming.

[0005] The present technology was developed in light of these circumstances, and makes it possible to easily adjust the SR. [Means for solving the problem]

[0006] An information processing method according to a first aspect of the present technology includes an information processing device calculating the intensity of light corresponding to each dye from light detected from each multi-dyed particle in a sample using a spectral reference for each dye obtained by a single-dyed particle, calculating a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes based on the distribution of the light intensity corresponding to each dye, and adjusting the spectral reference for each dye based on the leakage evaluation index.

[0007] An information processing device according to a first aspect of the present technology includes an unmixing unit that calculates the intensity of light corresponding to each dye from light detected from each multi-dyed particle in a sample using the spectral reference of each dye obtained by the single-dyed particle; an evaluation calculation unit that calculates a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes based on the distribution of the light intensity corresponding to each dye; and a spectral reference adjustment unit that adjusts the spectral reference of each dye based on the leakage evaluation index.

[0008] An information processing system according to a second aspect of the present technology includes a detection unit that detects light from each of a plurality of multi-dyed particles in a sample, and an information processing unit. The information processing unit includes an unmixing unit that calculates the intensity of light corresponding to each dye from the light detected from each of the multi-dyed particles in the sample using a spectral reference for each dye obtained by a single-dyed particle, an evaluation calculation unit that calculates a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes based on the distribution of the light intensity corresponding to each dye, and a spectral reference adjustment unit that adjusts the spectral reference for each dye based on the leakage evaluation index.

[0009] In a first aspect of the present technology, the spectral reference of each dye obtained by a single-dye particle is used to calculate the light intensity corresponding to each dye from the light detected from each multi-dye particle in the sample, and a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes is calculated based on the distribution of the light intensity corresponding to each dye, and the spectral reference of each dye is adjusted based on the leakage evaluation index.

[0010] In a second aspect of the present technology, light from each of a plurality of multi-dyed particles in a sample is detected, and the intensity of light corresponding to each dye is calculated from the light detected from each of the multi-dyed particles in the sample using the spectral reference of each dye obtained by the single-dyed particles, and a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes is calculated based on the distribution of the light intensity corresponding to each dye, and the spectral reference of each dye is adjusted based on the leakage evaluation index. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 10 is a diagram showing an example of a two-dimensional plot of light intensity. [Figure 2] FIG. 10 is a diagram for explaining problems that arise when SR is used. [Figure 3] FIG. 1 is a block diagram illustrating an example of the configuration of an information processing system. [Figure 4] FIG. 1 is a block diagram showing an example of the configuration of a biological sample analyzer. [Figure 5] FIG. 2 is a block diagram showing an example of the configuration of an information processing unit. [Figure 6] FIG. 2 is a block diagram showing an example of the configuration of an analysis pre-processing unit. [Figure 7] 1 is a flowchart illustrating the flow of an experiment. [Figure 8] 10 is a flowchart illustrating a first embodiment of pre-analysis processing. [Figure 9] FIG. 10 is a diagram illustrating an example of gating. [Figure 10]10 is a flowchart for explaining details of a first embodiment of an SR adjustment process. [Figure 11] FIG. 10 is a diagram for explaining the relationship between the unmixing state and SI. [Figure 12] FIG. 10 is a diagram for explaining a method for adjusting SR. [Figure 13] FIG. 10 is a diagram for explaining a method for adjusting SR. [Figure 14] FIG. 10 is a diagram illustrating an example of an orthogonality evaluation index. [Figure 15] FIG. 10 is a diagram illustrating an example of an orthogonality evaluation index. [Figure 16] 10 is a flowchart illustrating a second embodiment of pre-analysis processing. [Figure 17] FIG. 10 is a diagram showing an example of a two-dimensional plot of light intensity and a correlation coefficient. [Figure 18] FIG. 10 is a diagram showing an example of correlation coefficients between dyes. [Figure 19] FIG. 10 is a diagram showing an example of a two-dimensional plot of light intensity and a correlation coefficient. [Figure 20] FIG. 10 is a diagram showing an example of a two-dimensional plot of light intensity and a correlation coefficient. [Figure 21] FIG. 10 is a diagram showing an example of a two-dimensional plot of light intensity and a correlation coefficient. [Figure 22] FIG. 10 is a diagram showing an example of a two-dimensional plot of light intensity and a correlation coefficient. [Figure 23] 10 is a flowchart for explaining details of a second embodiment of the SR adjustment process. [Figure 24] FIG. 10 is a diagram showing an example of correlation coefficients between dyes. [Figure 25] FIG. 10 is a diagram showing an example of correlation coefficients between dyes. [Figure 26] FIG. 1 illustrates an example of the configuration of a computer. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present technology will be described in the following order. 0. Background of this technology 1. Embodiment 2. Variations 3.Other

[0013] <<0. Background of this technology>> First, the background of the present technology will be described with reference to FIGS.

[0014] For example, in the technology described in Patent Document 1, an unmixing process is performed on light data obtained by detecting light generated by irradiating biological particles (hereinafter referred to as multi-dyed particles) labeled (dyed) with multiple dyes (e.g., fluorescent dyes), thereby obtaining light intensity data that individually indicates the intensity of light (e.g., fluorescence) corresponding to each dye of each multi-dyed particle.

[0015] In this unmixing process, the SR of each dye is used. The SR is reference data that represents the standard wavelength distribution (spectrum) of light corresponding to each dye used to stain bioparticles. For example, the SR of each dye can be obtained by individually detecting the light generated by irradiating bioparticles labeled only with the target dye (hereinafter referred to as single-stained particles).

[0016] When performing unmixing processing on a sample containing multiple multi-dyed particles (hereafter referred to as a multi-dyed particle sample) using SR acquired with a single-dyed particle, ideally the light corresponding to each dye should be completely separated.

[0017] For example, it is ideal to maintain the orthogonality of a two-dimensional plot showing the distribution of light intensity corresponding to two dyes (hereinafter referred to as orthogonality of a two-dimensional plot). For example, in a two-dimensional plot, it is ideal for the distribution of light intensity in a population of bioparticles that show a negative reaction to one dye to be orthogonal to the axis showing the light intensity corresponding to the other dye. For example, in a two-dimensional plot, it is ideal for the distribution of light intensity in a population of bioparticles that show a positive reaction to one dye to be orthogonal to the axis showing the light intensity corresponding to the other dye.

[0018] Hereinafter, the light intensity corresponding to each dye will be referred to as the light intensity for each dye.

[0019] Ideally, the light intensity for each dye should change independently, i.e., there should be no dependency of light intensity between dyes (hereinafter referred to as inter-dye dependency).

[0020] For example, Figure 1 shows an example of a two-dimensional plot of light intensity for dye 1 and dye 2. Specifically, the vertical axis of Figures 1A and 1B represents the light intensity for dye 1 transformed by biexponential transformation, and the horizontal axis represents the light intensity for dye 2 transformed by biexponential transformation. Figures 1A and 1B show the distribution of light intensity of bioparticles that showed a negative reaction to dye 2.

[0021] In this case, for example, as shown in Figure 1A, it is ideal for the light intensity distribution to be nearly orthogonal to the axis (vertical axis) of light intensity for dye 1. In other words, it is ideal for the light intensity for dye 1 to be nearly constant, regardless of the light intensity for dye 2.

[0022] However, when analyzing multiple multi-stained particle samples, the SR of each dye may be used, resulting in a decrease in orthogonality of the 2D plot or an increase in the inter-dye dependence. For example, as shown in Figure 1B, the light intensity for dye 1 may increase as the light intensity for dye 2 increases.

[0023] This is due to, for example, the following reasons.

[0024] For example, calculation errors due to standardization can cause a decrease in orthogonality in two-dimensional plots and an increase in inter-dye dependency. Here, calculation errors due to standardization refer to calculation errors in the standardization of SRs obtained from single-stained particle samples when using them to unmix multi-stained particle samples.

[0025] For example, when analyzing a multi-stained particle sample using an FCM of a different model than the one used to generate the SR, differences in optical properties due to differences in the lasers installed in each FCM may result in a decrease in orthogonality of the 2D plot or an increase in inter-dye dependency.

[0026] For example, even if a multi-stained particle sample is analyzed using the same model of FCM as that used to generate the SR, differences in the optical properties between individual FCMs may result in a decrease in the orthogonality of the 2D plot and an increase in the dependency between dyes.

[0027] For example, as shown in Figure 2B and C, the notch regions MA1 and MA2 of the spectra may differ between FCM individuals. In contrast, as shown in Figure 2A, when an SR without a notch region is used, differences in the notch regions between FCM individuals can sometimes result in a decrease in the orthogonality of the two-dimensional plot and an increase in the dependency between dyes.

[0028] For example, even if a multi-dyed particle sample is analyzed using the same FCM as that used to generate the SR, differences in various settings between the generation of the SR and the analysis of the multi-dyed particle sample may result in a decrease in the orthogonality of the 2D plot or an increase in the dependency between dyes.

[0029] In contrast, this technology makes it possible to easily and appropriately adjust the SR of each dye so as to suppress the decrease in orthogonality of the two-dimensional plot and the increase in dependency between dyes.

[0030] <<1. Embodiment>> Next, an embodiment of the present technology will be described with reference to FIGS.

[0031] <Example of information processing system configuration> FIG. 3 shows an example of the configuration of an information processing system 1 to which the present technology is applied.

[0032] Information processing system 1 comprises biological sample analyzers 11-1 to 11-n, server 12-1, and server 12-2.

[0033] Biological sample analyzers 11-1 to 11-m and server 12-2 are connected via a network (not shown). Biological sample analyzers 11-1 to 11-m and server 12-2 are owned by a single organization.

[0034] The organizational unit that owns biological sample analyzers 11-1 to 11-m and server 12-2 is not particularly limited. For example, the organization may be a single company, school, organization, etc., or a department of a company, school, organization, etc.

[0035] Biological sample analyzers 11-m+1 to 11-n, server 12-1, and server 12-2 are connected via a network (not shown).

