Information processing method and system for flow cytometer and flow cytometer

Abstract

The application discloses an information processing method and system for a flow cytometer and the flow cytometer. The information processing method comprises: adjusting a compensation matrix calculated based on first gain sets and second gain sets to obtain an adjusted compensation matrix; and compensating a target detection signal obtained by detecting a multi-stained sample by the flow cytometer using the adjusted compensation matrix to obtain a compensated detection signal. The first detection result is a detection result obtained by detecting a plurality of single-stained samples by the flow cytometer. The first gain sets are obtained based on respective gains of a plurality of detectors included in the flow cytometer when the first detection result is obtained, and the second gain sets are obtained based on respective gains of the plurality of detectors when the target detection signal is obtained.

Description

Information processing methods and systems for flow cytometers and flow cytometers Technical Field

[0001] This disclosure relates to the field of flow cytometry, and more specifically to information processing methods and systems for flow cytometry and flow cytometry instruments. Background Technology

[0002] Flow cytometry, such as spectroscopic flow cytometry, is becoming a popular method in multicolor group clinical research. Due to signal interference between different detection channels, a demixing process (also known as a "compensation process") is required to determine the label abundance of each unit (e.g., cells, particles, etc.) in the sample. Summary of the Invention

[0003] A brief overview of this disclosure is given below to provide a basic understanding of certain aspects of it. However, it should be understood that this overview is not an exhaustive summary of this disclosure. It is not intended to identify key or essential parts of this disclosure, nor is it intended to limit the scope of this disclosure. Its purpose is merely to present certain concepts of this disclosure in a simplified form as a prelude to the more detailed description that follows.

[0004] The purpose of this disclosure is to provide an improved information processing system and method for a flow cytometer, and a flow cytometer, for performing a compensation process on a target detection signal.

[0005] According to one aspect of this disclosure, an information processing method for a flow cytometer is provided, comprising: adjusting a compensation matrix calculated from a first detection result based on a first gain set and a second gain set to obtain an adjusted compensation matrix, wherein the first detection result is a detection result obtained by detecting multiple monostained samples using the flow cytometer; and compensating a target detection signal obtained by detecting multiple stained samples using the adjusted compensation matrix to obtain a compensated detection signal, wherein the first gain set is obtained based on the gains of each of a plurality of detectors included in the flow cytometer when the first detection result is acquired, and the second gain set is obtained based on the gains of each of the plurality of detectors when the target detection signal is acquired.

[0006] According to another aspect of this disclosure, an information processing system for a flow cytometer is provided, comprising: a compensation matrix adjustment unit configured to adjust a compensation matrix calculated from a first detection result based on a first gain set and a second gain set to obtain an adjusted compensation matrix, wherein the first detection result is a detection result obtained by detecting multiple monostained samples by the flow cytometer; and a signal compensation unit configured to compensate a target detection signal obtained by detecting multiple stained samples by the flow cytometer using the adjusted compensation matrix to obtain a compensated detection signal, wherein the first gain set is obtained based on the gains of each of a plurality of detectors included in the flow cytometer when the first detection result is acquired, and the second gain set is obtained based on the gains of each of the plurality of detectors when the target detection signal is acquired.

[0007] According to another aspect of this disclosure, a flow cytometer including the above-described information processing system is provided.

[0008] In accordance with other aspects of this disclosure, computer program code and computer program products for implementing the methods according to this disclosure are also provided, as well as a computer-readable storage medium having the computer program code for implementing the methods according to this disclosure recorded thereon.

[0009] Other aspects of embodiments of this disclosure are set forth in the following description section, wherein preferred embodiments of the present disclosure are described in detail without limiting them. Attached Figure Description

[0010] This disclosure can be better understood by referring to the detailed description given below in conjunction with the accompanying drawings, in which the same or similar reference numerals are used throughout the drawings to denote the same or similar parts. These drawings, together with the following detailed description, are incorporated in and form part of this specification, and are used to further illustrate preferred embodiments of the disclosure and explain the principles and advantages of the disclosure. Wherein:

[0011] Figure 1 is a flowchart illustrating an example of an information processing method for a flow cytometer according to an embodiment of the present disclosure;

