An automated analysis platform for high-throughput sequencing data

Abstract

The application discloses a kind of high-throughput sequencing data automatic analysis platform, including user management module, task management module, data management module, result management module and software management module.The application integrates complex high-throughput data analysis and management work into a high-throughput sequencing data automatic analysis platform with strong compatibility, high degree of automation and easy to use.The application platform supports third-party plug-in import, and sequencing data can be automatically / manual called third-party plug-in for analysis.At the same time, the platform also supports automatic management of analysis tasks, avoids resource grabbing, freezing, over memory and other problems due to too many tasks, and prevents data loss through data backup function.The application platform is managed and operated through an interactive interface, which is convenient for non-professionals to operate, greatly reduces the difficulty of high-throughput sequencing technology in clinical and scientific research field application, and is widely applicable to scientific research and clinical high-throughput sequencing data analysis and management work.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of high-throughput sequencing analysis, and particularly relates to a high-throughput sequencing data automatic analysis platform. BACKGROUND

[0002] High-throughput sequencing technology (HTS) has developed rapidly in recent years and has become an indispensable tool in the fields of genomics, transcriptomics and proteomics. Compared with traditional sequencing technology, high-throughput sequencing has the advantages of fast speed and high data output, which enables the rapid generation of massive biological data from the genome to the protein level. However, with the exponential growth of data size, the difficulty of data analysis and processing has also increased significantly.

[0003] In order to cope with this challenge, bioinformatics analysis methods have emerged, aiming to deeply analyze complex biological data through computational algorithms and data processing procedures. However, traditional bioinformatics analysis often relies on manual operation and step-by-step data processing, which is low in efficiency and requires high technical personnel, and is difficult to meet the real-time processing needs of high-throughput sequencing data. SUMMARY

[0004] Therefore, the embodiments of the present application provide a high-throughput sequencing data automatic analysis platform.

[0005] The first aspect of the present application provides a high-throughput sequencing data automatic analysis platform, comprising a user management module, a task management module, a data management module, a result management module and a software management module.

[0006] The user management module is used to control the access users and access rights of the platform.

[0007] The task management module is used to analyze the high-throughput sequencing data by calling analysis plug-ins to form quality control results of the high-throughput sequencing data; wherein a high-throughput sequencing data quality control result contains quality control results of multiple high-throughput sample data.

[0008] The data management module is used to store the quality control results of the high-throughput sequencing data.

[0009] The result management module is used to generate sample quality control reports according to the quality control results of the high-throughput sample data.

[0010] The software management module is used to backup the high-throughput sequencing data quality control results and sample quality control reports.

[0011] Further, the high-throughput sequencing data is uploaded to a sequencing data directory after being sequenced by a sequencer; the high-throughput sequencing data uploaded by the sequencer has identification information, and the platform obtains the high-throughput sequencing data for analysis by identifying the identification information in the sequencing data directory.

[0012] Further, the analysis plug-ins include platform plug-ins and third-party plug-ins; the platform plug-ins are pre-installed in the platform, and the third-party plug-ins are imported from outside;

[0013] The platform obtains the third-party plug-ins imported from outside by the following steps:

[0014] scanning files in the plug-in directory to identify the third-party plug-ins in the plug-in directory;

[0015] storing plug-in data of the third-party plug-ins in the plug-in directory in the platform;

[0016] The plug-in data includes names, versions, parameter items and applicable detection items of the third-party plug-ins, and the task management module calls the third-party plug-ins from the plug-in directory for analysis according to the plug-in data of the third-party plug-ins stored in the platform.

[0017] Further, the task management module calls the analysis plug-ins to analyze the high-throughput sequencing data, and specifically includes the following steps:

[0018] determining detection items of each high-throughput sequencing data;

[0019] According to the detection items, matching the analysis plug-ins corresponding to the detection items for each high-throughput sequencing data for analysis; or

[0020] According to the user input instruction, selecting the analysis plug-ins to analyze the high-throughput sequencing data.

[0021] Further, in the step of selecting the analysis plug-ins to analyze the high-throughput sequencing data according to the user input instruction, the user input instruction can customize and adjust the parameter items of the analysis plug-ins.

