Mass spectrometry data processing system and method

Abstract

The present invention discloses a mass spectrometry data processing system and method. The system includes a client and an edge computing device. The client is installed on the data side and is used to send a peak extraction request to the edge computing device and obtain a peak extraction result from the edge computing device. The peak extraction request includes peak extraction calculation parameters and mass spectrometry data extracted from the data side. The edge computing device is used to extract mass spectrometry peaks from the mass spectrometry data by using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result. The present invention introduces an edge computing device, which greatly reduces the size of the uploaded data and reduces the noise information in the data. There is no need for the user to switch to different sides (data side, local server, cloud server) for operations, and it is convenient and flexible to use. It is suitable for rapid data transmission from the data side to the cloud or the local server side, thereby reducing the processing pressure of subsequent calculations on the cloud or the local server.

Description

Technical Field

[0001] The present application relates to a mass spectrometry data processing system and method, specifically a processing system and method supporting edge computing of mass spectrometry data, belonging to the technical field of edge computing. Background Art

[0002] A mass spectrometer is an instrument used for separating and detecting different isotopes. That is, based on the principle that charged particles can be deflected in an electromagnetic field, it is a type of instrument that separates and detects the composition of substances according to the mass differences of atomic, molecular, or molecular fragment masses of substances. The mass spectrometer can be used alone or in combination with separation tools such as chromatographs, electrophoresis apparatuses, and ion mobility spectrometers to obtain more powerful separation and detection capabilities.

[0003] After the mass spectrometer analyzes the sample, it can obtain the mass-to-charge ratio information (m / z information) of ions and other auxiliary information such as retention time information, etc. Because the sample is complex, a large amount of noise signals will be generated during the data acquisition process, resulting in large mass spectrometry data even for a single data. The size of each data obtained by a conventional mass spectrometer ranges from several megabytes to hundreds of gigabytes. When the sample size is large, even for local calculation, the transmission and processing of the original data will pose challenges to the data processing system.

[0004] Compared with the single-machine local calculation mode, remote cloud computing of mass spectrometry data has many advantages such as collaboration and sharing. However, uploading the complete mass spectrometry data to the cloud server will generate a huge transmission pressure, resulting in too long transmission time. At the same time, it will generate a large storage and calculation pressure in the cloud, resulting in users increasing the calculation and time costs. Because the performance of the mass spectrometry data processing servers matched by different laboratories varies, directly using software to preprocess the data and upload it may have problems that some servers are difficult to meet the hardware configuration requirements, or there are problems that the software and hardware need to be optimized to play their performance, resulting in the fact that simply using software cannot meet the needs of a large number of mass spectrometry users. Compressing the data is also a solution to the above problems, but general lossless compression technologies cannot effectively reduce the volume of mass spectrometry data, nor can they reduce the data processing pressure on the server side, but instead increase the local execution compression time and the decompression time on the server side.

[0005] To overcome the above challenges, it is necessary to develop innovative data preprocessing devices and methods, especially data preprocessing devices and methods that meet the requirements of rapid and accurate processing of large-scale data in the cloud. Summary of the Invention

[0006] The purpose of the present application is to provide a mass spectrometry data processing system and method to solve the technical problems in the prior art that there is a lot of noise and a large amount of data in mass spectrometry data, increasing the data processing pressure on subsequent cloud or local servers.

[0007] The first embodiment of the present invention discloses a mass spectrometry data processing system, including a client and an edge computing device;

[0008] The client is installed on the data side, and is used to send a peak extraction request to the edge computing device and obtain a peak extraction result from the edge computing device; the peak extraction request includes peak extraction calculation parameters and mass spectrometry data extracted from the data side;

[0009] The edge computing device is used to extract mass spectrometry peaks from the mass spectrometry data by using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result.

[0010] The above data side can be a mass spectrometer for generating mass spectrometry data, or other devices storing mass spectrometry data; wherein the mass spectrometry data includes a data stream recording mass spectrometry signals, an original mass spectrometry file, and a converted standard mass spectrometry file; the original mass spectrometry file includes but is not limited to files in.d format and.raw format, and the standard mass spectrometry file includes but is not limited to files in.mzXML and.mzML formats.