[0012] Figure 2 is a block diagram illustrating a configuration example of an information processing system for a flow cytometer according to an embodiment of the present disclosure; and

[0013] Figure 3 is a block diagram illustrating an example structure of a personal computer that may be employed as an embodiment of this disclosure. Detailed Implementation

[0014] Exemplary embodiments of the present disclosure will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of actual implementations are described in the specification. However, it should be understood that many implementation-specific decisions must be made in the development of any such actual embodiment to achieve the developer’s specific goals, such as complying with constraints related to the system and business, and these constraints may vary from implementation to implementation. Furthermore, it should be understood that while development work can be very complex and time-consuming, such development work is merely a routine task for those skilled in the art who benefit from the present disclosure.

[0015] It should be understood that while the terms "first," "second," etc., may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, without departing from the scope of this disclosure, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

[0016] It should also be noted that, in order to avoid obscuring this disclosure with unnecessary details, only the equipment structure and / or processing steps closely related to the solution according to this disclosure are shown in the accompanying drawings, while other details that are not closely related to this disclosure are omitted.

[0017] The embodiments according to this disclosure are described in detail below with reference to the accompanying drawings.

[0018] First, an implementation example of the information processing method for a flow cytometer according to an embodiment of the present disclosure will be described with reference to FIG1. ​​FIG1 is a flowchart illustrating an example of the flow cytometer information processing method 100 according to an embodiment of the present disclosure.

[0019] As shown in FIG1, the information processing method 100 according to an embodiment of the present disclosure may begin at a start step S102 and end at a finish step S108. The information processing method 100 may include a compensation matrix adjustment step S104 and a signal compensation step S106.

[0020] In the compensation matrix adjustment step S104, the compensation matrix calculated based on the first detection result can be adjusted based on the first gain set and the second gain set to obtain the adjusted compensation matrix. For example, the first detection result can be the detection result obtained by detecting multiple single-stained samples using flow cytometry. For example, the compensation matrix X calculated based on the first detection result... L×P It can be expressed by the following formula (1):

[0021]

[0022] Compensation matrix X L×P Each column corresponds to a spectral feature of fluorescence or autofluorescence, and the compensation matrix X L×P Signals in the same row correspond to the same detector. Specifically, the compensation matrix X L×P The element X in the i-th row and j-th column ij This can correspond to the signal detected by the i-th detector when the control samples are stained with the dye corresponding to the j-th label.

[0023] In signal compensation step S106, the target detection signal can be compensated using the adjusted compensation matrix obtained in step S104, to obtain a compensated detection signal. For example, the target detection signal can be a detection signal obtained by detecting a target sample, such as a multi-stained sample, using flow cytometry. For example, the target sample may include one or more units (e.g., cells, particles, etc.). The compensated detection signal can be used to determine the label abundance of each unit in the target sample.

[0024] For example, the first gain set could be obtained based on the individual gains of the multiple detectors included in the flow cytometer when acquiring the first detection result. For example, the first gain set... It can be expressed by the following formula (2):

[0025]

[0026] In equation (2), the first gain set The element in the i-th row and j-th column This can represent the gain of the i-th detector when the control sample is stained with the dye corresponding to the j-th label to obtain the corresponding component of the first detection result.

[0027] For example, the second gain set could be obtained based on the individual gains of multiple detectors when acquiring the target detection signal. For example, the second gain set. It can be expressed by the following formula (3):

[0028]

[0029] In equation (3), the second gain set The i-th row element It can represent the gain of the i-th detector when acquiring the target detection signal.

[0030] For example, the adjusted compensation matrix X obtained through the compensation matrix adjustment step S104. L ′ ×pIt can be expressed by the following formula (4):

[0031]

[0032] For example, in the signal compensation step S106, the compensated detection signal can be obtained by the following formula (5). Where the i-th row component β i This represents the signal component corresponding to the i-th label. For example, based on βi, the label abundance associated with the i-th label of the corresponding unit (e.g., cell, particle, etc.) in the target sample can be determined.

[0033]

[0034] In equation (5), This represents the component of the target detection signal with respect to a unit in the target sample. Specifically, the i-th row component yi represents the component obtained by the i-th detector with respect to the aforementioned unit. Furthermore, in equation (5), This indicates the error term (see, for example, Novo D, Grégori G, Rajwa B. Generalized unmixing model for multispectral flow cytometry utilizing nonsquare compensation matrices[J]. Cytometry Part A, 2013, 83(5): 508-520).