[0022] Further, in the step of the task management module calling the analysis plug-ins to analyze the high-throughput sequencing data, the hardware resources of the platform are scheduled by the following steps:

[0023] determining hardware resource occupation of each analysis plug-in and total hardware resources of the platform;

[0024] determining analysis tasks in each time period, combining the analysis tasks arbitrarily to form a plurality of task queues; in the task queues, hardware resource occupation of the analysis plug-ins executing the analysis tasks at the same time does not exceed the total hardware resources of the platform;

[0025] The task management module uses the task queue with the shortest time consumption.

[0026] Further, after the task management module analyzes the high-throughput sequencing data by calling the analysis plug-in, the task management module also outputs log information of the analysis plug-in; the log information records parameter item settings of the analysis plug-in, start time and end time of the analysis plug-in, and quality control results output by the analysis plug-in.

[0027] Further, the quality control results of the high-throughput sequencing data stored by the data management module specifically include sample quantity, sequencing mode, throughput, base quantity, sequencing fragment quantity, Q30%, splitting ratio, cluster density, GC content, and uploading time.

[0028] In the quality control results of the high-throughput sequencing data, the quality control results of each high-throughput sample data specifically include a label of the sample data, a detection item, a base quantity, a sequencing fragment quantity, Q20%, Q30%, and GC content.

[0029] Further, the sample quality control report includes a table form and a chart form, and the sample quality control report is used to represent a change trend of sample data in a sequencing process.

[0030] Further, the platform interacts with a user through multiple operation interfaces; the interactive operation includes inputting an instruction, viewing / downloading / deleting quality control results of high-throughput sequencing data / sample data, running / deleting an analysis plug-in, and data backup.

[0031] Embodiments of the present application have the following beneficial effects: the embodiments of the present application integrate complex high-throughput data analysis and management into a high-throughput sequencing data automatic analysis platform with strong compatibility, high automation, and convenient use. The platform of the embodiments of the present application supports third-party plug-in import, and sequencing data can automatically / manually call third-party plug-ins for analysis. Meanwhile, the platform of the present application also supports automatic management of analysis tasks, avoids problems such as resource grabbing, freezing, and memory overflow due to too many tasks, and prevents data loss through a data backup function. The platform of the embodiments of the present application manages and operates through an interactive interface, is convenient for non-professionals to operate, greatly reduces the difficulty of application of high-throughput sequencing technology in the clinical and scientific research fields, and is widely applicable to high-throughput sequencing data analysis and management in scientific research and clinical fields.

[0032] Additional aspects and advantages of the present application will be described in the following description part, some of which will become apparent from the following description, or will be understood through practice of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0034] Figure 1 is a high-throughput sequencing data automatic analysis platform structure schematic diagram of the present application.

[0035] Figure 2 is a high-throughput sequencing data schematic diagram in the present application.

[0036] Figure 3 is an analysis plug-in schematic diagram in the task management module of the present application.

[0037] Figure 4 is an analysis process schematic diagram of the task management module of the present application.

[0038] Figure 5 is a quality control result schematic diagram of the high-throughput sequencing data recorded by the data management module of the present application.

[0039] Figure 6 is a quality control result schematic diagram of the high-throughput sample data recorded by the data management module of the present application.

[0040] Figure 7 is a log information schematic diagram of the analysis plug-in output by the task management module of the present application.

[0041] Figure 8 is a sample quality control report schematic diagram in the form of a table output by the result management module of the present application.

[0042] Figure 9 is a sample quality control report schematic diagram in the form of a chart output by the result management module of the present application.

[0043] Figure 10 is a data backup effect schematic diagram of the software management module of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0045] The embodiment of the present application is a high-throughput sequencing data automatic analysis platform developed based on the MVC structure (Model-View-Controller). As shown in Figure 1As shown, the platform includes a user management module, a task management module, a data management module, a result management module, and a software management module. A user can log in to access the platform through a browser and perform relevant operations.