[0011] The above edge computing device is set on the data side and serves as a dedicated data preprocessing server, which is composed of software and hardware with performance adaptation, and can be used in combination with computers or servers of different specifications. Since the edge computing device of the present invention is a dedicated data preprocessing server, its size can be smaller than that of a general desktop computer or server, and there is no need to match irrelevant software or hardware.

[0012] Preferably, the above edge computing device includes a management unit, a computing unit, and a storage unit;

[0013] The management unit is used to send the received peak extraction request to the computing unit and control the storage unit to store the peak extraction result output by the computing unit;

[0014] The computing unit is used to extract mass spectrometry peaks from the mass spectrometry data by using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result; the computing unit refers to a CPU, GPU, FPGA, or other artificial intelligence chips with floating-point computing capabilities; when using a GPU, a dedicated refrigeration device is allocated to ensure that the temperature is controlled within an appropriate range;

[0015] The storage unit is used to store the peak extraction result.

[0016] Preferably, the management unit includes a receiving module and a resource pool;

[0017] The receiving module is used to receive the peak extraction request;

[0018] The resource pool is used to extract the peak extraction request from the receiving module and send it to the computing unit.

[0019] Preferably, the system further includes a cloud;

[0020] The cloud is used to send a request for obtaining the peak extraction result to the client or the edge computing device and receive the peak extraction result uploaded by the client or the edge computing device;

[0021] Preferably, the system further includes a local server;

[0022] The local server is used to send a request for obtaining the peak extraction result to the client or the edge computing device and receive the peak extraction result uploaded by the client or the edge computing device.

[0023] Preferably, the management unit is further used to number the received peak extraction request and send the number to any one or more of the client, the cloud, and the local server;

[0024] Correspondingly, the client, the cloud, and the local server obtain the peak extraction result corresponding to the number from the storage unit.

[0025] Preferably, the edge computing device further includes a communication unit;

[0026] The communication unit is used to connect the edge computing device to the client, the cloud, and the local server.

[0027] The second embodiment of the present invention provides a mass spectrometry data processing method, including:

[0028] Obtain a peak extraction request sent by a client, where the peak extraction request includes mass spectrometry data and peak extraction calculation parameters; the client is installed on a data terminal containing the mass spectrometry data;

[0029] Extract mass spectrometry peaks from the mass spectrometry data by using a peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result.

[0030] Preferably, after extracting the mass spectrometry peaks from the mass spectrometry data by using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result, it further includes:

[0031] Receive a request for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, and send the corresponding peak extraction result to the entity that sent the request.

[0032] Preferably, after obtaining the peak extraction request sent by the client, the following steps are further included:

[0033] Number the peak extraction request and send the number to any one or more of the client, the cloud, and the local server;

[0034] Correspondingly, receiving a request for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the entity that sent the request, specifically:

[0035] Receiving a request for obtaining the peak extraction result containing the number sent by any one or more of the client, the cloud, and the local server;

[0036] Sending the peak extraction result corresponding to the number to the entity that sent the request.

[0037] Preferably, receiving a request for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the entity that sent the request, specifically:

[0038] Receiving a callback request for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, where the callback request includes a number, a callback address, and a callback method;

[0039] Uploading the peak extraction result corresponding to the number to the callback address according to the callback method;

[0040] Preferably, receiving a request for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the entity that sent the request, specifically:

[0041] Receiving an automatic notification request sent by any one or more of the client, the cloud, and the local server, where the automatic notification request includes a number;

[0042] When the number has a corresponding peak extraction result, sending a notification to the entity that sent the request;

[0043] Receiving a request for obtaining the peak extraction result initiated by any one or more of the client, the cloud, and the local server;

[0044] Sending the peak extraction result corresponding to the number to the entity that sent the request.

[0045] The mass spectrometry data processing system and method of the present invention have the following beneficial effects compared with the prior art:

[0046] The present invention introduces an edge computing device and a client installed at the data side. The data side uses the client application to call the edge computing device to complete the entire process of mass spectrometry peak extraction, uploading to the cloud or a local server, and initiating subsequent calculations to the cloud or a local server. This not only eliminates the need for users to switch to different terminals (data side, local server, cloud server) for operations but also enables the utilization of the computing resources of the cloud and the edge computing device. The present invention enables the mass spectrometry data at the data side to directly obtain calculation results through the edge computing device, reducing the processing pressure of subsequent calculations and the pressure of uploading to the cloud or a local server.