[0035] In flow cytometry, such as spectroscopic flow cytometry, a compensation process is required to compensate for the target detection signal to determine the label abundance of each cell in the target sample. In some techniques, the target detection signal is compensated using a compensation matrix (hereinafter also referred to as the "original compensation matrix") calculated based on a first detection result obtained by detecting multiple monostained samples. Therefore, it is necessary to maintain consistency between the gain of each detector when obtaining the first detection result and the gain of each detector when obtaining the target detection signal. That is, for each detector, the gain of that detector when obtaining the first detection result needs to be the same as the gain of that detector when obtaining the target detection signal. If the gain of a corresponding detector needs to be adjusted because the target detection signal is too strong or too weak, the first detection result needs to be reacquired with the adjusted gain and the compensation matrix recalculated, increasing time and labor costs.

[0036] On the other hand, as described above, in the information processing method 100 according to an embodiment of the present disclosure, the original compensation matrix is ​​adjusted based on a first gain set and a second gain set to obtain an adjusted compensation matrix, and the adjusted compensation matrix is ​​used to compensate the target detection signal. Therefore, it is not necessary to maintain consistency between the gain of each detector when obtaining the first detection result and the gain of each detector when obtaining the target detection signal, which can reduce time and labor costs. Furthermore, in the information processing method 100 according to an embodiment of the present disclosure, different gain representation methods can be used for different detectors. For example, amplitude can be used to represent gain for some detectors, while area can be used to represent gain for others, thus improving convenience.

[0037] As an example, the first gain set can be obtained based on the individual gains of multiple detectors and their corresponding first benchmark gains when acquiring the first detection result. For each detector, the corresponding first benchmark gain can be the gain of that detector during quality control before detecting multiple monostained samples to obtain the first detection result. In this case, the first gain set in equation (2) The element in the i-th row and j-th column It can represent the relative gain of the i-th detector when the sample is stained with the dye corresponding to the j-th label to obtain the corresponding component of the first detection result. For example, it can be the ratio of the gain of the i-th detector when the sample is stained with the dye corresponding to the j-th label to the first reference gain of the i-th detector during the quality control process before obtaining the first detection result.

[0038] For example, the second gain set can be obtained based on the individual gains of multiple detectors and their corresponding second reference gains when acquiring the target detection signal. For each detector, the corresponding second reference gain can be the gain of that detector during the quality control process before acquiring the target detection signal. In this case, the second gain set in equation (3) element in row i It can represent the relative gain of the i-th detector when acquiring the target detection signal, for example, the ratio of the gain of the i-th detector when acquiring the target detection signal to the gain of the i-th detector during the quality control process before acquiring the target detection signal.

[0039] By using the relative gains of each detector to obtain an adjusted compensation matrix, the influence of flow cytometry deviations occurring during the time interval from acquiring the first detection result to acquiring the target detection signal on the adjusted compensation matrix can be prevented or reduced, thereby further improving the tag abundance determined based on the compensated detection signal.

[0040] The above description has outlined an information processing method 100 for a flow cytometer according to embodiments of the present disclosure. Corresponding to the above-described embodiments of the information processing method 100 for a flow cytometer, the present disclosure also provides the following embodiments of an information processing system for a flow cytometer. FIG2 is a block diagram illustrating a configuration example of an information processing system 200 for a flow cytometer according to embodiments of the present disclosure.

[0041] For example, as shown in FIG2, an information processing system 200 according to an embodiment of the present disclosure may include a compensation matrix adjustment unit 204 and a signal compensation unit 206.

[0042] The compensation matrix adjustment unit 204 can be configured to adjust the compensation matrix calculated from the first detection result based on a first gain set and a second gain set to obtain an adjusted compensation matrix. For example, the first detection result can be the detection result obtained by detecting multiple single-stained samples using flow cytometry. For example, the compensation matrix adjustment unit 204 can execute the compensation matrix adjustment step S104 described above with reference to FIG1. ​​Therefore, for details, please refer to the description of the compensation matrix adjustment step S104 above. It will only be briefly described below.