[0046] In terms of the user management module, users accessing the platform of the present application mainly include experimenters, bioinformatics analysts, project managers, and software administrators. The embodiment of the present application can control the access rights of various types of access users through the user management module and provide different users with the display of different module control interfaces. The access rights of various types of users are specifically shown in Table 1:

[0047] Table 1

[0048]

[0049] In terms of the task management module, the task management module in the embodiment of the present application is used to analyze high-throughput sequencing data calling analysis plug-ins to form quality control results of high-throughput sequencing data.

[0050] When the sequencer completes the high-throughput sequencing operation, the high-throughput sequencing data as the sequencing result will be uploaded to the designated sequencing directory. Each high-throughput sequencing data corresponds to a sequencing directory. Each high-throughput sequencing data directory contains multiple high-throughput sample data, such as Figure 2 As shown, the high-throughput sample data has specific representation information of "experiment number_detection project_sample number_bar code number", such as Figure 2 The experiment number of the sample data "NIPTSL56_NIPT-BJ215851-MUDI4009" selected in the above table is "NIPTSL56", the detection project is "NIPT", the sample number is "BJ215851", and the bar code number is "MUDI4009".

[0051] The platform of the embodiment of the present application will periodically scan the sequencing directory to obtain the newly uploaded high-throughput sequencing data of the sequencer. By way of example, the scanning period can be set to 10 minutes.

[0052] After the platform imports the high-throughput sequencing data, the analysis plug-in is called for analysis to obtain the high-throughput sequencing result. As shown in the above table, Figure 3 As shown, the analysis plug-in includes platform plug-ins and third-party plug-ins, the platform plug-ins are pre-installed in the platform, and the third-party plug-ins are imported from the outside. The plug-in pre-installed in the platform of the embodiment of the present application is "fastp_plugin", and the remaining plug-ins are imported into the platform from the outside by the bioinformatics analyst or the project manager. Specifically, the bioinformatics analyst or the project manager places the third-party plug-in to be installed in the preset plug-in directory, and the platform will periodically scan the plug-in directory to obtain the newly installed third-party plug-in or update the version of the third-party plug-in.

[0053] After the platform acquires the third-party plug-in, the platform synchronizes plug-in data of the third-party plug-in to the platform. The plug-in data specifically includes "auto.sh", "config.txt", "project.txt", "version.txt", etc., wherein "auto.sh" contains a main program entry of plug-in running, config.txt contains parameters supported by the plug-in for customization, project.txt contains detection projects adapted by the plug-in, and version.txt contains version information of the plug-in.

[0054] In the embodiment of the application, the task management module calls the analysis plug-in to analyze the high-throughput sequencing data, including two processes of automatic analysis and manual analysis. As shown in Figure 4 In the automatic analysis process, the task management module matches corresponding analysis plug-ins for analysis according to the detection project identifier in the high-throughput sequencing data. For example, data identified by NIPT (Non-invasive Prenatal Testing) in the high-throughput sequencing data is matched to the T21_plugin analysis plug-in for analysis. Through the T21_plugin analysis plug-in, the sequencing data is analyzed to obtain a screening result of fetal chromosomal abnormalities. In the manual analysis process, the user can submit an analysis task through a corresponding front-end interface, and the task management module uses the analysis plug-in set by the task to analyze the high-throughput sequencing data. As a preferred embodiment, the user can further set the custom parameters of the plug-in when submitting the analysis task, for example, the T21_plugin analysis plug-in can set the number of CPUs used and the number of memories used by each CPU.

[0055] In the process of calling the analysis plug-in by the platform to analyze the high-throughput sequencing data, the user can query and manage the analysis process through the corresponding front-end interface, or send a stop analysis instruction to stop the analysis plug-in from analyzing the high-throughput sequencing data.