[0047] In addition, the present invention uses an exclusive mass spectrometry data processing device and method, which greatly reduces the size of the uploaded data, reduces the noise information in the data, is convenient and flexible to use, is suitable for rapid data transmission from the data side to the cloud or the local server side, and effectively reduces the data processing cost of the cloud or the local server. Brief Description of the Drawings

[0048] Figure 1 It is a schematic structural diagram of a mass spectrometry data processing system of the present application;

[0049] Figure 2 It is a flowchart of a mass spectrometry data processing method of the present application.

[0050] List of Components and Reference Numerals:

[0051] 1. Client; 2. Edge computing device; 21. Management unit; 22. Computing unit; 23. Storage unit; 24. Communication unit; 3. Cloud. Detailed Description of the Embodiments

[0052] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0053] The present invention will be described in detail below in conjunction with embodiments, but the present invention is not limited to these embodiments.

[0054] The structure of the mass spectrometry data processing system of the present invention is shown in Figure 1, including a client 1 and an edge computing device 2; the client 1 is installed on the data side for sending a peak extraction request to the edge computing device 2 and obtaining a peak extraction result from the edge computing device 2; the peak extraction request in this application includes peak extraction calculation parameters and mass spectrometry data extracted from the data side; the edge computing device 2 is used to determine a peak extraction algorithm according to the peak extraction calculation parameters, and then use the peak extraction algorithm to extract mass spectrometry peaks from the mass spectrometry data to obtain a peak extraction result.

[0055] The above data side can be a mass spectrometer for generating mass spectrometry data, or other devices storing mass spectrometry data; when the data side is a mass spectrometer, the client is installed on the mass spectrometer. The mass spectrometer establishes a communication channel with the communication unit of the edge computing device through the client on it, and uploads the generated mass spectrometry data and peak extraction calculation parameters to the edge computing device through the communication channel. The mass spectrometry data in the data side includes a data stream recording mass spectrometry signals, original mass spectrometry files, and converted standard mass spectrometry files; the original mass spectrometry files include, but are not limited to, files in.d format and.raw format, and the standard mass spectrometry files include, but are not limited to, files in.mzXML and.mzML formats.

[0056] The above edge computing device is set on the data side and serves as a dedicated data preprocessing server, which consists of software and hardware with performance adaptation and can be used in combination with computers or servers of different specifications. Since the edge computing device of the present invention is a dedicated data preprocessing server, its size can be smaller than that of a general desktop computer or server, and there is no need to match irrelevant software or hardware.

[0057] The peak extraction algorithm in this application is an algorithm in the prior art, such as the algorithm in the mass spectrometry automatic processing and identification system in the prior art. The peak extraction algorithm can be determined according to the peak extraction calculation parameters.

[0058] The edge computing device 2 in this application includes a management unit 21, a computing unit 22, and a storage unit 23. Among them, the management unit 21 is used to send the received peak extraction request to the computing unit 22 and control the storage unit 23 to store the peak extraction result output by the computing unit 22. The computing unit 22 is used to extract mass spectrometry peaks from the mass spectrometry data by using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain the peak extraction result. The storage unit 23 is used to store the peak extraction result. The computing unit in this application refers to a CPU, GPU, FPGA, or other artificial intelligence chips with floating-point computing capabilities. When using a GPU, a dedicated refrigeration device is allocated to ensure that the temperature is controlled within an appropriate range. The management unit 21 in this application is a management system or management software for the internal system of the edge computing device 2, mainly realizing the allocation of user requests, computing resources, and storage resources. The computing unit 22 is a processor for mass spectrometry data, extracting and processing the mass spectrometry data to obtain molecular / sample characteristic information, that is, mass spectrometry peaks. The storage unit 23 stores service applications, stores the mass spectrometry data uploaded by users, and the processed molecular / sample characteristic data.

[0059] Further, the management unit 21 of this application includes a receiving module and a resource pool. The receiving module is used to receive the peak extraction request. The resource pool is used to extract the peak extraction request from the receiving module and send it to the computing unit 22. Among them, the receiving module can be a task queue. The specific implementation process is as follows: When the task queue is not empty, check whether there are resources in the resource pool at regular intervals. If there are resources, run the earliest task in the task queue, remove it from the queue, and send it to the computing unit 22, thereby realizing resource allocation. When the computing unit 22 receives the task and starts to execute, it uses the peak extraction algorithm corresponding to the peak extraction calculation parameters of the task to convert the mass spectrometry data in the task into data or data files containing molecular / sample characteristic information. After running, it returns the resources to the resource pool of the management unit and marks the task as successfully executed. The hardware of the computing unit in this application includes but is not limited to CPU, GPU, memory, etc. The software and algorithms run by the computing unit can be any mass spectrometry peak extraction algorithm.