[0043] The signal compensation unit 206 can be configured to compensate the target detection signal using the adjusted compensation matrix obtained by the compensation matrix adjustment unit 204, so as to obtain a compensated detection signal. For example, the target detection signal may be a detection signal obtained by detecting a target sample such as a multi-stained sample using flow cytometry.

[0044] For example, the first gain set may be obtained based on the individual gains of the multiple detectors included in the flow cytometer when acquiring the first detection result. The second gain set may be obtained based on the individual gains of the multiple detectors when acquiring the target detection signal.

[0045] Similar to the information processing method 100 described above, the information processing system 200 according to embodiments of this disclosure can adjust the original compensation matrix based on a first gain set and a second gain set to obtain an adjusted compensation matrix, and use the adjusted compensation matrix to compensate the target detection signal. Therefore, it is not necessary to maintain consistency between the gain of each detector when obtaining the first detection result and the gain of each detector when obtaining the target detection signal, which can reduce time and labor costs. Furthermore, in the information processing system 200 according to embodiments of this disclosure, different gain representation methods can be used for different detectors; for example, amplitude can be used to represent gain for some detectors, while area can be used to represent gain for others, thus improving convenience.

[0046] As an example, the first set of gains can be obtained based on the individual gains of multiple detectors and their corresponding first reference gains when acquiring the first detection result. For each detector, the corresponding first reference gain can be the gain of that detector during quality control before detecting multiple monostained samples to obtain the first detection result. Similarly, the second set of gains can be obtained based on the individual gains of multiple detectors and their corresponding second reference gains when acquiring the target detection signal. For each detector, the corresponding second reference gain can be the gain of that detector during quality control before acquiring the target detection signal.

[0047] By using the relative gains of each detector to obtain an adjusted compensation matrix, the influence of flow cytometry deviations occurring during the time interval from acquiring the first detection result to acquiring the target detection signal on the adjusted compensation matrix can be prevented or reduced, thereby further improving the accuracy of the tag abundance determined based on the compensated detection signal.

[0048] Note that although examples of representations of the first and second gain sets are given in this paper, in practical applications, appropriate representations of the first and second gain sets can be used as needed, and correspondingly, the formula for calculating the adjusted compensation matrix may differ from the described examples.

[0049] Furthermore, according to embodiments of this disclosure, a flow cytometer including the aforementioned information processing system 200 may also be provided. For example, the flow cytometer may include a spectral flow cytometer, but is not limited thereto.

[0050] It should be noted that although the above description of the information processing system and method for flow cytometer according to embodiments of the present disclosure, as well as the functional configuration and operation of the flow cytometer, is merely an example and not a limitation. Those skilled in the art can modify the above embodiments based on the principles of the present disclosure, such as adding, deleting, or combining functional modules and operations in various embodiments, and all such modifications fall within the scope of the present disclosure.

[0051] Furthermore, it should be noted that the system embodiments described here correspond to the method embodiments described above. Therefore, any content not described in detail in the system embodiments can be found in the description of the corresponding parts in the method embodiments, and will not be repeated here.

[0052] Furthermore, this disclosure also provides a storage medium and a program product. It should be understood that the machine-executable instructions in the storage medium and program product according to embodiments of this disclosure can also be configured to perform the aforementioned information processing methods; therefore, details not described in detail here can be referred to the descriptions in the preceding corresponding sections and will not be repeated here.

[0053] Accordingly, the storage medium used to carry the aforementioned program product including machine-executable instructions is also included in the disclosure of this invention. This storage medium includes, but is not limited to, floppy disks, optical disks, magneto-optical disks, memory cards, memory sticks, etc.

[0054] Furthermore, it should be noted that the aforementioned series of processes and systems can also be implemented via software and / or firmware. In the case of software and / or firmware implementation, the programs constituting the software are installed from a storage medium or network onto a computer with a dedicated hardware architecture, such as the general-purpose personal computer 500 shown in Figure 3. This computer, when equipped with various programs, is capable of performing various functions, etc.

[0055] In Figure 3, the Central Processing Unit (CPU) 501 performs various processes according to the program stored in the Read-Only Memory (ROM) 502 or the program loaded into the Random Access Memory (RAM) 503 from the storage section 508. The RAM 503 also stores data as needed when the CPU 501 performs various processes.