[0036] Hereinafter, when there is no need to distinguish between biological sample analyzers 11-1 to 11-n, they will simply be referred to as biological sample analyzer 11. Hereinafter, when there is no need to distinguish between servers 12-1 and 12-2, they will simply be referred to as server 12.

[0037] The biological sample analyzer 11 is composed of, for example, a flow cytometer and an imaging cytometer.

[0038] The server 12, for example, controls each biological sample analyzer 11. The server 12 manages and processes, for example, the data and programs used by each biological sample analyzer 11, as well as the data obtained by processing each biological sample analyzer 11.

[0039] Server 12-1 also prevents, for example, data obtained by biological sample analyzer 11 within an organization from leaking outside the organization.

[0040] The number of servers 12 and organizations is not limited to the example shown in this drawing. Also, for example, one organization may own multiple servers 12.

[0041] <Configuration example of biological sample analyzer 11> FIG. 4 shows an example of the configuration of the biological sample analyzer 11 of FIG.

[0042] The biological sample analyzer 11 includes a light irradiation unit 111 that irradiates light onto the biological sample S flowing through the flow path C, a detection unit 112 that detects light generated by irradiating the biological sample S with light, and an information processing unit 113 that processes information related to the light detected by the detection unit 112. Examples of the biological sample analyzer 11 include a flow cytometer and an imaging cytometer. The biological sample analyzer 11 may also include a sorting unit 114 that sorts specific biological particles P from within the biological sample. An example of a biological sample analyzer 11 that includes a sorting unit 114 is a cell sorter.

[0043] (biological samples) The biological sample S may be a liquid sample containing biological particles. The biological particles may be, for example, cells or non-cellular biological particles. The cells may be living cells, and more specific examples include blood cells such as red blood cells and white blood cells, and germ cells such as sperm and fertilized eggs. The cells may be directly collected from a specimen such as whole blood, or may be cultured cells obtained after culturing. Examples of the non-cellular biological particles include extracellular vesicles, particularly exosomes and microvesicles.

[0044] The bioparticles may be labeled with one or more labeling substances (e.g., dyes (particularly fluorescent dyes) and fluorescent dye-labeled antibodies). For example, the bioparticles may be labeled (stained) with one or more types of fluorescent dyes. The labeling of the bioparticles with fluorescent dyes may be performed by known techniques. Specifically, when the bioparticles are cells, the cells to be measured can be labeled with the fluorescent dye by mixing a fluorescently labeled antibody that selectively binds to an antigen present on the cell surface with the cells to be measured and allowing the fluorescently labeled antibody to bind to the antigen on the cell surface. Alternatively, the cells to be measured can be labeled with the fluorescent dye by mixing a fluorescent dye that is selectively taken up by specific cells with the cells to be measured.

[0045] A fluorescently labeled antibody is an antibody to which a fluorescent dye is bound as a label. The fluorescently labeled antibody may be an antibody to which a fluorescent dye is directly bound. Alternatively, the fluorescently labeled antibody may be an antibody to which avidin-bound fluorescent dye is bound via the avidin-biodin reaction, which is labeled with biotin. Note that either a polyclonal antibody or a monoclonal antibody can be used as the antibody.

[0046] The fluorescent dye for labeling cells is not particularly limited, and at least one of known dyes used for staining cells can be used. For example, fluorescent dyes include phycoerythrin (PE), fluorescein isothiocyanate (FITC), PE-Cy5, PE-Cy7, PE-Texas Red (registered trademark), allophycocyanin (APC), APC-Cy7, ethidium bromide, propidium iodide, Hoechst (registered trademark) 33258, Hoechst (registered trademark) 33342, DAPI (4',6-diamidino-2-phenylindole), acridine orange, chromomycin, mithramycin, olivomycin, pyronin Y, and thiazole orange. Examples of suitable anti-inflammatory agents that can be used include rhodamine 101, isothiocyanate, BCECF, BCECF-AM, C.SNARF-1, C.SNARF-1-AMA, aequorin, Indo-1, Indo-1-AM, Fluo-3, Fluo-3-AM, Fura-2, Fura-2-AM, oxonol, Texas Red (registered trademark), rhodamine 123, 10-N-nony-acridine orange, fluorescein, fluorescein diacetate, carboxyfluorescein, carboxyfluorescein diacetate, carboxydichlorofluorescein, and carboxydichlorofluorescein diacetate. In addition, derivatives of the above-mentioned fluorescent dyes can also be used.

[0047] (flow path) The flow channel C is configured to allow the biological sample S to flow. In particular, the flow channel C can be configured to form a flow in which biological particles contained in the biological sample are aligned in a substantially straight line. The flow channel structure including the flow channel C may be designed to form a laminar flow. In particular, the flow channel structure is designed to form a laminar flow in which the flow of the biological sample (sample flow) is surrounded by the flow of sheath liquid. The design of the flow channel structure may be appropriately selected by those skilled in the art, and a known design may be adopted. The flow channel C may be formed in a flow channel structure such as a microchip (a chip having flow channels on the order of micrometers) or a flow cell. The width of the flow channel C may be 1 mm or less, and in particular, 10 μm or more and 1 mm or less. The flow channel C and the flow channel structure including it may be made of a material such as plastic or glass.

[0048] The biological sample analyzer of the present disclosure is configured so that light from light irradiation unit 111 is irradiated onto the biological sample flowing within flow path C, and particularly onto biological particles within the biological sample. The biological sample analyzer of the present disclosure may be configured so that the interrogation point of light on the biological sample is within the flow path structure in which flow path C is formed, or so that the interrogation point of light is outside the flow path structure. An example of the former is a configuration in which the light is irradiated onto flow path C within a microchip or flow cell. In the latter, the light may be irradiated onto biological particles after they have left the flow path structure (particularly its nozzle portion), and an example of this is a jet-in-air flow cytometer.

[0049] (Light irradiation part) The light irradiation unit 111 includes a light source unit that emits light and a light-guiding optical system that guides the light to an irradiation point. The light source unit includes one or more light sources. The type of light source is, for example, a laser light source or an LED. The wavelength of the light emitted from each light source may be any of ultraviolet light, visible light, and infrared light. The light-guiding optical system includes optical components such as a beam splitter group, a mirror group, or an optical fiber. The light-guiding optical system may also include a lens group for focusing light, such as an objective lens. There may be one or more irradiation points where the light intersects with the biological sample. The light irradiation unit 111 may be configured to focus light emitted from one or more different light sources to one irradiation point.

[0050] (Detection unit) The detection unit 112 includes at least one photodetector that detects light generated by irradiating the bioparticles with light. The detected light is, for example, fluorescence or scattered light (e.g., one or more of forward scattered light, back scattered light, and side scattered light). Each photodetector includes one or more light-receiving elements, and has, for example, a photodetector array. Each photodetector may include, as the light-receiving element, one or more PMTs (photomultiplier tubes) and / or photodiodes such as APDs and MPPCs. The photodetector includes, for example, a PMT array in which multiple PMTs are arranged in a one-dimensional direction. The detection unit 112 may also include an imaging element such as a CCD or CMOS. The detection unit 112 can acquire images of the bioparticles (e.g., bright-field images, dark-field images, and fluorescence images) using the imaging element.

[0051] The detection unit 112 includes a detection optical system that allows light of a predetermined detection wavelength to reach a corresponding photodetector. The detection optical system includes a spectroscopic unit such as a prism or a diffraction grating, or a wavelength separation unit such as a dichroic mirror or an optical filter. The detection optical system is configured to, for example, disperse light generated by irradiating bioparticles with light, and detect the dispersed light using a plurality of photodetectors, the number of which is greater than the number of fluorescent dyes with which the bioparticles are labeled. A flow cytometer that includes such a detection optical system is called a spectral flow cytometer. The detection optical system is also configured to, for example, separate light corresponding to the fluorescent wavelength range of a specific fluorescent dye from the light generated by irradiating bioparticles with light, and detect the separated light using a corresponding photodetector.

[0052] Furthermore, the detection unit 112 may include a signal processing unit that converts the electrical signal obtained by the photodetector into a digital signal. The signal processing unit may include an A / D converter as a device that performs the conversion. The digital signal obtained by the conversion by the signal processing unit may be transmitted to the information processing unit 113. The digital signal may be handled by the information processing unit 113 as data related to light (hereinafter also referred to as "light data"). The light data may be light data including, for example, fluorescent light data. More specifically, the light data may be light intensity data, and the light intensity may be light intensity data of light including fluorescent light (which may include feature quantities such as area, height, and width).

[0053] (Information Processing Department) The information processing unit 113 includes, for example, a processing unit that processes various data (e.g., optical data) and a storage unit that stores various data. When the processing unit acquires optical data corresponding to a fluorescent dye from the detection unit 112, the processing unit may perform fluorescence spillover correction (compensation processing) on ​​the light intensity data. Furthermore, in the case of a spectral flow cytometer, the processing unit executes fluorescence separation processing on the optical data to acquire light intensity data corresponding to the fluorescent dye. The fluorescence separation processing may be performed, for example, according to the unmixing method described in Japanese Patent Application Laid-Open No. 2011-232259. When the detection unit 112 includes an image sensor, the processing unit may acquire morphological information of bioparticles based on images acquired by the image sensor. The storage unit may be configured to store the acquired optical data. The storage unit may further be configured to store spectral reference data used in the unmixing processing.

[0054] If biological sample analyzer 11 includes fractionating unit 114 (described below), information processing unit 113 can determine whether to fractionate bioparticles based on the optical data and / or morphological information. Information processing unit 113 can then control fractionating unit 114 based on the result of this determination, allowing fractionating unit 114 to fractionate the bioparticles.

[0055] The information processing unit 113 may be configured to be able to output various data (e.g., optical data or images). For example, the information processing unit 113 may output various data (e.g., two-dimensional plots, spectral plots, etc.) generated based on the optical data. The information processing unit 113 may also be configured to be able to accept input of various data, for example, accepting gating processing on a plot by a user. The information processing unit 113 may include an output unit (e.g., a display, etc.) or an input unit (e.g., a keyboard, etc.) for executing the output or input.