[0060] The mass spectrometry data processing system of this application further includes a cloud 3. The cloud server is used to send a request to obtain the peak extraction result to the client or the edge computing device and receive the peak extraction result uploaded by the client or the edge computing device. The cloud 3 can further analyze the peak extraction result preprocessed by the edge computing device to obtain a complete mass spectrometry data analysis result.

[0061] The mass spectrometry data processing system of the present application also includes a local server, which is used to send a request to obtain a peak extraction result to a client or an edge computing device and receive the peak extraction result uploaded by the client or the edge computing device. The local server can further analyze the peak extraction result preprocessed by the edge computing device to obtain a completed mass spectrometry data analysis result.

[0062] In the present application, the peak extraction results in the client 1 or the edge computing device 2 can be automatically uploaded to the cloud or local server, or the peak extraction results can be sent to the request issuing entity after the cloud or local server sends a request to obtain the peak extraction results.

[0063] The management unit of the present application is also used to number the received peak extraction request, record the mass spectrum data and peak extraction calculation parameters corresponding to the number as a group of tasks and add them to the task queue, and send the number to any one or more entities in the client, cloud and local server. Then the calculation unit 22 uses the peak extraction algorithm corresponding to the peak extraction calculation parameters in the number to extract the mass spectrum peak from the mass spectrum data in the number, obtain the peak extraction result corresponding to the number and store it in the storage unit 23. Afterwards, the client, cloud and local server obtain the peak extraction result corresponding to the number from the storage unit for subsequent display or processing.

[0064] In order to realize the communication between the edge computing device and the client 1, the cloud 3 and the local server, a communication unit 24 is also provided in the edge computing device 2 of the present application; the communication unit 24 can be a device and software using standard communication protocols such as network communication and USB, specifically, it can be optical fiber, router, WIFI wireless network, Bluetooth signal, USB, etc.

[0065] The present invention introduces an edge computing device and a client installed on the data end. The data end uses the client application to call the edge computing device to complete the complete process of mass spectrum peak extraction, uploading to the cloud or local server, and initiating subsequent calculations to the cloud or local server. There is no need for users to switch to different ends (data end, local server, cloud server) for operation, and the computing resources of the cloud and edge computing devices can be utilized. The present invention enables the mass spectrum data of the data end to automatically and directly obtain the calculation results through the edge computing device, reducing the processing pressure of subsequent calculations and the pressure of uploading to the cloud or local server.

[0066] In addition, the present invention uses a dedicated mass spectrometry data processing device and method, which greatly reduces the size of the uploaded data and reduces the noise information in the data. It is easy and flexible to use and is suitable for rapid data transmission from the data end to the cloud or local server end, effectively reducing the data processing cost of the cloud or local server.

[0067] The second embodiment of the present invention provides a method for processing mass spectrometry data, see Figure 2 , including:

[0068] Step 1: Obtain a peak extraction request sent by the client. The peak extraction request includes mass spectrometry data and peak extraction calculation parameters; the client is installed on the data side containing the mass spectrometry data;

[0069] Step 2: The edge computing device uses the peak extraction algorithm corresponding to the peak extraction calculation parameters to extract mass spectrometry peaks from the mass spectrometry data, obtaining a peak extraction result.

[0070] The edge computing device is set on the data side.

[0071] Specifically, the client installed on the data side calls the edge computing device to request peak extraction for the mass spectrometry data. The request content (i.e., the peak extraction request) includes the peak extraction calculation parameters and the mass spectrometry data obtained from the data side, and the calling method varies according to the communication protocol of the edge computing device. Before the client obtains the peak extraction request, it is necessary to ensure that there is a compatible communication channel between the data side and the edge computing device, the data side and the cloud, and the data side and the local server, or to ensure that there is a compatible communication channel between the edge computing device and the cloud, the edge computing device and the client, and the edge computing device and the local server. The communication channel can be a device and software using standard communication protocols such as network communication and USB. Specifically, it can be optical fiber, router, WIFI wireless network, Bluetooth signal, USB, etc.