[0056] CPU 501, ROM 502 and RAM 503 are interconnected via bus 504. Input / output interface 505 is also connected to bus 504.

[0057] The following components are connected to the input / output interface 505: input section 506, including a keyboard, mouse, etc.; output section 507, including a display, such as a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; storage section 508, including a hard disk, etc.; and communication section 509, including a network interface card, such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network, such as the Internet.

[0058] As needed, drive 510 is also connected to input / output interface 505. Removable media 511, such as disks, optical disks, magneto-optical disks, semiconductor memories, etc., are installed on drive 510 as needed, so that computer programs read from them can be installed into storage section 508 as needed.

[0059] When the above series of processes are implemented through software, the program constituting the software is installed from a network such as the Internet or a storage medium such as removable media 511.

[0060] Those skilled in the art will understand that such storage media are not limited to the removable medium 511 shown in FIG. 3, which stores programs and is distributed separately from the device to provide programs to users. Examples of removable media 511 include magnetic disks (including floppy disks (registered trademark)), optical disks (including optical disc read-only memory (CD-ROM) and digital versatile disks (DVD)), magneto-optical disks (including mini-disk (MD) (registered trademark)), and semiconductor memories. Alternatively, the storage medium may be ROM 502, a hard disk included in storage section 508, etc., which stores programs and is distributed to users along with the device containing them.

[0061] Preferred embodiments of the present disclosure have been described above with reference to the accompanying drawings, but the present disclosure is by no means limited to the examples described above. Various changes and modifications can be made by those skilled in the art within the scope of the appended claims, and it should be understood that such changes and modifications naturally fall within the technical scope of the present disclosure.

[0062] For example, the multiple functions included in one unit in the above embodiments can be implemented by separate devices. Alternatively, the multiple functions implemented by multiple units in the above embodiments can be implemented by separate devices respectively. In addition, one of the above functions can be implemented by multiple units. Needless to say, such a configuration is included within the scope of the present disclosure.

[0063] In this specification, the steps described in the flowchart include not only processes executed sequentially in the stated order, but also processes executed in parallel or individually, rather than necessarily sequentially. Furthermore, even within the steps of sequential processing, needless to say, the order can be appropriately altered.

Claims

1. An information processing method for flow cytometers, comprising: Based on a first gain set and a second gain set, the compensation matrix calculated from the first detection result is adjusted to obtain an adjusted compensation matrix, wherein the first detection result is obtained by detecting multiple single-stained samples using the flow cytometer; and the adjusted compensation matrix is ​​used to compensate the target detection signal obtained by detecting multiple stained samples using the flow cytometer to obtain a compensated detection signal, wherein the first gain set is obtained based on the gains of each of the multiple detectors included in the flow cytometer and the corresponding first reference gain when the first detection result is obtained, wherein the second gain set is obtained based on the gains of each of the multiple detectors and the corresponding second reference gain when the target detection signal is obtained, and wherein, for each of the multiple detectors, the corresponding first reference gain is the gain of that detector during the quality control process before detecting the multiple single-stained samples, and the corresponding second reference gain is the gain of that detector during the quality control process before obtaining the target detection signal.

2. An information processing system for flow cytometers, comprising: A compensation matrix adjustment unit is configured to adjust a compensation matrix calculated from a first detection result based on a first gain set and a second gain set to obtain an adjusted compensation matrix, wherein the first detection result is obtained by detecting multiple single-stained samples using the flow cytometer; and a signal compensation unit is configured to compensate a target detection signal obtained by detecting multiple stained samples using the adjusted compensation matrix to obtain a compensated detection signal, wherein the first gain set is obtained based on the gains of each of the multiple detectors included in the flow cytometer and a corresponding first reference gain when the first detection result is obtained, wherein the second gain set is obtained based on the gains of each of the multiple detectors and a corresponding second reference gain when the target detection signal is obtained, and wherein, for each of the multiple detectors, the corresponding first reference gain is the gain of that detector during quality control before detecting the multiple single-stained samples, and the corresponding second reference gain is the gain of that detector during quality control before obtaining the target detection signal.

3. A flow cytometer, comprising the information processing system according to claim 2.

4. A computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform the information processing method according to claim 1.

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