[0056] The information processing unit 113 may be configured as a general-purpose computer, for example, as an information processing device including a CPU, RAM, and ROM. The information processing unit 113 may be included in a housing that includes the light irradiation unit 111 and the detection unit 112, or may be located outside the housing. Furthermore, various processes or functions performed by the information processing unit 113 may be realized by a server computer or a cloud connected via a network.

[0057] (Preparative separation section) The sorting unit 114 sorts the bioparticles according to the determination result by the information processing unit 113. The sorting method may be a method of generating droplets containing bioparticles by vibration, applying an electric charge to the droplets to be sorted, and controlling the direction of travel of the droplets with electrodes. The sorting method may also be a method of controlling the direction of travel of the bioparticles within the flow channel structure to perform sorting. The flow channel structure is provided with, for example, a control mechanism using pressure (spray or suction) or electric charge. An example of such a flow channel structure is a chip (for example, the chip described in JP 2020-76736 A) having a flow channel structure in which a flow channel C branches into a recovery flow channel and a waste flow channel downstream, and specific bioparticles are recovered into the recovery flow channel.

[0058] <Configuration example of information processing unit 113> FIG. 5 shows an example of the functional configuration of the information processing unit 113 of the biological sample analyzer 11 of FIG.

[0059] The information processing unit 113 includes an input unit 201 , a control unit 202 , an output unit 203 , a communication unit 204 , a reference DB 205 , and a storage unit 206 .

[0060] The input section 201 is equipped with various input devices for inputting data to and operating the biological sample analyzer 11.

[0061] The control unit 202 controls each unit of the information processing unit 113 and executes various processes. The control unit 202 includes an analysis pre-processing unit 221 and an analysis unit 222.

[0062] The analysis pre-processing unit 221 performs pre-processing before performing analysis of the optical data of the multi-stained particle sample supplied from the detection unit 112. For example, the analysis pre-processing unit 221 adjusts the SR of each dye stored in the reference DB 205.

[0063] The analysis unit 222 performs various analytical processes on the optical data of the multi-dyed particle sample supplied from the detection unit 112 using the SR of each dye stored in the reference DB 205 .

[0064] The output unit 203 includes an output device capable of outputting various types of information, such as a display device such as a display, an audio output device such as a speaker, etc. For example, the output unit 203 outputs analysis information indicating the analysis results of the optical data of the multi-dyed particle sample.

[0065] The communication unit 204 communicates with the server 12 and the like via a network (not shown).

[0066] The reference DB 205 stores reference data relating to the SR of each dye.

[0067] The storage unit 206 stores data and programs required for processing by the information processing unit 113 .

[0068] <Configuration Example of Analysis Preprocessing Unit 221> Fig. 6 shows an example of the functional configuration of the analysis pre-processing unit 221 in Fig. 5. The analysis pre-processing unit 221 includes an unmixing unit 251, an axis conversion unit 252, a gating unit 253, an evaluation index calculation unit 254, and an SR adjustment unit 255.

[0069] The unmixing unit 251 performs an unmixing process on the optical data of the multi-dyed particle sample supplied from the detection unit 112, using the SR of each dye stored in the reference DB 205. This allows the light intensity for each dye of each biological particle (multi-dyed particle) contained in the multi-dyed particle sample to be calculated individually. The unmixing unit 251 supplies information indicating the light intensity for each dye of each biological particle to the axis conversion unit 252.

[0070] The axis conversion unit 252 performs axis conversion of the light intensity for each pigment of each bioparticle. For example, the axis conversion unit 252 performs biexponential conversion of the light intensity for each pigment of each bioparticle. The axis conversion unit 252 supplies information individually indicating the light intensity for each pigment of each bioparticle after axis conversion to the gating unit 253, the evaluation index calculation unit 254, and the SR adjustment unit 255.

[0071] The gating unit 253 performs gating of the bioparticles in the multi-dyed particle sample for each dye based on the distribution of light intensity for each dye of each bioparticle after axis conversion. The gating unit 253 supplies information indicating the gating results for each dye to the evaluation index calculation unit 254 and the SR adjustment unit 255.

[0072] The evaluation index calculation unit 254 calculates a leakage evaluation index for each dye based on the light intensity distribution for each dye of each bioparticle after axis conversion and the gating results for each dye. The leakage evaluation index is an index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes. The evaluation index calculation unit 254 supplies information indicating the leakage evaluation index for each dye to the SR adjustment unit 255.

[0073] The SR adjustment unit 255 adjusts the SR of each dye stored in the reference DB 205 based on the light intensity distribution for each dye of each bioparticle after axis conversion, the gating results for each dye, and the spillover evaluation index for each dye. The SR adjustment unit 255 supplies the adjusted SR of each dye to the unmixing unit 251 and stores it in the reference DB 205 as needed. The SR adjustment unit 255 also selects a dye to use in SR adjustment and notifies the axis conversion unit 252 of the selected dye.

[0074] <Experimental Procedure> FIG. 7 shows an example of the procedure for an experiment using the biological sample analyzer 11.

[0075] In step S1, a hypothesis to be verified in an experiment is set.

[0076] In step S2, an experimental protocol is created. At this time, a panel design is constructed for biological sample analyzer 11. That is, an optimal combination of multiple labeling substances (for example, dyes) to be used in the experiment is designed.

[0077] In step S3, the equipment to be used in the experiment is set.

[0078] In step S4, reference data including data on the SR of each dye is acquired. The acquired reference data is stored in the reference DB 205.

[0079] In step S5, light generated by irradiating the bioparticles contained in the multi-dyed particle sample with light is measured, thereby obtaining experimental data including optical data of the multi-dyed particle sample.

[0080] In step S6, pre-analysis processing is performed, whereby the SR of each dye contained in the reference data is adjusted based on the experimental data.

[0081] In step S7, the adjusted SR of each dye is used to analyze the experimental data, for example, by a normal user, by machine learning, or by supporting normal analysis with machine learning.

[0082] In step S8, the experimental data is summarized, for example, by compiling an experimental report including the analysis results of the experimental data.

[0083] In step S9, the experiment data is shared, for example, the experiment report is made public on the server 12, or the experiment report is presented.

[0084] Note that this technology is mainly directed to the processing in step S6.

[0085] <First embodiment of analysis preprocessing> Next, a first embodiment of the pre-analysis process in step S6 of FIG. 7 will be described with reference to the flowchart of FIG.

[0086] In the first embodiment of the pre-analysis process, the SR of each dye is adjusted using an orthogonality evaluation index as a contamination evaluation index. Details of the contamination evaluation index and the orthogonality evaluation index will be described later.

[0087] In step S101, the unmixing unit 251 performs an unmixing process. Specifically, the unmixing unit 251 performs an unmixing process on the multi-dyed particle sample included in the experimental data using the SR of each dye stored in the reference DB 205. This calculates the light intensity for each dye of each biological particle (multi-dyed particle) included in the multi-dyed particle sample. The unmixing unit 251 supplies information individually indicating the light intensity for each dye of each biological particle to the axis conversion unit 252.

[0088] In step S102, the SR adjustment unit 255 selects a dye to be used for adjusting the SR. For example, the SR adjustment unit 255 selects one of the dyes for which the orthogonality of the two-dimensional plot has not yet been evaluated as the dye to be evaluated. For example, the SR adjustment unit 255 selects one of the dyes for which the SR has not yet been adjusted as the dye to be adjusted. The SR adjustment unit 255 notifies the axis conversion unit 252 of the selected dye to be evaluated and the dye to be adjusted.

[0089] In step S103, the axis conversion unit 252 performs axis conversion. For example, the axis conversion unit 252 performs biexponential conversion on the light intensities of the evaluation target dye and the adjustment target dye of each bioparticle. The axis conversion unit 252 supplies information individually indicating the light intensities of the evaluation target dye and the adjustment target dye of each bioparticle after the axis conversion to the gating unit 253, the evaluation index calculation unit 254, and the SR adjustment unit 255.

[0090] In step S104, the gating unit 253 performs gating. Specifically, the gating unit 253 performs gating of bioparticles in the multi-dyed particle sample based on a graph showing the distribution of light intensity for the evaluation target dye of each bioparticle after axis conversion (hereinafter referred to as a light intensity distribution graph).

[0091] This sets a boundary (hereinafter referred to as a positive-negative boundary) that separates a cluster containing bioparticles that reacted positively to the dye to be evaluated (hereinafter referred to as positive particles) from a cluster containing bioparticles that reacted negatively (hereinafter referred to as negative particles).Then, the bioparticles in the multi-stained particle sample are separated into a cluster containing positive particles (hereinafter referred to as a positive cluster) and a cluster containing negative particles (hereinafter referred to as a negative cluster).

[0092] The method for setting the positive / negative boundary is not particularly limited, but the positive / negative boundary is set so that the variance in light intensity between the positive and negative populations is large and the variance in light intensity within each population is small.

[0093] For example, the gating unit 253 sets the positive / negative boundary using a clustering method such as Otsu's rule, silhouette analysis, or K-means method.

[0094] It should be noted that, for example, the user may manually set the positive / negative boundary.

[0095] For example, Fig. 9 shows an example of setting the positive / negative boundary. Fig. 9A and Fig. 9B show examples of light intensity distribution graphs (histograms) for the dye to be evaluated. The horizontal axis of Fig. 9A and Fig. 9B indicates the light intensity after axis conversion, and the vertical axis indicates the number of particles.

[0096] For example, when Otsu's law is used, the positive / negative boundary may be set to the value shown by the dotted line in A of Fig. 9, contrary to the user's intention. In this case, for example, the user may manually adjust the value of the positive / negative boundary, as shown in B of Fig. 9.

[0097] Similarly, the gating unit 253 performs gating of bioparticles in the multi-dyed particle sample based on the light intensity distribution graph for the dye to be adjusted for each bioparticle.