[0072] Further, after using the peak extraction algorithm corresponding to the peak extraction calculation parameters to extract mass spectrometry peaks from the mass spectrometry data and obtaining a peak extraction result, it further includes:

[0073] Step 3: Receive requests for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, and send the corresponding peak extraction result to the requesting entity.

[0074] To facilitate the distinction of multiple peak extraction requests, after the present application obtains the peak extraction request sent by the client, it further includes:

[0075] Number the peak extraction request and send the number to any one or more of the client, the cloud, and the local server.

[0076] Correspondingly, receiving requests for obtaining the peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the requesting entity, specifically:

[0077] Receive requests for obtaining the peak extraction result containing the number sent by any one or more of the client, the cloud, and the local server;

[0078] Send the peak extraction results corresponding to the number to the entity that sent the request. The sending process can specifically adopt three methods, specifically:

[0079] The first method is data - end polling.

[0080] Any one or more of the client, cloud, and local server use the number to initiate a request to the edge computing device to obtain the peak extraction results at regular intervals. This request is an active download request for peak extraction results until the request is successful. Only when the task corresponding to the number is marked as successful will it respond successfully. Then, send the peak extraction results (molecular / sample feature information) corresponding to the number to the entity that sent the request.

[0081] The second method is edge device feedback.

[0082] Any one or more of the client, cloud, and local server use the number to initiate a request to the edge computing device to obtain the peak extraction results. This request is an automatic feedback request for peak extraction results. The automatic feedback request for peak extraction results includes the number, feedback method, and feedback address. The edge computing device will initiate an upload to the feedback address using the specified feedback method after the task corresponding to the number is completed, that is, upload the peak extraction results corresponding to the number to the feedback address.

[0083] The third method is edge device notification.

[0084] Any one or more of the client, cloud, and local server use the number to initiate a request to the edge computing device to obtain the peak extraction results. This request includes an automatic notification request and a download request. The edge computing device will notify the entity that sent the automatic notification request after the task corresponding to the number is completed. After receiving the notification, the entity that sent the automatic notification request will initiate an active download request to the edge computing device, and the edge computing device will send the peak extraction results corresponding to the number to this entity.

[0085] The following will detail the present application with more specific embodiments.

[0086] Embodiment 1

[0087] In this embodiment, the hardware of the edge computing device used includes a main board, an Intel CPU, a Cambrian MLU270 computing chip, 16GB of memory, a 512GB hard drive, a network card, and a custom chassis. The software is the pre-installed Ubuntu 18.04 system, a peak extraction network service based on Python Flask, uses Celery queues to manage computing tasks, and uses a Redis database to record the status of the resource pool. The edge computing device can accept HTTP requests. The interfaces include an interface for querying the status of the computing device (GET request), an interface for uploading mass spectrometry data and peak extraction calculation parameters (POST request), and an interface for requesting the download address of the result (GET request). The peak extraction algorithm is implemented using a Python script.

[0088] In this embodiment, the hardware of the cloud service used is a Huawei Cloud 4-core 16GB memory node. The software is the pre-installed Centos 7 system, a peak alignment and differential analysis WEB service based on Python Flask, uses Celery queues to manage computing tasks, uses a Redis database to record the status of the resource pool, provides HTML-based web resources, uses Postgres to manage user login information, and has a fixed Internet IP. The cloud service can accept HTTP requests. The interfaces include a login interface (POST request), an interface for uploading peak extraction result data and subsequent computing task parameters (POST request), an interface for requesting task results (GET request), and an interface for querying the task list (GET request).

[0089] In this embodiment, the hardware of the data terminal device used is a standard computer with a network card. The software is the pre-installed Windows 7 system, a client application developed based on C#, and the Chrome browser. The client application can send HTTP requests and incorporates all interface call methods for the edge computing device and the cloud service.

[0090] In this embodiment, the client used involves the following hardware and devices: a TP-Link router, a Unicom fiber optic for network access, an edge computing device, a data terminal device, a client application, and a cloud server. Prerequisite operations: Connect the network access fiber optic to the WAN port of the router, and connect the edge computing device and the data terminal device to the LAN ports of the router. Ensure that the data terminal can connect to the Internet and the edge computing device 1 through the router.