[0056] As a preferred embodiment, in the process of calling the analysis plug-in by the platform to analyze the high-throughput sequencing data, the hardware resources of the platform can be scheduled to prevent resource occupation between different analysis tasks, causing insufficient memory or lag of the platform. In the embodiment of the application, the Slurm software is used to schedule the hardware resources of the platform. Slurm (Simple Linux Utility for Resource Management) is an open-source task scheduling system and cluster management software, which can allocate CPU cores, memories, disk spaces and other resources according to the needs of tasks to optimize different types of tasks, such as parallel tasks, batch processing tasks, etc. As a specific embodiment, the Slurm software schedules the hardware resources of the platform through the following steps:

[0057] Determine the hardware resource consumption of each analysis plugin and the total hardware resources of the platform;

[0058] The analysis tasks for each time period are determined, and the analysis tasks are arbitrarily combined to form multiple task queues. In the task queue, the hardware resource consumption of the analysis plug-in executing the analysis task at the same time does not exceed the total hardware resource of the platform.

[0059] Select the task queue with the shortest execution time for the task management module to use.

[0060] After the analysis is complete, the task management module will output the quality control results of the high-throughput sequencing data to the data management module. A diagram illustrating the quality control results of the high-throughput sequencing data is shown below. Figure 5 As shown, the quality control results include sample quantity, sequencing mode, throughput, base count, number of sequencing fragments, Q30% (percentage of samples with a quality score ≥30), split ratio, cluster density, GC content, and upload time. Users can view the quality control results of high-throughput sequencing data through the front-end interface of the data management module. Since a single high-throughput sequencing dataset contains multiple high-throughput sample data sets, clicking the "Details" button in the quality control results section allows further viewing of the quality control results for individual high-throughput sample data sets. Figure 6 As shown, the quality control results of high-throughput sample data specifically include the sample data's barcode, detection items, number of bases, number of sequencing fragments, Q20% (the percentage of quality values ​​≥20), Q30%, and GC content, etc.

[0061] In some embodiments, the task management module also outputs logs for the corresponding analysis plugins when completing the analysis task. For example... Figure 7 As shown, the log information records the parameter settings of the analysis plugin, the plugin's start time, end time, and the quality control results output by the plugin. Users can use the log information to determine whether the analysis task was completed normally and to retrieve errors that occurred during the analysis process.

[0062] After the task management module completes the analysis task, the results management module generates a detailed sample quality control report based on the quality control results of the high-throughput sample data. The quality control report includes both tabular and graphical formats. The tabular format is as follows: Figure 8 As shown, the chart format is as follows Figure 9 As shown, the sample quality control report provides a detailed description of the high-throughput sample data. For example... Figure 8 The table shown contains information such as the analysis plugin version corresponding to the sample data, sequencing mode, average read length before filtering, average read length after filtering, repetition rate, cumulative read length distribution, adapter sequence 1, adapter sequence 2, number of sequencing fragments, number of bases, Q20%, Q30%, etc. Figure 9The chart shows the proportion of ATCG bases in each cycle of the sequencing order after filtering. When analyzing certain sample data, the user can further understand the high-throughput sample data through the sample quality control generated by the result management module.

[0063] After the task management module completes the analysis task, the software management module backs up the high-throughput sequencing data quality control results and sample quality control reports. As shown in the figure, Figure 10 As shown, the backup interface can back up data and download data with one click, which is convenient for users to use the platform of the embodiment of the application.

[0064] The platform of the embodiment of the application interacts with the user through multiple operation interfaces. The supported interactive operations include inputting instructions, viewing / downloading / deleting high-throughput sequencing data / sample data quality control results, running / deleting analysis plugins, and data backup, which facilitates non-professionals to operate and greatly reduces the difficulty of application of high-throughput sequencing technology in the clinical and scientific research fields.

[0065] The following is the processing flow of a specific high-throughput sequencing data of the platform of the embodiment of the application:

[0066] S1. Use the non-invasive fetal chromosomal abnormality detection kit matched with the sequencer to sequence 96 high-throughput samples, and transfer the sequencing results to the server of the platform of the application in the form of sftp.

[0067] S2. The platform server automatically scans the program at regular intervals, identifies the newly uploaded high-throughput sequencing data, organizes the data information, transfers it to the platform background database, and automatically starts the quality control program fastp_plugin.

[0068] S3. The platform background identifies that the detection project type of the high-throughput sequencing data is NIPT, retrieves the plugin, finds that it matches T21_plugin, and automatically runs T21_plugin to analyze the data.