[0098] This sets a positive / negative boundary for the dye to be adjusted, and separates the biological particles in the multi-stained particle sample into a positive population and a negative population for the dye to be adjusted.

[0099] The gating unit 253 supplies the evaluation index calculation unit 254 and the SR adjustment unit 255 with information indicating the results of gating the bioparticles in the multi-stained particle sample for the dye to be evaluated and the dye to be adjusted.

[0100] In step S105, the evaluation index calculation unit 254 calculates an orthogonal evaluation index. Specifically, the evaluation index calculation unit 254 calculates an orthogonal evaluation index that indicates the orthogonality of the light intensity for the dye to be evaluated in a two-dimensional plot that shows the distribution of the light intensity for the dye to be evaluated of the bioparticles in the multi-stained particle sample and the light intensity for the dye to be adjusted. For example, the evaluation index calculation unit 254 calculates a Stain Index (SI), a Signal Separation (SS), or a Spillover Spread Matrix (SSM) as the orthogonal evaluation index.

[0101] For example, the SI for the dye to be evaluated is calculated by the following formula (1).

[0102] SI={median(posi)-median(nega)} / {2×σ(nega)} ···(1)

[0103] Note that median(posi) is the median of the light intensity of bioparticles in the positive population for the dye being evaluated, median(nega) is the median of the light intensity of bioparticles in the negative population for the dye being evaluated, and σ(nega) is the standard deviation of the light intensity of bioparticles in the negative population for the dye being evaluated.

[0104] For example, the SS for the dye to be evaluated is calculated by the following formula (2).

[0105] SS={mean(posi)-mean(nega)} / {σ(posi)-σ(nega)} ···(2)

[0106] mean(posi) is the average light intensity of bioparticles in the positive population for the dye being evaluated. mean(nega) is the average light intensity of bioparticles in the negative population for the dye being evaluated. σ(posi) is the standard deviation of the light intensity of bioparticles in the positive population for the dye being evaluated.

[0107] The evaluation index calculation unit 254 supplies the SR adjustment unit 255 with information indicating the orthogonal evaluation index for the dye to be evaluated.

[0108] In step S106, the analysis pre-processing unit 221 executes an SR adjustment process.

[0109] Here, the SR adjustment process will be described in detail with reference to the flowchart of FIG.

[0110] In step S151, the SR adjustment unit 255 adjusts the SR. Specifically, the SR adjustment unit 255 detects the unmixing state for the evaluation target dye based on the light intensity distribution for the evaluation target dye and the adjustment target dye of each bioparticle after axis conversion, and the results of gating bioparticles in the multi-stained particle sample for the evaluation target dye and the adjustment target dye. For example, the SR adjustment unit 255 adjusts the SR of the adjustment target dye using the SR of the evaluation target dye based on the orthogonal evaluation index for the evaluation target dye and the unmixing state for the evaluation target dye. The SR adjustment unit 255 supplies the adjusted SR of the adjustment target dye to the unmixing unit 251.

[0111] The method for adjusting the SR will be described in detail later.

[0112] In step S152, an unmixing process is executed, similar to the process in step S101 of Fig. 8. At this time, the adjusted SR supplied from the SR adjustment unit 255 is used as the SR of the dye to be adjusted, and the SR stored in the reference DB 205 is used as the SR of the other dyes.

[0113] In steps S153 to S155, the same processing as in steps S103 to S105 in Fig. 8 is performed. As a result, the orthogonality evaluation index for the evaluation target dye is calculated using the SR of each color including the adjusted SR of the adjustment target dye.

[0114] In step S156, the evaluation index calculation unit 254 determines whether the orthogonality evaluation index satisfies the termination condition. If it is determined that the orthogonality evaluation index does not satisfy the termination condition, the process returns to step S151.

[0115] Thereafter, the processes of steps S151 to S156 are repeatedly executed until it is determined in step S156 that the orthogonal evaluation index satisfies the termination condition, thereby adjusting the SR of the dye to be adjusted so that the orthogonal evaluation index for the dye to be evaluated satisfies the termination condition.

[0116] On the other hand, if it is determined in step S156 that the orthogonality evaluation index satisfies the termination condition, the process proceeds to step S157.

[0117] Here, an example of a method for adjusting SR will be described with reference to FIGS.

[0118] FIG. 11 shows an example of a two-dimensional plot of light intensity for Dye 1 and Dye 2, as well as the SI for Dye 1 and Dye 2.

[0119] The vertical axis of each two-dimensional plot in FIG. 11 is the light intensity for dye 1 after axis transformation, and the horizontal axis is the light intensity for dye 2 after axis transformation.

[0120] The two-dimensional plots arranged horizontally at the bottom of Fig. 11 show an example of the change in the two-dimensional plot with respect to the unmixing state for dye 1 (vertical axis). The horizontal dotted auxiliary line L1 indicates the center of gravity (median) of the light intensity distribution in the vertical axis (dye 1) direction in a population of bioparticles that are negative for dye 1 and dye 2 (hereinafter referred to as the Nega-Nega population), for example.

[0121] The bar graph at the bottom center of Figure 11 shows an example of the change in SI with the unmixing state for dye 1.

[0122] When unmixing for dye 1 is optimal, the light intensity for dye 1 in the dye 1-negative population is approximately the same, regardless of the light intensity for dye 2. In this case, the SI for dye 1 is maximized.

[0123] On the other hand, in the case of over-unmixing of dye 1, the light intensity for dye 1 in the population negative for dye 1 weakens as the light intensity for dye 2 strengthens. That is, the light intensity for dye 1 in the population negative for dye 1 changes in the negative direction (- direction) with respect to auxiliary line L1 as the light intensity for dye 2 strengthens. This is, for example, a state in which the light intensity for dye 1 of a bioparticle that is negative for dye 1 and positive for dye 2 leaks into the negative direction. In this case, the SI for dye 1 decreases as the degree of over-unmixing increases, in other words, as the amount of light intensity for dye 1 leaking into the negative direction of a bioparticle that is negative for dye 1 and positive for dye 2 increases.

[0124] Furthermore, in the case of under-unmixing for dye 1, the light intensity for dye 1 in the population negative for dye 1 increases as the light intensity for dye 2 increases. That is, the light intensity for dye 1 in the population negative for dye 1 changes in the positive direction (+ direction) with respect to auxiliary line L1 as the light intensity for dye 2 increases. This is, for example, a state in which the light intensity for dye 1 of a bioparticle that is negative for dye 1 and positive for dye 2 leaks into the positive direction. In this case, the SI for dye 1 decreases as the degree of under-unmixing increases, in other words, as the amount of light intensity for dye 1 leaking into the positive direction of a bioparticle that is negative for dye 1 and positive for dye 2 increases.

[0125] For example, the leakage evaluation index for dye 1 is an index for evaluating the degree to which light corresponding to dye 2 leaks into light corresponding to dye 1. Specifically, for example, the leakage evaluation index for dye 1 is an index for evaluating the degree to which the distribution of light intensity in a group of bioparticles that are negative for dye 1 and positive for dye 2 leaks into the auxiliary line L1 in a positive or negative direction.

[0126] For example, the orthogonal evaluation index for dye 1 is a type of spillover evaluation index, and is an index that indicates the degree to which the distribution of light intensity in a group of bioparticles that are negative for dye 1 is orthogonal to the vertical axis (axis of dye 1). SI, SS, or SSM can be used as the orthogonal evaluation index for dye 1.

[0127] The two-dimensional plots arranged vertically on the left side of Figure 11 show an example of the change in the two-dimensional plot depending on the unmixing state for dye 2 (horizontal axis). The vertical dotted auxiliary line L2 indicates, for example, the position of the center of gravity of the light intensity distribution in the Nega-Nega population along the horizontal axis (dye 2).

[0128] The upper bar graph in the center of Figure 11 shows an example of the change in SI with the unmixing state for dye 2.

[0129] When unmixing for dye 2 is optimal, the light intensity for dye 2 within the dye 2-negative population is approximately the same, regardless of the light intensity for dye 1. In this case, the SI for dye 2 is maximized.

[0130] On the other hand, in the case of over-unmixing for dye 2, the light intensity for dye 2 in the dye-negative group weakens as the light intensity for dye 1 strengthens. That is, the light intensity for dye 2 in the dye-negative group changes in the negative direction (- direction) with respect to auxiliary line L2 as the light intensity for dye 1 strengthens. This is, for example, a state in which the light intensity for dye 2 of a bioparticle that is positive for dye 1 and negative for dye 2 leaks into the negative direction. In this case, the SI for dye 2 decreases as the degree of over-unmixing increases, in other words, as the amount of light intensity for dye 2 leaking into the negative direction of a bioparticle that is positive for dye 1 and negative for dye 2 increases.

[0131] Furthermore, in the case of under-unmixing for dye 2, the light intensity for dye 2 in the population negative for dye 2 increases as the light intensity for dye 1 increases. That is, the light intensity for dye 2 in the population negative for dye 2 changes in the positive direction (+ direction) with respect to auxiliary line L2 as the light intensity for dye 1 increases. This is, for example, a state in which the light intensity for dye 2 of a bioparticle that is positive for dye 1 and negative for dye 2 leaks into the positive direction. In this case, the SI for dye 2 decreases as the degree of under-unmixing increases, in other words, as the amount of light intensity for dye 2 leaking into the positive direction of a bioparticle that is positive for dye 1 and negative for dye 2 increases.

[0132] For example, the leakage evaluation index for dye 2 is an index for evaluating the degree to which light corresponding to dye 1 leaks into light corresponding to dye 2. Specifically, for example, the leakage evaluation index for dye 2 is an index for evaluating the amount of leakage of the light intensity distribution in a group of bioparticles that are positive for dye 1 and negative for dye 2 in the positive or negative direction with respect to auxiliary line L2.