[0091] The operation process of this embodiment is as follows:

[0092] First step, open the client application on the data terminal, fill in the cloud service username and password on the login interface, and click OK. If the prerequisite operations are correct and the cloud service user information is correct, the login is successful and the main interface is entered.

[0093] Step 2: If the first step is successful, switch to the Edge Computing Device page, enter the IP address and service port number of the edge computing device in the router LAN, enter the peak extraction calculation parameters, and click "Try to Connect". If the settings in the first step and this step are correct, a tick will be displayed in the connection status box; otherwise, a warning dialog box will pop up.

[0094] Step 3: After the second step is successful, switch to the task initiation interface and click "Initiate Task". In the task settings window, click "Add File", select the mass spectrometry data files (.mzxml, raw,.d, etc.) that need to be batch processed in subsequent tasks, and click "OK"; in the task settings window, select "Peak Alignment + Differential Analysis" from the task type drop-down box and click "Submit Task".

[0095] Step 4: You can view the status of each data file in the task list: after each data file is published to the edge computing device, "Peak Extraction in Progress" will be displayed; after the extraction is successful, it will be displayed as "Extraction Successful" and the result file will be downloaded to the local (csv, txt, etc.); each result file downloaded to the local will be added to the task list and "Uploading (to the cloud)" will be displayed; after the upload is completed, "Upload Successful" will be displayed. After the same batch of data files complete the submission to the edge computing, download of the calculation results, and upload to the cloud, the client will automatically send a request to the cloud for "Peak Alignment + Differential Analysis" of them. As shown in Table 1, it shows the effects in terms of the reduction of the data file size and the time cost of cloud processing for 10 mass spectrometry data files (.d) after being processed by the edge computing device.

[0096] Table 1

[0097]

[0098] It can be seen that the system of the present invention greatly reduces the size of the uploaded data, reduces the noise information in the data, is convenient and flexible to use, is suitable for fast data transmission from the data end to the cloud or the local server end, and effectively reduces the data processing cost of the cloud or the local server.

[0099] Example 2

[0100] The device used in this example is the same as that in Example 1, except for the first step in the operation process.

[0101] The first step of the operation process in this example is as follows:

[0102] First step: Open the client application at the data end, directly log in to the cloud service without entering the username and password, and enter the main interface.

[0103] The subsequent steps are the same as those in Example 1.

[0104] In this application, the form of the cloud service is not limited, nor is the form of the client application. In Embodiment 2, the cloud may require the client to fill in more parameters when selecting a task type or not to select a task type. The subsequent task can be initiated before the upload is completed (if the cloud service supports delayed processing). The client can be a browser on the data side, or the function can be integrated into the WEB page provided by the cloud or edge computing device.

[0105] The present invention introduces an edge computing device and a client installed on the data side. The data side uses the client application to call the edge computing device to complete the entire process of mass spectrometry peak extraction, uploading to the cloud or local server, and initiating subsequent calculations to the cloud or local server. This not only eliminates the need for the user to switch to different terminals (data side, local server, cloud server) for operations but also enables the use of the computing resources of the cloud and edge computing devices. The present invention enables the mass spectrometry data on the data side to directly obtain calculation results automatically through the edge computing device, reducing the processing pressure of subsequent calculations and the pressure of uploading to the cloud or local server.

[0106] The above are only several embodiments of this application and do not impose any form of limitation on this application. Although this application is disclosed above with preferred embodiments, it is not intended to limit this application. Any person skilled in the art can make some changes or modifications using the technical content disclosed above within the scope of the technical solution of this application, which are equivalent to equivalent implementation cases and all fall within the scope of the technical solution.