[0069] S4. After the quality control data performed by the fastp_plugin plugin is completed, the quality control results of the high-throughput sequencing data can be seen, and clicking the sample data number will pop up the detailed quality control results of each sample data.

[0070] S5. After the T21_plugin plugin completes the analysis task, the log information of the running of the plugin program can be seen in the log information.

[0071] In summary, through the development and specification of a series of automatic programs, the platform of the embodiment of the application can automatically complete quality control and analysis of the sequencing data of the sequencer without human intervention, simplify the difficulty of clinical application of gene sequencing technology, and improve the efficiency of clinical testing.

[0072] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the embodiments of the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

[0073] Those skilled in the art can understand that the modules in the device in the embodiments of the present application can be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments of the present application can be combined into one module or unit or component, and furthermore can be divided into multiple sub-modules or sub-units or sub-components. All features disclosed in the specification (including the corresponding claims, abstract and drawings) and all processes or units of any method or device disclosed in this way can be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless explicitly stated otherwise, each feature disclosed in the specification (including the corresponding claims, abstract and drawings) can be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0074] Through the description of the above embodiments, those skilled in the art can understand that, for the convenience and brevity of description, only the division of the above functional modules is taken as an example, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0075] Note that the logic and / or steps represented and / or otherwise described herein in flow chart form represent executable instructions, for example, that can be sequenced to implement logic functionality, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from a medium and execute the instructions. For purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can specifically include the following: an electronic connection (an electronic device having one or more wires), a portable computer diskette (a magnetic device), a random-access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or other suitable medium upon which the program is printed, as the program can be electronically captured, for example, via an optical scanner, then compiled, interpreted, or otherwise processed in the electronic manner into a useable form, and then stored in the computer memory.

[0076] In addition, each of the various embodiments described in this specification has been described as if specific implementations only are envisioned. However, the person skilled in the art will understand that the various embodiments described in this specification can be combined with each other, unless specifically noted. In addition, the person skilled in the art will understand that the various embodiments described in this specification can be implemented by means of a computer program product. Accordingly, those program elements that can be necessary for realizing the various embodiments and their functions can be stored at a medium and supplied to a relevant device or unit according to the particular case, in order to be executed by the latter. Therefore, the computer program itself can fully and specifically implement the embodiments in question, independently of the software and / or hardware on which it is executed. In addition, the person skilled in the art will understand that the various embodiments described in this specification can be implemented by means of a cloud computing model. Therefore, the cloud computing resources can fully and specifically implement the embodiments in question, independently of the software and / or hardware on which it is executed.

[0077] It should be understood that aspects of the application can be implemented in hardware, software, firmware or a combination thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, and in another embodiment, any of the following can be used: discrete logic circuitry having logic gates for implementing logic functions upon data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and / or the like.

[0078] In the description of the present application, the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like, are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. The appearances of the above terms in various places in the specification are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0079] In addition, the terms "first", "second", and the like, in the description of the embodiments of the present application, are used for descriptive purposes and not necessarily for describing all embodiments, or implying relative importance or implicitly dictating the order of elements mentioned in this embodiment. Therefore, the features defined with "first", "second" and the like in the embodiments of the present application can explicitly or implicitly indicate that the embodiments include at least one of the features. In the description of the present application, the term "a plurality of" means at least two or two or more, such as two, three, four, etc., unless otherwise specifically limited in the embodiments.

[0080] In the embodiments of the present application, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element, in addition, components, features, elements with the same name in different embodiments of the present application can have the same meaning or different meaning, and the specific meaning thereof should be determined in the interpretation of the specific embodiment or further combined with the context in the specific embodiment.

[0081] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and that variations, modifications, substitutions and changes can be suggested to one skilled in the art without departing from the scope of the present application. Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the present application. It is intended that the present application cover any and all variations of the application that come within the scope of the present application, along with all of the equivalents thereof. It is intended that the specification and examples be considered exemplary only, with the true scope and spirit of the application indicated by the following claims.