[0133] For example, the orthogonal evaluation index for dye 2 is a type of spillover evaluation index, and is an index that indicates the degree to which the distribution of light intensity in a group of bioparticles that are negative for dye 2 is orthogonal to the horizontal axis (axis of dye 2). SI, SS, or SSM can be used as the orthogonal evaluation index for dye 2.

[0134] In response to this, the SR adjustment unit 255 adjusts the SR of the dye to be adjusted so as to improve the orthogonal evaluation index for the dye to be evaluated.

[0135] For example, A to E in Fig. 12 schematically show two-dimensional plots of light intensity for the dye to be evaluated and the dye to be adjusted. The vertical axis of the two-dimensional plot represents the light intensity for the dye to be evaluated after axis transformation, and the horizontal axis represents the light intensity for the dye to be adjusted after axis transformation.

[0136] The hatched ellipses A to E in Fig. 12 schematically show the light intensity distribution of a population of bioparticles that are negative for the dye to be evaluated and the dye to be adjusted (Nega-Nega population). The dotted ellipses A to E in Fig. 12 schematically show the light intensity distribution of a population of bioparticles that are positive for the dye to be evaluated and negative for the dye to be adjusted (hereinafter referred to as Posi-Nega population). The open ellipses A to E in Fig. 12 schematically show the light intensity distribution of a population of bioparticles that are negative for the dye to be evaluated and positive for the dye to be adjusted (hereinafter referred to as Nega-Posi population).

[0137] The light intensity distribution of a group of bioparticles that are positive for the dye to be evaluated and the dye to be adjusted (hereinafter referred to as a Posi-Posi group) is omitted from the illustration.

[0138] For example, as shown in A of FIG. 12, when the dye to be evaluated is in an under-unmixing state, the SR adjustment unit 255 adjusts the SR2 of the current dye to be adjusted to SR2r1 using the following equation (3).

[0139] SR2r1=SR2+αSR1 (3)

[0140] That is, SR1 of the dye to be evaluated is added to SR2 of the current dye to be adjusted with a weight α.

[0141] As a result, for example, as shown in B of FIG. 12, the result of unmixing the dye to be evaluated using the adjusted SR2r1 becomes over-unmixing.

[0142] In response to this, the SR adjustment unit 255 adjusts the SR2r1 of the current adjustment target pigment to SR2r2 using the following equation (4).

[0143] SR2r2=SR2r1-βSR1 (4)

[0144] That is, SR1 of the dye to be evaluated is subtracted from SR2r1 of the current dye to be adjusted with a weight β.

[0145] As a result, for example, as shown in C of FIG. 12, the result of unmixing the dye to be evaluated using the adjusted SR2r2 is under-unmixing.

[0146] In response to this, the SR adjustment unit 255 adjusts the SR2r2 of the current adjustment target pigment to SR2r3 using the following equation (5).

[0147] SR2r3=SR2r2+γSR1 (5)

[0148] That is, SR1 of the dye to be evaluated is added to SR2r2 of the current dye to be adjusted with a weight γ.

[0149] As a result, for example, as shown in D of FIG. 12, the result of unmixing the dye to be evaluated using the adjusted SR2r3 becomes over-unmixing.

[0150] In response to this, the SR adjustment unit 255 adjusts the SR2r3 of the current adjustment target pigment to SR2r4 using the following equation (6).

[0151] SR2r4=SR2r3-ΔSR1 (6)

[0152] That is, SR1 of the dye to be evaluated is subtracted from SR2r2 of the current dye to be adjusted with a weight Δ.

[0153] This brings the unmixing of the dye to be evaluated into an appropriate state, and SR2r4 at this time is updated as the SR of the dye to be adjusted after adjustment.

[0154] The weights used to adjust the SR (for example, weights α to Δ) are adjusted based on the degree of under-unmixing or over-unmixing for the dye to be evaluated. For example, the SR adjustment coefficient is set based on the difference (hereinafter referred to as the center of gravity difference) between the center of gravity in the vertical axis (dye to be evaluated) direction in the light intensity distribution of the Nega-Nega group and the center of gravity in the vertical axis (dye to be evaluated) direction in the light intensity distribution of the Nega-Posi group.

[0155] For example, as the centroid difference increases in the positive direction, i.e., as the degree of under-unmixing for the evaluation target dye increases, the weight sign is set to be positive and the absolute value of the weight is increased, thereby increasing the amount by which the SR of the evaluation target dye is added to the SR of the adjustment target dye.

[0156] On the other hand, as the difference in the center of gravity becomes larger in the negative direction, i.e., as the degree of over-unmixing for the dye to be evaluated increases, the sign of the weight is set to negative and the absolute value of the weight is increased, thereby increasing the amount by which the SR of the dye to be evaluated is subtracted from the SR of the dye to be adjusted.

[0157] Fig. 13 shows an example of a change in SI for a dye to be evaluated as the SR of the dye to be adjusted is adjusted. The vertical axis of Fig. 13A shows the SI for the dye to be evaluated, and the horizontal axis shows the weights (e.g., the weights α and β described above) used to adjust the SR of the dye to be adjusted. The vertical axis of Fig. 13B shows the SI for the dye to be evaluated, and the horizontal axis shows the number of times the SR of the dye to be adjusted is adjusted.

[0158] In this way, as the SR of the dye to be adjusted is adjusted, the SI for the dye to be evaluated increases. Then, for example, in step S156, when the SI for the dye to be evaluated reaches near its peak, the SR adjustment unit 255 determines that the orthogonality evaluation index satisfies the termination condition, and the process proceeds to step S157.

[0159] In some cases, the SI for the dye to be evaluated may decrease after reaching a peak. In this case, for example, the SR for the dye to be adjusted is finally set to the SR immediately before the SI decreases.

[0160] In this manner, the SR of the dye to be adjusted is adjusted so that the SI for the dye to be evaluated is as large as possible.

[0161] Although detailed explanation is omitted, when SS is used as the orthogonality evaluation index, the SR of the dye to be adjusted is adjusted so that the SS for the dye to be evaluated becomes as large as possible.

[0162] In this way, the SR of the dye to be adjusted is adjusted so that the orthogonality of the light intensity distribution to the dye to be evaluated is as high as possible.

[0163] 10, in step S157, the SR adjustment unit 255 saves the adjusted SR. For example, the SR adjustment unit 255 updates the SR of the dye to be adjusted stored in the reference DB 205 with the adjusted SR.

[0164] Then, the SR adjustment process ends.

[0165] For example, in the SR adjustment process, after the SR of the dye to be adjusted is adjusted, the dye to be evaluated and the dye to be adjusted may be swapped, and the SR of the dye to be adjusted after the swap (the dye to be evaluated before the swap) may continue to be adjusted.

[0166] 8, in step S107, the SR adjustment unit 255 determines whether the SRs of all the dyes have been adjusted. If it is determined that the SRs of all the dyes have not yet been adjusted, the process returns to step S101.

[0167] Thereafter, in step S107, the processes of steps S101 to S107 are repeatedly executed until it is determined that the SRs of all the dyes have been adjusted.

[0168] On the other hand, if it is determined in step S107 that the SRs of all the dyes have been adjusted, the pre-analysis process ends.

[0169] <Modification of orthogonality evaluation index> Next, a modified example of the orthogonality evaluation index will be described with reference to FIGS.

[0170] 14A and 14B show examples of two-dimensional plots of light intensity for dye 1 and dye 2. The vertical axis of FIG. 14A and 14B represents the light intensity for dye 1 after axis transformation, and the horizontal axis represents the light intensity for dye 2 after axis transformation.

[0171] For example, the slope of the two-dimensional plot may be used as an orthogonality evaluation index.

[0172] Specifically, for example, the slope of a straight line L11 connecting the center of gravity of the vertical axis (dye 1) of the light intensity distribution in the Nega-Nega group and the center of gravity of the vertical axis (dye 1) of the light intensity distribution in the Nega-Posi group may be used as an orthogonality evaluation index for dye 1.

[0173] In this case, for example, the SR of dye 2 is adjusted so that the slope of the line L11 approaches zero.

[0174] For example, the slope of the line L12 connecting the center of gravity of the horizontal axis (dye 2) of the light intensity distribution in the Nega-Nega group and the center of gravity of the horizontal axis (dye 2) of the light intensity distribution in the Posi-Nega group may be used as an orthogonality evaluation index for dye 2.

[0175] In this case, for example, the SR of dye 1 is adjusted so that the slope of line L12 approaches infinity. Note that, because it is difficult to make the slope of line L12 approach infinity, the vertical and horizontal axes may be interchanged, and the SR of dye 1 may be adjusted so that the slope of line L12 approaches zero.

[0176] 14A shows a case where unmixing for dye 2 is appropriate, and FIG. 14B shows a state where dye 2 is under-unmixed.

[0177] Furthermore, instead of the center of gravity of the distribution of light intensity in the Nega-Nega group, the Nega-Posi group, and the Posi-Nega group, the average may be used.

[0178] Figure 15 shows contour-marked two-dimensional plots of light intensity for dye 1 and dye 2. The vertical axis of Figures 15A and 15B represents the light intensity for dye 1 after axis transformation, and the horizontal axis represents the light intensity for dye 2 after axis transformation.

[0179] For example, approximate lines L21 and L22 that trace the ridges of the two-dimensional plot may be calculated by the least squares method and used as the orthogonality evaluation index.

[0180] For example, the approximate line L21 is used as an orthogonality evaluation index for dye 1. In this case, the SR of dye 2 is adjusted so that the slope of the approximate line L22 approaches zero.

[0181] For example, the approximate line L22 is used as an orthogonal evaluation index for dye 2. In this case, the SR of dye 1 is adjusted so that the slope of the approximate line L21 approaches infinity. Note that, because it is difficult to make the slope of the approximate line L21 approach infinity, the vertical and horizontal axes may be interchanged, and the SR of dye 1 may be adjusted so that the slope of the approximate line L21 approaches zero.

[0182] In this case, gating processing for dye 1 and dye 2 becomes unnecessary.

[0183] 15A shows a case where unmixing for dye 2 is appropriate, and FIG. 15B shows a state where dye 2 is under-unmixed.