Claims

1. A mass spectrometry data processing system, characterized in that, It includes a client, an edge computing device, a cloud, and a local server; The client is installed on the data side and is used to send a peak extraction request to the edge computing device and obtain a peak extraction result from the edge computing device; the peak extraction request includes peak extraction calculation parameters and mass spectrometry data extracted from the data side; The edge computing device is used to extract mass spectrometry peaks from the mass spectrometry data using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result; The cloud is used to send a request to obtain the peak extraction result to the client or the edge computing device and receive the peak extraction result uploaded by the client or the edge computing device; The local server is used to send a request to obtain the peak extraction result to the client or the edge computing device and receive the peak extraction result uploaded by the client or the edge computing device; The method by which the edge computing device sends the peak extraction result to any one or more of the client, the cloud, and the local server is data-side polling, edge device backhaul, or edge device notification; The operation process of the mass spectrometry data processing system is as follows: First step, open the client on the data side, fill in the cloud service username and password on the login interface, and click OK; Second step, switch to the edge computing device page, enter the IP address and service port number of the edge computing device in the router local area network, enter the peak extraction calculation parameters, and click Connect; Third step, switch to the task initiation interface and click Initiate Task; In the task setting window, click Add File, select the mass spectrometry data file to be batch-processed in the subsequent task, and click OK; in the task setting window, select "Peak Alignment + Differential Analysis" in the task type drop-down box and click Submit Task; Fourth step, after each mass spectrometry data file is published to the edge computing device, it shows that peak extraction is in progress. After successful extraction, it shows extraction success and downloads the result file to the local. Each result file downloaded to the local is added to the task list and shows that it is being uploaded to the cloud. After the upload is complete, it shows upload success; After the same batch of mass spectrometry data files complete the submission to the edge computing, download of the calculation results, and upload to the cloud, the client will automatically send a request to the cloud to perform "Peak Alignment + Differential Analysis" on them.

2. The mass spectrometry data processing system according to claim 1, wherein The edge computing device includes a management unit, a computing unit, and a storage unit; The management unit is used to send the received peak extraction request to the computing unit and control the storage unit to store the peak extraction result output by the computing unit; The computing unit is used to extract mass spectrometry peaks from the mass spectrometry data using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result; The storage unit is used to store the peak extraction result.

3. The mass spectrometry data processing system according to claim 2, wherein The management unit includes a receiving module and a resource pool; The receiving module is used to receive the peak extraction request; The resource pool is used to extract the peak extraction request from the receiving module and send it to the computing unit.

4. The mass spectrometry data processing system according to claim 3, wherein The management unit is also configured to number the received peak extraction request and send the number to any one or more of the client, the cloud, and the local server; Accordingly, the client, the cloud, and the local server obtain the peak extraction result corresponding to the number from the storage unit.

5. The mass spectrometry data processing system according to claim 4, wherein The edge computing device further includes a communication unit; The communication unit is configured to connect the edge computing device to the client, the cloud, and the local server.

6. A method for processing mass spectrometry data of a mass spectrometry data processing system according to any one of claims 1-5, characterized in that, Including: Obtain a peak extraction request sent by a client, where the peak extraction request includes mass spectrometry data and peak extraction calculation parameters; the client is installed on a data terminal containing the mass spectrometry data; Extract mass spectrometry peaks from the mass spectrometry data using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result.

7. The mass spectrometry data processing method according to claim 6, wherein After extracting the mass spectrometry peaks from the mass spectrometry data using the peak extraction algorithm corresponding to the peak extraction calculation parameters to obtain a peak extraction result, it further includes: Receive a request for obtaining a peak extraction result sent by any one or more of the client, the cloud, and the local server, and send the corresponding peak extraction result to the entity that sent the request.

8. The mass spectrometry data processing method according to claim 7, characterized in that After obtaining the peak extraction request sent by the client, it further includes: Number the peak extraction request and send the number to any one or more of the client, the cloud, and the local server; Correspondingly, the step of receiving a request for obtaining a peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the entity that sent the request is specifically: Receive a request for obtaining a peak extraction result containing the number sent by any one or more of the client, the cloud, and the local server; Send the peak extraction result corresponding to the number to the entity that sent the request.

9. The mass spectrometry data processing method according to claim 8, wherein The step of receiving a request for obtaining a peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the entity that sent the request is specifically: Receive a callback request for obtaining a peak extraction result sent by any one or more of the client, the cloud, and the local server, where the callback request includes a number, a callback address, and a callback method; Upload the peak extraction result corresponding to the number to the callback address according to the callback method. Preferably, the step of receiving a request for obtaining a peak extraction result sent by any one or more of the client, the cloud, and the local server, and sending the corresponding peak extraction result to the entity that sent the request is specifically: Receive an automatic notification request sent by any one or more of the client, the cloud, and the local server, where the automatic notification request includes a number; When the number has a corresponding peak extraction result, send a notification to the entity that sent the request. Receive a request for obtaining a peak extraction result initiated by any one or more of the client, the cloud, and the local server; Send the peak extraction result corresponding to the number to the entity that sent the request.

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