Claims

1. A high-throughput sequencing data automated analysis platform, characterized in that, The platform comprises a user management module, a task management module, a data management module, a result management module and a software management module. The user management module is configured to control access users and access permissions of the platform. The task management module is configured to call analysis plug-ins to analyze high-throughput sequencing data, and form quality control results of the high-throughput sequencing data; wherein one high-throughput sequencing data quality control result comprises quality control results of multiple high-throughput sample data. The data management module is configured to store the quality control results of the high-throughput sequencing data. The result management module is configured to generate sample quality control reports according to the quality control results of the high-throughput sample data. The software management module is configured to back up the high-throughput sequencing data quality control results and the sample quality control reports. The analysis plug-ins comprise platform plug-ins and third-party plug-ins; the platform plug-ins are pre-installed in the platform, and the third-party plug-ins are imported from outside. The platform obtains the third-party plug-ins imported from outside through the following steps: scanning files in a plug-in directory to identify third-party plug-ins in the plug-in directory; storing plug-in data of the third-party plug-ins in the plug-in directory in the platform; The plug-in data comprises names, versions, parameter items and applicable detection items of the third-party plug-ins; the task management module calls the third-party plug-ins from the plug-in directory to analyze according to the plug-in data of the third-party plug-ins stored in the platform. After the task management module calls analysis plug-ins to analyze high-throughput sequencing data, and forms quality control results of the high-throughput sequencing data, the task management module also outputs log information of the analysis plug-ins; the log information records parameter item settings of the analysis plug-ins, start time, end time of the analysis plug-ins and quality control results output by the plug-ins.

2. The high-throughput sequencing data automated analysis platform of claim 1, wherein, The high-throughput sequencing data is uploaded to a sequencing data directory after being sequenced by a sequencer; the high-throughput sequencing data uploaded by the sequencer has identification information; the platform obtains the high-throughput sequencing data for analysis by identifying the identification information in the sequencing data directory.

3. The high-throughput sequencing data automated analysis platform of claim 1, wherein, The task management module calls analysis plug-ins to analyze high-throughput sequencing data, specifically comprising the following steps: determining detection items of each high-throughput sequencing data; matching analysis plug-ins corresponding to the detection items for each high-throughput sequencing data according to the detection items for analysis; or selecting analysis plug-ins to analyze high-throughput sequencing data according to user input instructions.

4. The high-throughput sequencing data automated analysis platform of claim 3, wherein, In the step of selecting analysis plug-ins to analyze high-throughput sequencing data according to user input instructions, the user input instructions can be used to customize adjustment of parameter items of the analysis plug-ins.

5. The high-throughput sequencing data automated analysis platform of claim 1, wherein, In the step of the task management module calling analysis plug-ins to analyze high-throughput sequencing data, the hardware resources of the platform are scheduled through the following steps: determining hardware resource occupation of each analysis plug-in and total hardware resources of the platform; determining analysis tasks in each time period, combining the analysis tasks in any way to form multiple task queues; in the task queues, hardware resource occupation of analysis plug-ins executing analysis tasks at the same time does not exceed the total hardware resources of the platform; selecting a task queue with the shortest time consumption for use by the task management module.

6. The high-throughput sequencing data automated analysis platform of claim 1, wherein, The data management module stores the quality control results of the high-throughput sequencing data, specifically including sample quantity, sequencing mode, throughput, base quantity, sequencing fragment quantity, Q30%, splitting ratio, cluster density, GC content and uploading time; In the quality control results of the high-throughput sequencing data, the quality control results of each high-throughput sample data specifically include the label, detection item, base quantity, sequencing fragment quantity, Q20%, Q30% and GC content of the sample data.

7. The high-throughput sequencing data automated analysis platform of claim 6, wherein, The sample quality control report includes table form and chart form, and the sample quality control report is used to characterize the change trend of sample data in the sequencing process.

8. The high-throughput sequencing data automated analysis platform according to any one of claims 1-7, wherein, The platform interacts with the user through multiple operation interfaces; the interaction operation includes input instruction, viewing / downloading / deleting high-throughput sequencing data / sample data quality control results, running / deleting analysis plug-in and data backup.

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