[0184] When the slope of the two-dimensional plot is used as the orthogonality evaluation index as in FIGS. 14 and 15, it becomes possible to clearly define the termination condition of the orthogonality evaluation index described above.

[0185] In this way, the SR of each dye can be easily and appropriately adjusted using the orthogonal evaluation index. For example, manual SR adjustment is no longer necessary, reducing the user's workload and suppressing variations in the SR adjustment results for each user. As a result, for example, the TAT (Turnaround Time) required for analyzing experimental data can be reduced, and the quality of the analysis results can be improved.

[0186] Furthermore, by adjusting the generated SR, it can be used for the same FCM, different FCMs of the same model, and FCMs of different models, thereby expanding the range of application of the SR.

[0187] <Second embodiment of pre-analysis processing> Next, a second embodiment of the pre-analysis process in step S6 of FIG. 7 will be described with reference to the flowchart of FIG.

[0188] In the second embodiment of the analysis pre-processing, the SR of each dye is adjusted using a dependency evaluation index, which is an index for evaluating dependency between dyes, as a leakage evaluation index.

[0189] In step S201, an unmixing process is performed in the same manner as in step S101 in FIG.

[0190] In step S202, the axis conversion unit 252 performs axis conversion. For example, the axis conversion unit 252 performs biexponential conversion on the light intensity for each pigment of each bioparticle by the same process as in step S102 of Fig. 8. The axis conversion unit 252 supplies information individually indicating the light intensity for each pigment of each bioparticle after the axis conversion to the gating unit 253 and the evaluation index calculation unit 254.

[0191] In step S203, the gating unit 253 performs gating. Specifically, the gating unit 253 performs gating of bioparticles in the multi-stained particle sample for each dye based on a light intensity distribution graph showing the distribution of light intensity for each dye of each bioparticle after axis conversion, using processing similar to that of step S103 in FIG. 8. This sets a positive / negative boundary for each dye, and the bioparticles in the multi-stained particle sample are separated into positive and negative populations for each dye. The gating unit 253 supplies information indicating the results of gating the bioparticles in the multi-stained particle sample for each dye to the evaluation index calculation unit 254.

[0192] In step S204, the evaluation index calculation unit 254 calculates a dependency evaluation index. For example, for each combination of dyes, the evaluation index calculation unit 254 calculates a correlation coefficient that quantifies the dependency of light intensity between two dyes as the dependency evaluation index.

[0193] For example, Figure 17 shows an example of a two-dimensional plot of light intensity between two dyes. For example, the evaluation index calculation unit 254 calculates the correlation coefficient between two dyes in a population of bioparticles within a frame. The population of bioparticles within the frame is a negative-positive population that includes bioparticles that are negative for the dye on the vertical axis (hereinafter referred to as the vertical axis dye) and positive for the dye on the horizontal axis (hereinafter referred to as the horizontal axis dye). In other words, the evaluation index calculation unit 254 calculates the correlation coefficient between the light intensity for the vertical axis dye and the light intensity for the horizontal axis dye in the negative-positive population.

[0194] For example, the evaluation index calculation unit 254 calculates the correlation coefficient of the light intensity of bioparticles in the Negativity-Positive population for all combinations of dyes.

[0195] In the following, for example, the correlation coefficient between the light intensity for dye 1 and the light intensity for dye 2 in a negative-positive population containing bioparticles that are negative for dye 1 (vertical axis dye) and positive for dye 2 (horizontal axis dye) will be simply referred to as the correlation coefficient between dye 1 and dye 2.

[0196] 18 shows an example of the correlation coefficients between dyes 1 to 5. The vertical axis indicates the vertical axis dye of the two-dimensional plot, and the horizontal axis indicates the horizontal axis dye of the two-dimensional plot.

[0197] For example, the correlation coefficient between pigment 1 (vertical axis pigment) and pigment 2 (horizontal axis pigment) is -0.1101. For example, the correlation coefficient between pigment 1 and pigment 3 is -0.1517. For example, the correlation coefficient between pigment 1 and pigment 4 is -0.1836. For example, the correlation coefficient between pigment 1 and pigment 5 is -0.9477.

[0198] Note that Figure 17 above shows an example of a two-dimensional plot used to calculate the correlation coefficient between dye 3 and dye 5 in Figure 18. In this example, unmixing for dye 3 (vertical axis dye) is appropriate. The correlation coefficient between dye 3 and dye 5 is 0.02931.

[0199] In this way, when unmixing is appropriate for the vertical axis dye, the absolute value of the correlation coefficient between the vertical axis dye and the horizontal axis dye becomes small.

[0200] Figure 19 shows an example of a two-dimensional plot used to calculate the correlation coefficient between dyes 4 and 5 in Figure 18. In this example, the unmixing for dye 4 is in an under-unmixing state. The correlation coefficient between dyes 4 and 5 is 0.9851.

[0201] In this way, when the vertical axis dye is in an under-unmixed state, the correlation coefficient between the vertical axis dye and the horizontal axis dye is usually a positive value. Furthermore, the stronger the positive correlation between the light intensity for the vertical axis dye and the light intensity for the horizontal axis dye, the larger the absolute value of the correlation coefficient between the vertical axis dye and the horizontal axis dye.

[0202] Figure 20 shows an example of a two-dimensional plot used to calculate the correlation coefficient between dye 4 and dye 2 in Figure 18. In this example, the unmixing for dye 4 is in an under-unmixing state. The correlation coefficient between dye 4 and dye 2 is 0.1148.

[0203] In this way, even if the state of under-unmixing for the vertical axis dye is large, if the positive correlation between the light intensity for the vertical axis dye and the light intensity for the horizontal axis dye is weak, the absolute value of the correlation coefficient between the vertical axis dye and the horizontal axis dye will be small.

[0204] Figure 21 shows an example of a two-dimensional plot used to calculate the correlation coefficient between dye 1 and dye 5 in Figure 18. In this example, the unmixing for dye 1 is in an over-unmixing state. The correlation coefficient between dye 1 and dye 5 is -0.9477.

[0205] In this way, when the vertical axis dye is in an over-unmixed state, the correlation coefficient between the vertical axis dye and the horizontal axis dye is usually a negative value. Furthermore, the stronger the negative correlation between the light intensity for the vertical axis dye and the light intensity for the horizontal axis dye, the larger the absolute value of the correlation coefficient between the vertical axis dye and the horizontal axis dye.

[0206] Figure 22 shows an example of a two-dimensional plot used to calculate the correlation coefficient between dye 1 and dye 2 in Figure 18. In this example, the unmixing for dye 1 is in an over-unmixing state. The correlation coefficient between dye 1 and dye 2 is -0.1101.

[0207] In this way, even if the state of over-unmixing for the vertical axis dye is large, if the negative correlation between the light intensity for the vertical axis dye and the light intensity for the horizontal axis dye is weak, the absolute value of the correlation coefficient between the vertical axis dye and the horizontal axis dye will be small.

[0208] In step S205, the evaluation index calculation unit 254 determines whether all dependency evaluation indexes satisfy the termination condition. For example, the evaluation index calculation unit 254 compares the absolute value of the correlation coefficient between each pigment with a predetermined threshold (e.g., 0.1). If the absolute value of at least one correlation coefficient is equal to or greater than the threshold, the evaluation index calculation unit 254 determines that all dependency evaluation indexes have not yet satisfied the termination condition, and the process proceeds to step S206.

[0209] In step S206, the SR adjustment unit 255 selects dyes to be used in adjusting the SR. Specifically, the evaluation index calculation unit 254 supplies information indicating the correlation coefficient between each dye to the SR adjustment unit 255. For example, the SR adjustment unit 255 selects the dye combination with the largest absolute value of the correlation coefficient as the dye to be used in adjusting the SR. Furthermore, the SR adjustment unit 255 sets the horizontal axis dye of the selected dye combination as the dye to be adjusted, and sets the vertical axis dye as the dye to be added or subtracted.

[0210] The adjustment target dye is a dye whose SR is to be adjusted, and the addition / subtraction target dye is a dye whose SR is to be added or subtracted by weighting the SR of the adjustment target dye.

[0211] For example, in the example of Figure 18, the absolute value of the correlation coefficient between pigment 4 and pigment 5 is the largest. Therefore, the combination of pigment 4 and pigment 5 is selected, pigment 5 is set as the pigment to be adjusted, and pigment 4 is set as the pigment to be added or subtracted.

[0212] Note that if a combination of two dyes is found to have a positive or negative correlation due to biological factors other than spillover, the SR adjustment unit 255 will not select such a combination of dyes. For example, if the dye to be added or subtracted is a CD3 marker and the dye to be adjusted is a T cell receptor marker present together with CD3, a positive correlation is inherently confirmed between these two markers, regardless of spillover. In response to this, the SR adjustment unit 255 will not select a combination of a CD3 marker and a T cell receptor marker present together with CD3.

[0213] In step S207, the analysis pre-processing unit 221 executes an SR adjustment process.

[0214] Here, the SR adjustment process will be described in detail with reference to the flowchart of FIG.

[0215] In step S251, the SR adjustment unit 255 adjusts the SR. Specifically, the SR adjustment unit 255 adjusts the SR of the dye to be adjusted (dye on the horizontal axis) by adding or subtracting the SR of the dye to be adjusted (dye on the vertical axis) with a weight to the SR of the dye to be adjusted (dye on the horizontal axis).

[0216] Specifically, when the correlation coefficient between the dye to be added or subtracted and the dye to be adjusted is a positive value, the SR adjustment unit 255 determines that the dye to be added or subtracted is in an under-unmixing state, and weights and adds the SR of the dye to the SR of the dye to be adjusted. At this time, the SR adjustment unit 255 increases the weight as the absolute value of the correlation coefficient increases.

[0217] On the other hand, if the correlation coefficient between the dye to be added or subtracted and the dye to be adjusted is a negative value, the SR adjustment unit 255 determines that the dye to be added or subtracted is in an over-unmixing state, and weights and subtracts the SR of the dye to be added or subtracted from the SR of the dye to be adjusted. At this time, the SR adjustment unit 255 increases the weight as the absolute value of the correlation coefficient increases.

[0218] In step S252, the unmixing process is performed in the same manner as in step S152 in Fig. 10. That is, the unmixing process is performed using the SR of each dye, including the SR of the dye to be adjusted after adjustment.

[0219] In step S253, axis conversion is performed in the same manner as in step S202 of Fig. 16. At this time, for example, axis conversion is performed only on the adjustment target dye and the addition / subtraction target dye.

[0220] In step S254, gating is performed in the same manner as in the process of step S203 in Fig. 16. At this time, for example, gating is performed only on the dyes to be adjusted and the dyes to be added or subtracted.

[0221] In step S255, a dependency evaluation index is calculated, similar to the processing in step S204 of Fig. 16. At this time, for example, only the correlation coefficient between the addition / subtraction target pigment and the adjustment target pigment is calculated. That is, the correlation coefficient between the addition / subtraction target pigment and the adjustment target pigment in the Negative-Positive group of a two-dimensional plot with the addition / subtraction target pigment as the vertical axis pigment and the adjustment target pigment as the horizontal axis pigment is calculated.

[0222] In step S256, the evaluation index calculation unit 254 determines whether the dependency evaluation index satisfies the termination condition. For example, the evaluation index calculation unit 254 compares the absolute value of the correlation coefficient calculated in the processing of step S255 with a predetermined threshold (e.g., 0.1). If the absolute value of the correlation coefficient is equal to or greater than the threshold, the evaluation index calculation unit 254 determines that the dependency evaluation index does not satisfy the termination condition, and the processing returns to step S251.

[0223] Thereafter, in step S256, the processes of steps S251 to S256 are repeatedly executed until it is determined that the dependency evaluation index satisfies the termination condition, thereby adjusting the SR of the adjustment target dye until the correlation coefficient between the adjustment target dye and the addition / subtraction target dye becomes less than a predetermined threshold.

[0224] On the other hand, in step S256, if the correlation coefficient is less than the threshold, the evaluation index calculation unit 254 determines that the dependency evaluation index satisfies the termination condition, and the process proceeds to step S257.

[0225] For example, if the under-unmixing state and the over-unmixing state are repeated even though the SR adjustment width is sufficiently small, the SR adjustment may be terminated even if the termination condition that the absolute value of the correlation coefficient is less than the threshold is not satisfied. That is, the loop process of steps S251 to S256 may be terminated, and the process may proceed to step S257.

[0226] In step S257, the adjusted SR is saved, similarly to the process in step S157 of FIG.

[0227] Then, the SR adjustment process ends.

[0228] Thereafter, the process returns to step S201 in FIG. 16, and steps S201 to S207 are repeatedly executed until it is determined in step S205 that all dependency evaluation indexes satisfy the termination condition.

[0229] As a result, the SR of the dyes on the horizontal axis is adjusted in descending order of the absolute value of the correlation coefficient.

[0230] For example, in the example of Figure 18, in the combination of pigment 4 and pigment 5, the SR of pigment 5 is adjusted, then in the combination of pigment 1 and pigment 5, the SR of pigment 5 is adjusted, and in the combination of pigment 2 and pigment 5, the SR of pigment 5 is adjusted.

[0231] Note that, since the correlation coefficient of each dye combination changes when the SR of dye 5 is adjusted, the SR adjustment is not necessarily performed in this order.

[0232] Figure 24 shows an example of the correlation coefficients between the dyes after adjusting the SR of dye 5. In this example, the absolute values ​​of the correlation coefficients between dye 1 and dye 3, between dye 2 and dye 3, and between dye 4 and dye 3 are large. Therefore, the SR of dye 3 is adjusted.

[0233] For example, in a combination of dye 1 and dye 3, the SR of dye 3 is adjusted, then in a combination of dye 4 and dye 3, the SR of dye 3 is adjusted, and then in a combination of dye 2 and dye 3, the SR of dye 3 is adjusted.

[0234] Note that, since the correlation coefficient of each dye combination changes when the SR of dye 3 is adjusted, the SR adjustment is not necessarily performed in this order.

[0235] 25 shows an example of the correlation coefficients between the dyes after adjusting the SR of dye 3. In this example, the correlation coefficients between the dyes are all at the threshold value (less than 0.1).

[0236] As a result, in step S205 of FIG. 16, it is determined that all dependency evaluation indexes satisfy the termination condition, and the analysis pre-processing ends.

[0237] In addition, for a combination of dyes whose dependency evaluation index once satisfied the termination condition, if the termination condition is no longer satisfied after adjusting the SR of other dyes, the SR may be adjusted again.

[0238] In this way, the SR of each dye can be easily and appropriately adjusted using the dependency evaluation index, just as in the case of using the orthogonal evaluation index.

[0239] Furthermore, if the dependency evaluation index (correlation coefficient) satisfies the termination condition, it is not necessary to adjust all SRs, which reduces the load and time required for processing.

[0240] Furthermore, the orthogonality evaluation index is calculated using the distribution of light intensity of the two-dimensional plot of the Nega-Nega group and the Nega-Posi group, but the dependence evaluation index is calculated using only the distribution of light intensity of the two-dimensional plot of the Nega-Posi group. Therefore, the amount of calculation required to calculate the evaluation index is reduced.

[0241] <<2. Modifications>> Hereinafter, modifications of the above-described embodiment of the present technology will be described.

[0242] <Modifications regarding sharing of processing> For example, part of the processing of the information processing unit 113 described above may be executed by the server 12.

[0243] For example, the analysis preprocessing unit 221 may be provided in the server 12, and the server 12 may adjust the SR of each dye.

[0244] <Application examples of this technology> This technology may also be applied to the analysis of particles other than biological particles labeled with multiple dyes. For example, beads may be analyzed for calibration purposes. For example, the particles to be analyzed may be industrially synthesized particles such as latex particles, gel particles, or industrial particles. For example, the industrially synthesized particles may be particles synthesized from organic resin materials such as polystyrene and polymethyl methacrylate, inorganic materials such as glass, silica, and magnetic materials, or metals such as gold colloid and aluminum. Each particle may be spherical or non-spherical, and there are no particular limitations on its size or mass.

[0245] <<3.Others>> <Example of computer configuration> The above-described series of processes can be executed by hardware or software. When the series of processes is executed by software, the programs that make up the software are installed on a computer. Here, the term "computer" includes computers built into dedicated hardware, and general-purpose personal computers, for example, that can execute various functions by installing various programs.

[0246] FIG. 26 is a block diagram showing an example of the hardware configuration of a computer that executes the above-described series of processes by a program.

[0247] In the computer 1000, a CPU (Central Processing Unit) 1001, a ROM (Read Only Memory) 1002, and a RAM (Random Access Memory) 1003 are interconnected by a bus 1004.

[0248] An input / output interface 1005 is further connected to the bus 1004. An input unit 1006, an output unit 1007, a storage unit 1008, a communication unit 1009, and a drive 1010 are connected to the input / output interface 1005.

[0249] The input unit 1006 includes input switches, buttons, a microphone, an image sensor, etc. The output unit 1007 includes a display, a speaker, etc. The storage unit 1008 includes a hard disk, a non-volatile memory, etc. The communication unit 1009 includes a network interface, etc. The drive 1010 drives removable media 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory.

[0250] In the computer 1000 configured as described above, the CPU 1001 performs the above-described series of processes by, for example, loading a program recorded in the memory unit 1008 into the RAM 1003 via the input / output interface 1005 and the bus 1004 and executing it.

[0251] The program executed by the computer 1000 (CPU 1001) can be provided by being recorded on a removable medium 1011 such as a package medium, for example. The program can also be provided via a wired or wireless transmission medium such as a local area network, the Internet, or digital satellite broadcasting.

[0252] In the computer 1000, the program can be installed in the storage unit 1008 via the input / output interface 1005 by inserting the removable medium 1011 into the drive 1010. The program can also be received by the communication unit 1009 via a wired or wireless transmission medium and installed in the storage unit 1008. Alternatively, the program can be installed in the ROM 1002 or the storage unit 1008 in advance.

[0253] The program executed by the computer may be a program that processes in chronological order according to the order described in this specification, or may be a program that processes in parallel or at the required timing, such as when called.

[0254] In this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all the components are contained in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device housed in a single housing with multiple modules, are both systems.

[0255] Furthermore, the embodiments of the present technology are not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present technology.

[0256] For example, this technology can be configured as cloud computing, in which a single function is shared and processed collaboratively by multiple devices via a network.

[0257] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by multiple devices.

[0258] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0259] <Configuration combination example> The present technology can also be configured as follows.

[0260] (1) The information processing device calculating light intensities corresponding to each dye from light detected from each multi-dyed particle in the sample using spectral references for each dye acquired by a single-dyed particle; calculating a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes based on the distribution of light intensity corresponding to each dye; adjusting the spectral reference for each dye based on the spillover evaluation index; An information processing method including: (2) The information processing device includes: and adjusting a first spectral reference, which is the spectral reference of the first dye, based on the spillover evaluation index of a first light corresponding to the first dye into a second light corresponding to the second dye. The information processing method according to (1) above. (3) The information processing device includes: adjusting the first spectral reference by weighting and adding or subtracting a second spectral reference, which is the spectral reference of the second dye, to the first spectral reference based on the spillover evaluation index; The information processing method according to (2) above. (4) The information processing device includes: When the second dye is in an under-unmixed state, the second spectral reference is weighted and added to the first spectral reference, and when the second dye is in an over-unmixed state, the second spectral reference is weighted and subtracted from the first spectral reference. The information processing method according to (3) above. (5) The information processing device includes: until the leakage evaluation index satisfies a predetermined condition. calculating light intensities corresponding to each dye from light detected from the multi-dyed particle using the spectral references for each dye, including the adjusted first spectral reference; Calculating the leakage evaluation index of the first light into the second light; adjusting the first spectral reference based on the leakage evaluation index; Repeat The information processing method according to any one of (2) to (4) above. (6) The information processing device includes: Calculating the leakage evaluation index based on the distribution of the intensity of the first light and the intensity of the second light in the sample. The information processing method according to any one of (2) to (5) above. (7) The leakage evaluation index is an orthogonality evaluation index that indicates the orthogonality of the distribution of the intensity of the second light in a two-dimensional plot that shows the distribution of the intensity of the first light and the intensity of the second light. The information processing method according to (6) above. (8) The orthogonality evaluation index is a Stain Index, a Signal Separation, or a Spillover Spread Matrix. The information processing method according to (7) above. (9) The orthogonal evaluation index is the slope of the distribution of light intensity in the group of multi-colored particles that showed a negative reaction to the second dye in the two-dimensional plot. The information processing method according to (7) or (8). (10) The leakage evaluation index is a dependency evaluation index that indicates the dependency between the intensity of the first light and the intensity of the second light. The information processing method according to (6) above. (11) The dependency evaluation index indicates the dependency of the intensity of the first light and the intensity of the second light in the group of multi-colored particles that showed a positive reaction to the first dye and a negative reaction to the second dye. The information processing method according to (10) above. (12) The dependency evaluation index is a correlation coefficient indicating the correlation between the intensity of the first light and the intensity of the second light in the population of the multi-colored particles. The information processing method according to (11) above. (13) The information processing device includes: performing gating of the multi-colored particles in the sample based on the first light intensity distribution and the second light intensity distribution in the sample; The spillover evaluation index is calculated based on the results of gating the multi-colored particles. The information processing method according to any one of (2) to (12) above. (14) The information processing device includes: By gating, the multi-dyed particles in the sample are separated into the multi-dyed particles that showed a positive reaction to the first dye and the multi-dyed particles that showed a negative reaction to the first dye, and are separated into the multi-dyed particles that showed a positive reaction to the second dye and the multi-dyed particles that showed a negative reaction to the second dye. The information processing method according to (13) above. (15) The information processing device includes: The spillover evaluation index is calculated for the group of multi-dyed particles that showed a positive reaction to the first dye and a negative reaction to the second dye. The information processing method according to (14) above. (16) The information processing device includes: The spillover evaluation index is calculated for a group of the multi-dyed particles that showed a positive reaction to the first dye and a negative reaction to the second dye, and for a group of the multi-dyed particles that showed a negative reaction to the first dye and a negative reaction to the second dye. The information processing method according to (14) above. (17) The information processing device includes: The spillover evaluation index is calculated for the group of multi-dyed particles that showed a positive reaction to the second dye and for the group of multi-dyed particles that showed a negative reaction to the second dye. The information processing method according to (14) above. (18) The information processing device includes: Using the adjusted spectral reference for each dye, perform an analysis of data regarding the light detected from each of the multi-dyed particles in the sample. The information processing method according to any one of (1) to (17) above. (19) an unmixing unit that calculates the intensity of light corresponding to each dye from the light detected from each multi-dyed particle in the sample using a spectral reference for each dye acquired by a single-dyed particle; an evaluation calculation unit that calculates a leakage evaluation index that indicates the degree of leakage of light corresponding to each pigment into light corresponding to other pigments based on the distribution of the intensity of light corresponding to each pigment; a spectral reference adjustment unit that adjusts the spectral reference of each dye based on the leakage evaluation index; An information processing device comprising: (20) a detection unit that detects light from each of a plurality of multi-colored particles in the sample; Information Processing Department Equipped with The information processing unit an unmixing unit that calculates the intensity of light corresponding to each dye from the light detected from each of the multi-dyed particles in the sample using a spectral reference for each dye acquired by a single-dyed particle; an evaluation calculation unit that calculates a leakage evaluation index that indicates the degree of leakage of light corresponding to each pigment into light corresponding to other pigments based on the distribution of the intensity of light corresponding to each pigment; a spectral reference adjustment unit that adjusts the spectral reference of each dye based on the leakage evaluation index; An information processing system comprising:

[0261] The effects described in this specification are merely examples and are not limiting, and other effects may also be present. [Explanation of symbols]

[0262] 1 Information processing system, 11-1 to 11-n Biological sample analyzer, 12-1, 12-2 Server, 111 Light irradiation unit, 112 Detection unit, 113 Information processing unit, 114 Fractionation unit, 202 Control unit, 203 Output unit, 205 Reference DB, 221 Analysis pre-processing unit, 222 Analysis unit, 251 Unmixing unit, 252 Axis conversion unit, 253 Gating unit, 254 Evaluation index calculation unit, 255 SR adjustment unit

Claims

1. The information processing device calculating light intensities corresponding to each dye from light detected from each multi-dyed particle in the sample using spectral references for each dye acquired by a single-dyed particle; calculating a leakage evaluation index indicating the degree of leakage of light corresponding to each dye into light corresponding to other dyes based on the distribution of light intensity corresponding to each dye; adjusting the spectral reference for each dye based on the spillover evaluation index; An information processing method including:

2. The information processing device includes: and adjusting a first spectral reference, which is the spectral reference for the first dye, based on the leakage evaluation index of a first light corresponding to the first dye into a second light corresponding to the second dye. The information processing method according to claim 1 .

3. The information processing device includes: adjusting the first spectral reference by weighting and adding or subtracting a second spectral reference, which is the spectral reference of the second dye, to the first spectral reference based on the spillover evaluation index; The information processing method according to claim 2 .

4. The information processing device includes: When the second dye is in an under-unmixed state, the second spectral reference is weighted and added to the first spectral reference, and when the second dye is in an over-unmixed state, the second spectral reference is weighted and subtracted from the first spectral reference. The information processing method according to claim 3 .

5. The information processing device includes: until the leakage evaluation index satisfies a predetermined condition. calculating light intensities corresponding to each dye from light detected from the multi-dyed particle using the spectral references for each dye, including the adjusted first spectral reference; Calculating the leakage evaluation index of the first light into the second light; adjusting the first spectral reference based on the leakage evaluation index; Repeat The information processing method according to claim 2 .

6. The information processing device includes: Calculating the leakage evaluation index based on the distribution of the intensity of the first light and the intensity of the second light in the sample. The information processing method according to claim 2 .

7. The leakage evaluation index is an orthogonality evaluation index that indicates the orthogonality of the distribution of the intensity of the second light in a two-dimensional plot that shows the distribution of the intensity of the first light and the intensity of the second light. The information processing method according to claim 6.

8. The orthogonality evaluation index is a Stain Index, a Signal Separation, or a Spillover Spread Matrix. The information processing method according to claim 7.

9. The orthogonal evaluation index is the slope of the distribution of light intensity in the group of multi-colored particles that showed a negative reaction to the second dye in the two-dimensional plot. The information processing method according to claim 7.

10. The leakage evaluation index is a dependency evaluation index that indicates the dependency between the intensity of the first light and the intensity of the second light. The information processing method according to claim 6.

11. The dependency evaluation index indicates the dependency of the intensity of the first light and the intensity of the second light in the group of multi-colored particles that showed a positive reaction to the first dye and a negative reaction to the second dye. The information processing method according to claim 10.

12. The dependency evaluation index is a correlation coefficient indicating the correlation between the intensity of the first light and the intensity of the second light in the population of the multi-colored particles. The information processing method according to claim 11.

13. The information processing device includes: performing gating of the multi-colored particles in the sample based on the first light intensity distribution and the second light intensity distribution in the sample; The spillover evaluation index is calculated based on the results of gating the multi-colored particles. The information processing method according to claim 2 .

14. The information processing device includes: By gating, the multi-dyed particles in the sample are separated into the multi-dyed particles that showed a positive reaction to the first dye and the multi-dyed particles that showed a negative reaction to the first dye, and are separated into the multi-dyed particles that showed a positive reaction to the second dye and the multi-dyed particles that showed a negative reaction to the second dye. The information processing method according to claim 13.

15. The information processing device includes: The spillover evaluation index is calculated for the group of multi-dyed particles that showed a positive reaction to the first dye and a negative reaction to the second dye. The information processing method according to claim 14.

16. The information processing device includes: The spillover evaluation index is calculated for a group of the multi-dyed particles that showed a positive reaction to the first dye and a negative reaction to the second dye, and for a group of the multi-dyed particles that showed a negative reaction to the first dye and a negative reaction to the second dye. The information processing method according to claim 14.

17. The information processing device includes: The spillover evaluation index is calculated for the group of multi-dyed particles that showed a positive reaction to the second dye and for the group of multi-dyed particles that showed a negative reaction to the second dye. The information processing method according to claim 14.

18. The information processing device includes: Using the adjusted spectral reference for each dye, perform an analysis of data regarding the light detected from each of the multi-dyed particles in the sample. The information processing method according to claim 1 .

19. an unmixing unit that calculates the intensity of light corresponding to each dye from the light detected from each multi-dyed particle in the sample using a spectral reference for each dye acquired by a single-dyed particle; an evaluation calculation unit that calculates a leakage evaluation index that indicates the degree of leakage of light corresponding to each pigment into light corresponding to other pigments based on the distribution of the intensity of light corresponding to each pigment; a spectral reference adjustment unit that adjusts the spectral reference of each dye based on the leakage evaluation index; An information processing device comprising:

20. a detection unit that detects light from each of a plurality of multi-colored particles in the sample; Information Processing Department Equipped with The information processing unit an unmixing unit that calculates the intensity of light corresponding to each dye from the light detected from each of the multi-dyed particles in the sample using a spectral reference for each dye acquired by a single-dyed particle; an evaluation calculation unit that calculates a leakage evaluation index that indicates the degree of leakage of light corresponding to each pigment into light corresponding to other pigments based on the distribution of the intensity of light corresponding to each pigment; a spectral reference adjustment unit that adjusts the spectral reference of each dye based on the leakage evaluation index; An information processing system comprising:

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